My research group website:
Students (see all)
Austin Wright, ML PhD
Seongmin Lee, CS PhD
Anthony Peng, CS PhD
Ben Hoover, ML PhD
Matthew Hull, ML PhD
Alec Helbling, ML PhD
Mansi Phute, CS PhD
Aeree Cho, ML PhD
Alex Yang, CS UG
Pratham Mehta, CS BS
Aishwarya Chakravarthy, CS BS
Sri Ranganathan Palaniappan, CS BS- Chae Yeong (Grace) Kim, CS BS
Rahul Narayanan, CS BS
Kunal Mohindra, CS BS
Recent Alumni (see all)
Zijie (Jay) Wang, ML PhD
Haekyu Park, CS PhD
Harsha Karanth, CS MS
David Munechika, CS BSMS- Evan Montoya, CS BS
Chakri RVK. Analytics MS
Megan Dass, CS UG
Kevin Li, CS UG
Sivapriya Vellaichamy, Analytics MS
Omar Shaikh, CS UG
Zhiyan (Frank) Zhou, CS UG
Rahul Duggal, CS PhD
Nilaksh Das, CSE PhD
Scott Freitas, ML PhD
Jonathan Leo, CS BS/MS
Fred Hohman, CSE PhD
Teaching
CSE6242/CX4242:
Data & Visual Analytics
Every semseter. Online + Campus.
Funding & Support
Our research made possible by support and funding from:
NSF (RI, 2403297, CNS 1704701, IIS 1563816, OISE 2246298, IIS 1551614, TWC 1526254, IIS1217559, CMMI 1935551, EAGER IIS 1745382),
NIH (1-U54EB020404-01),
DARPA (GARD, ADAMS),
NASA,
Children's Healthcare of Atlanta,
Google, Intel, Nvidia, Cisco, ADP, Amazon, Avast, Microsoft Research, Meta (Facebook), Bosch, Gen (Symantec), Yahoo, Fiddler Labs, eBay, LogicBlox,
LexisNexis Dean's Award,
James Edenfield Faculty Fellowship,
Raytheon Faculty Fellowship
Polo Chau
Legal name:
Duen Horng Chau
Duen Horng Chau
Professor,
School of Computational Science & Engineering
Associate Director, MS in Analytics
Director of Industry Relations, The Institute for Data Engineering and Science
Associate Director of Corporate Relations, The Center for Machine Learning
Georgia Tech
Associate Director, MS in Analytics
Director of Industry Relations, The Institute for Data Engineering and Science
Associate Director of Corporate Relations, The Center for Machine Learning
Georgia Tech
polo
gatech.edu
faculty.cc.gatech.edu/~dchau
gatech.edu
faculty.cc.gatech.edu/~dchau Please read our FAQ if you are interested in joining my group.
Positions
Aug 2024 -
Professor
School of Computational Science & Engineering, Georgia Tech
School of Computational Science & Engineering, Georgia Tech
Jul 2021 -
Adjunct Associate Professor
School of Interactive Computing, Georgia Tech
School of Interactive Computing, Georgia Tech
Oct 2019 -
Director of Industry Relations
Institute for Data Engineering and Science (IDEaS), Georgia Tech
Institute for Data Engineering and Science (IDEaS), Georgia Tech
Oct 2019 -
Associate Director of Corporate Relations for Machine Learning
The Center for Machine Learning, Georgia Tech
The Center for Machine Learning, Georgia Tech
Aug 2018 - Aug 2024
Associate Professor
School of Computational Science & Engineering, Georgia Tech
School of Computational Science & Engineering, Georgia Tech
May 2014 -
Associate Director
MS in Analytics, Georgia Tech
MS in Analytics, Georgia Tech
Aug 2018 - Aug 2021
Machine Learning Area Leader
College of Computing, Georgia Tech
College of Computing, Georgia Tech
Aug 2012 - Aug 2018
Assistant Professor
School of Computational Science & Engineering, Georgia Tech
School of Computational Science & Engineering, Georgia Tech
Dec 2012 - Dec 2015
Adjunct Assistant Professor
School of Interactive Computing, Georgia Tech
School of Interactive Computing, Georgia Tech
Education
Aug 2012
Ph.D. Machine Learning Carnegie Mellon University
Thesis: Data Mining Meets HCI: Making Sense of Large Graphs
Award: Carnegie Mellon SCS Dissertation Award, Honorable Mention
Committee: Christos Faloutsos, Jason Hong, Niki Kittur, Jiawei Han (UIUC)
Watch my defense video on YouTube.
Thesis: Data Mining Meets HCI: Making Sense of Large Graphs
Award: Carnegie Mellon SCS Dissertation Award, Honorable Mention
Committee: Christos Faloutsos, Jason Hong, Niki Kittur, Jiawei Han (UIUC)
Watch my defense video on YouTube.
May 2010
M.S. Machine Learning Carnegie Mellon University
Aug 2005
Masters of Human-Computer Interaction Carnegie Mellon University
2004
B.Eng. Information Engineering (Honors) The Chinese Univ. of Hong Kong
Online Auction Fraud Detection
Advisor: Prof. Soung-Chang Liew
Online Auction Fraud Detection
Advisor: Prof. Soung-Chang Liew
2000
Diocesan Boys' School (high school) Hong Kong
Research Areas and Thrusts
My research group Polo Club of Data Science innovates at the intersection of machine learning and visualization to synthesize scalable, interactive, and trustworthy tools that amplify human’s ability to understand and interact with billion-scale data and machine learning models.
Our research thrusts include: human-centered AI (interpretable, safe, fair AI; adversarial ML), large graph visualization and mining, cybersecurity and social good.
See all our projects at our group website. Some highlights:
AI Explainers for Everyone:
Transformer Explainer (VIS Best Poster; went viral),
Diffusion Explainer (went viral),
and CNN Explainer helps beginners learn deep learning models (went viral; invited to SIGGRAPH),
Dodrio
compares NLP attention mechanisms with linguistic knowledge,
GAN Lab
visualizes how generative adversarial network (GAN) works (went viral; with Google),
ActiVis
enables visual exploration of industry-scale deep neural networks
(deployed on Meta's ML platform used by 25% engineers; invited to SIGGRAPH),
ManimML (IEEE VIS Best Poster; went viral) communicates ML architectures with animation,
Communicating with Interactive Articles examines interactive article design by synthesizing theory from education, journalism, and visualization.
Scalable Visual Discovery for Trustworthy and Interpretable AI: Summit and NeuroCartography scalably summarize and visualize learned concepts, Bluff pinpoints model vulnerabilities, FairVis visually discovers ML bias, Recast audits toxicity detection models, comprehensive survey on visual analytics for deep learning (best for practitioners and new researchers), industry human-AI guidelines comparision.
Protecting AI models: ShapeShifter the first targeted physical attack (highlighted by DARPA as state-of-the-art; with Intel), SHIELD fast and practical defense (KDD Audience Appreciation Award, Runner-up), SkeletonVis reveals temporal and spatial incoherence of attacks, UnMask protects deep learning through robust feature alignment, robust accented speech recognition (with Amazon AWS AI), REST for robust sleep monitoring, ADAGIO for audio defense.
Novel datasets and tools: TIGER for evaluating graph robustness (part of Nvidia Data Science teaching kit), MalNet the largest graph- and image-based security datasets, PEGASUS billion-scale graph mining (Open Source Software World Challenge, Silver Award).
Social good (education, health, human trafficking): Firebird for fire risk prediction (KDD Best Student Paper, Runner-up; with Atlanta Fire Rescue Department), Chronodes for mobile health visual data exploration (ACM TiiS Best Paper, Honorable Mention), CardiacAR for mixed-reality heart surgical planing (with Children's Healthcare of Atlanta), augmented coding (Best Poster, Chinese CHI), mixed-reality for learning programming (IDC Best Work-in-Progress, Honorable Mention), TrafficVis fights human trafficking (VIS Best Poster, Honorable Mention), Argo Scholar for literature exploration in browsers (VIS Best Poster, Honorable Mention), extends Argo Lite, Autograding of D3 visualizations (VIS Best Poster), EnergyVis explores ML model energy consumption, PeopleMap (VIS Best Poster, Honorable Mention), Magic Crop (auto-magically cropping headshot photos)
Cybersecurity & fraud detection: Polonium and Aesop malware detection over 37 billion machine-file relationships (patented and deployed by Symantec; protects 120 million people), Marco (SDM Best Student Paper), NetProbe eBay auction fraud detection (covered by WSJ, USA Today, Washington Post, LA Times, etc.), LatentGesture mobile authentication via touch signatures (covered by Wired, Engadget, Gizmodo, Yahoo News, Atlanta Business Chronicle, etc.), D2M detects adversarial movements in networks (with Microsoft), insider trading pattern discovery (with Securities and Exchange Commission), FairPlay (fraud and malware detection on Google Play).
Large graph visualization and mining: Apolo and Facets for mixed-initiative large graph sensemaking, Visage enables interactive visual graph querying, without writing complex code (SIGMOD Best Demo, Honorable Mention) Vigor summarizes query results.
Scalable Visual Discovery for Trustworthy and Interpretable AI: Summit and NeuroCartography scalably summarize and visualize learned concepts, Bluff pinpoints model vulnerabilities, FairVis visually discovers ML bias, Recast audits toxicity detection models, comprehensive survey on visual analytics for deep learning (best for practitioners and new researchers), industry human-AI guidelines comparision.
Protecting AI models: ShapeShifter the first targeted physical attack (highlighted by DARPA as state-of-the-art; with Intel), SHIELD fast and practical defense (KDD Audience Appreciation Award, Runner-up), SkeletonVis reveals temporal and spatial incoherence of attacks, UnMask protects deep learning through robust feature alignment, robust accented speech recognition (with Amazon AWS AI), REST for robust sleep monitoring, ADAGIO for audio defense.
Novel datasets and tools: TIGER for evaluating graph robustness (part of Nvidia Data Science teaching kit), MalNet the largest graph- and image-based security datasets, PEGASUS billion-scale graph mining (Open Source Software World Challenge, Silver Award).
Social good (education, health, human trafficking): Firebird for fire risk prediction (KDD Best Student Paper, Runner-up; with Atlanta Fire Rescue Department), Chronodes for mobile health visual data exploration (ACM TiiS Best Paper, Honorable Mention), CardiacAR for mixed-reality heart surgical planing (with Children's Healthcare of Atlanta), augmented coding (Best Poster, Chinese CHI), mixed-reality for learning programming (IDC Best Work-in-Progress, Honorable Mention), TrafficVis fights human trafficking (VIS Best Poster, Honorable Mention), Argo Scholar for literature exploration in browsers (VIS Best Poster, Honorable Mention), extends Argo Lite, Autograding of D3 visualizations (VIS Best Poster), EnergyVis explores ML model energy consumption, PeopleMap (VIS Best Poster, Honorable Mention), Magic Crop (auto-magically cropping headshot photos)
Cybersecurity & fraud detection: Polonium and Aesop malware detection over 37 billion machine-file relationships (patented and deployed by Symantec; protects 120 million people), Marco (SDM Best Student Paper), NetProbe eBay auction fraud detection (covered by WSJ, USA Today, Washington Post, LA Times, etc.), LatentGesture mobile authentication via touch signatures (covered by Wired, Engadget, Gizmodo, Yahoo News, Atlanta Business Chronicle, etc.), D2M detects adversarial movements in networks (with Microsoft), insider trading pattern discovery (with Securities and Exchange Commission), FairPlay (fraud and malware detection on Google Play).
Large graph visualization and mining: Apolo and Facets for mixed-initiative large graph sensemaking, Visage enables interactive visual graph querying, without writing complex code (SIGMOD Best Demo, Honorable Mention) Vigor summarizes query results.
Awards & Honors (my students' awards)
2025
Dean's Award for Faculty, for establishing Georgia Tech's AI leadership for College of Computing
2024
Innovator Award, MS Analytics 10 Year Anniversary
2024
IEEE VIS Best Poster Award, for Transformer Explainer
2024
KDD Best Paper, Runner-up (Applied Data Science) for Nested Fusion
2024
SIGIR Best Short Paper, Honorable Mention for MeMemo
2023
Google Research Award, for Scaling Up Educators' Capacities: Automating Visualization Assessment via Generative AI
2023
BMVC Best Poster, for Robust Principles
2023
IEEE VIS Best Poster Award, for ManimML
2023
ACL Best Paper, Honorable Mention, for DiffusionDB
2023
Senior Faculty Outstanding Undergraduate Research Mentor Award. Georgia Tech.
2022
IEEE VIS Best Paper, Honorable Mention, for TrafficVis
2022
Outstanding Mid-Career Faculty Research Award. College of Computing, Georgia Tech.
2022
NeuroCartography selected to present at SIGGRAPH’22 as a top IEEE VIS'21 paper (top 1% of 442 submissions)
2021
Best Paper Award, NeurIPS 2021 Workshop on Bridging the Gap: From Machine Learning Research to Clinical Practice (Research2Clinics), for GAM Changer
2021
IEEE VIS Best Poster Award, for autograding of D3 visualization
2021
IEEE VIS Best Poster Honorable Award, for Argo Scholar
2021
IEEE VIS Best Poster Honorable Mention, for TrafficVis
2020
IEEE VIS Best Poster Research Award, Honorable Mention (VAST track), for PeopleMap
2020
Facebook Faculty Research Award. PIs: Srijan Kumar, Polo Chau
2020
CNN Explainer selected to present at SIGGRAPH’21 as the only top IEEE VAST'20 paper
2019
Intel Outstanding Researcher Award
2019
IDC 2019 Best Work-in-Progress, Honorable Mention
2018
ACM TiiS 2018 Best Paper, Honorable Mention
2018
Chinese CHI 2018 Best Poster
2018
KDD Audience Appreciation Award, Runner-up
2018
James D. Lester III Family Award. College of Computing, Georgia Tech.
2018
ActiVis selected to present at SIGGRAPH’18 as the top IEEE VAST'17 paper
2017
SIGMOD 2017 Best Demo, Honorable Mention
2016
KDD 2016 Applied Data Science Best Student Paper, Runner-up
2015
Google Faculty Research Award.
2015
Outstanding Junior Faculty Research Award. College of Computing, Georgia Tech.
2015-16
James Edenfield Faculty Fellowship, with Munmun De Choudhury (IC)
2014
Yahoo Faculty Research and Engagement Program (FREP) Award by Yahoo! Labs. (GT press releases 1 & 2)
2014-15
Raytheon Faculty Fellowship, with Rahul Basole (IC).
2014
SIAM Data Mining (SDM) 2014 Best Student Paper award
2014
LexisNexis Dean's Excellence Award
2012
Carnegie Mellon School of Computer Science Dissertation Award, Honorable Mention
2010
Open Source Software World Challenge, Silver Award (3rd place), for the PEGASUS project which mines billion-node graphs. U Kang, Duen Horng Chau, Christos Faloutsos
2009 - 2010
Symantec Research Labs Graduate Fellowship, covers full tuition and stipend (in addition to the previous fellowship). Re-selected, as one of the only three graduate students worldwide to receive the award.
2009
Yahoo! Key Scientific Challenges Award, in Information Retrieval, Algorithms, and Data Mining. Awarded as one of the 20 graduate student nationwide, with a gift of $5,000 unrestricted research fund.
2008 - 2009
Symantec Research Labs Graduate Fellowship, covers full tuition and stipend.
Selected as one of the only two graduate students to receive the award. Featured on: The Wall Street Journal, MSN Money, CNNMoney.com, The Pittsburgh Tribune-Review, Fox Business, AOL Money & Finance, MSNBC Business.
2008
Winner, Symantec research competition (internal).
2006
Best Presentation Award, 3rd Place, PKDD'06.
2001, 2002, 2003
Dean's List
2002, 2003
Nominated for university scholarships
Industry Positions & Experiences
Summer 2014
eBay, Search Science San Jose
Visiting Professor
Visiting Professor
Summer - Fall 2011
Google, Ads Backend Team Mountain View, CA
Ph.D. Software Engineer Intern Mentor: Dr. Arun Swami
Ph.D. Software Engineer Intern Mentor: Dr. Arun Swami
Fall 2009
Symantec Research Labs Los Angeles, CA
Ph.D. Research Intern Mentor: Mr. Carey Nachenberg
Ph.D. Research Intern Mentor: Mr. Carey Nachenberg
Summer 2008
Symantec Research Labs Los Angeles, CA
Ph.D. Research Intern Mentor: Mr. Darren Shou
Ph.D. Research Intern Mentor: Mr. Darren Shou
2005 - 2007
Carnegie Mellon University, Human-Computer Interaction Institute Pittsburgh, PA
Research Associate Supervisor: Prof. Brad Myers
Research Associate Supervisor: Prof. Brad Myers
Summer 2003
The Chinese University of Hong Kong, Lightwave Communications Lab Hong Kong
Undergraduate Research Assistant
Undergraduate Research Assistant
2002 - 2007
Elfware Company Hong Kong
System Consultant
System Consultant
Outreach Invited Talks & Activities
Nov 10, 2023
Mentor, EECS Rising Stars
Mar 18, 2021
Perspectives on the state-of-the-art visual analytics. NSF convergence meeting on Analysis & Visualization for The Future of Quantitative Research in the Social Sciences. Host: Prof. Lisa Singh, Computer Science, Georgetown University.
Mar 17, 2021
Towards Secure and Interpretable AI: Scalable Methods, Interactive Visualizations, and Practical Tools. American Physical Society (APS) March Meeting 2021.
May 22, 2021
Working and Studying Aboard (in USA). Information Engineering Alumni Association (IEAA), The Chinese University of Hong Kong. Host: Albert Au Yeung.
Nov 10, 2020
IDEaS panel on Getting Started in Data Science and Machine Learning (panelist), Georgia Tech
July 28, 2020
Teaching Databricks in the Classroom
May 27, 2020
Education panel on Visualization for Data Science (panelist), Eurographis & EuroVis 2020
Mar 20, 2020
Accelerated Data Science in the Classroom: Teaching Analytics and Machine Learning with RAPIDS at Nvidia GPU Technology Conference (GTC) 2020.
Dec 12, 2019
Ask A Prof! inaugural blog post of On Teaching and Learning @ Georgia Tech
Jul 9, 2019
Undergraduate Research Faculty Panel (panelist), Georgia Tech
Jun 4, 2019
Visual Data Analytics tutorial. Smart Grid Edge Analytics Workshop, Georgia Tech
Aug 8, 2019
Visual Data Analytics tutorial. Foundation of Data Science – Summer School 2019, Georgia Tech
Sept 26, 2018
Hands-on augmented reality (AR) research demonstration for elementary school students from Charles R. Drew Charter School, using Microsoft HoloLens
Aug 6, 2018
Introduction to Machine Learning.
Summer workshop on data and scientific computing, Georgia Tech
Aug 1, 2017
Introduction to Machine Learning.
Summer workshop on data and scientific computing, Georgia Tech
Mar 6, 2017
Apr 16, 2016
10 Lessons Learned
from Working with Tech Companies.
Hacklytics, organized by Georgia Tech undergraduate students.
Jun 16, 2015
The Internet of Things (IoT) Joins the Enterprise: Strategies for Managing & Using All That Data.
All Analytics Academy.
May 21, 2015
Catching Bad Guys with Graph Mining and Visualization.
Center of Academic Excellence (NSA)
Jun 13, 2014
Graph Mining meets Human-Computer Interaction.
DIMACS REU Tutorial.
Rutgers University.
Jun 20, 2013
Making sense of big data: combining data mining and visualization
Teachers Workshop (CS Principles - Big Ideas), organized by Institute for Computing Education (ICE), a partnership between the Georgia Department of Education and the College of Computing at Georgia Tech.
Teaching
Courses
CSE6242/CX4242: Data and Visual Analytics, Georgia Tech. 1000+ students enrolled in each recent semester. Teaching it since 2013.
Computing for Data Analytics: Methods and Tools, CSE 6040, Fall 2014. Georgia Tech. Co-taught with Dr. Da Kuang.
Bee-Snap, an undergraduate cross-semester VIP project course (Vertically Integrated Projects).
Georgia Tech.
ECE-2811-VV4, ECE-3811-VV4, ECE-3812-VV4, ECE-4811-VV4, ECE-4812-VV4.
Introduction to Computational Science and Engineering. CSE 6001, Fall 2013, Georgia Tech. Co-taught with Rich Vuduc.
Tutorials
HCI Meets Data Mining: Principles and Tools for Big Data Analytics.
Polo Chau.
ACM Conference on Human Factors in Computing Systems (CHI) 2014.
Toronto, Canada.
April 24-May 1, 2014.
Big Graph Mining for the Web and Social Media.
U Kang, Leman Akoglu, Polo Chau.
The 7th ACM International Conference on Web Search and Data Mining (WSDM2014). New York City. February 24, 2014.
Big Graph Mining: Algorithms, Anomaly Detection, and Applications.
U Kang, Leman Akoglu, Polo Chau.
The 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). Niagra Falls, Canada, Aug 25-28, 2013.
PhD Consort. Mentor
Guest lectures
Information Visualization (CS7450). Instructor: Prof. Alex Endert. Fall 2014. Georgia Tech.
Data Mining for Malware Detection and Fraud Detection. Computing and Society (CS 4001).
Instructor: Prof. Jimeng Sun. Spring 2014. Georgia Tech.
Web-scale malware detection & fraud detection, and Interactive graph exploration & mining for Massive Graph Analytics (CSE 8803 MGA). Instructor: Prof. David Bader. Fall 2012. Georgia Tech.
Data Warehousing and Data Mining for Database Applications (15-415).
Instructor: Prof. Christos Faloutsos. Spring 2012. Carnegie Mellon University.
Instructor: Prof. Christos Faloutsos. Spring 2012. Carnegie Mellon University.
Web Search for Science of the Web (15-396).
Instructor: Prof. Luis von Ahn, Brendan Meeder. Fall 2011. Carnegie Mellon University.
Instructor: Prof. Luis von Ahn, Brendan Meeder. Fall 2011. Carnegie Mellon University.
Making Sense of Large Networks for Sensemaking: Cognitive, Social, and Technical Perspectives (05-899).
Instructor: Prof. Niki Kittur. Spring 2011. Carnegie Mellon University.
Instructor: Prof. Niki Kittur. Spring 2011. Carnegie Mellon University.
Teaching Assistant
Science of the Web (15-396).
Instructor: Prof. Luis von Ahn, Brendan Meeder. Fall 2011. Carnegie Mellon University.
Instructor: Prof. Luis von Ahn, Brendan Meeder. Fall 2011. Carnegie Mellon University.
Multimedia Databases and Data Mining (15-826).
Instructor: Prof. Christos Faloutsos. Spring 2010. Carnegie Mellon University.
Instructor: Prof. Christos Faloutsos. Spring 2010. Carnegie Mellon University.
Publications
Conference
ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features.
Alec Helbling, Tuna Han Salih Meral, Ben Hoover, Pinar Yanardag, Duen Horng Chau.
ICML, 2025.
Spotlight Paper, top 2.6% of 12,107 submissions
RenderBender: A Survey on Adversarial Attacks Using Differentiable Rendering.
Matthew Hull, Haoran Wang, Matthew Lau, Alec Helbling, Mansi Phute, Chao Zhang, Zsolt Kira, Willian Lunardi, Martin Andreoni, Wenke Lee, and Polo Chau.
IJCAI, 2025.
Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models.
ShengYun Peng, Pin-Yu Chen, Matthew Hull, Duen Horng Chau.
NeurIPS 2024.
Dense associative memory through the lens of random features.
Benjamin Hoover, Duen Horng Chau, Hendrik Strobelt, Parikshit Ram, Dmitry Krotov.
NeurIPS 2024.
Semi-Truths: A Large-Scale Dataset of AI-Augmented Images for Evaluating Robustness of AI-Generated Image detectors.
Anisha Pal, Julia Kruk, Mansi Phute, Manognya Bhattaram, Diyi Yang, Duen Horng Chau, Judy Hoffman.
NeurIPS 2024.
Effective Guidance for Model Attention with Simple Yes-no Annotations.
Seongmin Lee, Ali Payani, and Duen Horng Polo Chau.
Big Data 2024.
Nested Fusion: A Method for Learning High Resolution Latent Structure of Multi-Scale Measurement Data on Mars.
Austin P. Wright, Scott Davidoff, Duen Horng Chau.
KDD 2024.
Best Paper, Runner-up (Applied Data Science)
Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion.
Seongmin Lee, Benjamin Hoover, Hendrik Strobelt, Zijie J. Wang, ShengYun Peng, Austin Wright, Kevin Li, Haekyu Park, Haoyang Yang, Duen Horng (Polo) Chau.
IEEE VIS 2024.
Multi-User Mobile Augmented Reality for Cardiovascular Surgical Planning.
Pratham Mehta, Rahul Narayanan, Harsha Karanth, Haoyang Yang, Timothy C. Slesnick, Fawwaz Shaw, Duen Horng Chau.
IEEE VIS 2024.
Energy Transformer.
Benjamin Hoover, Yuchen Liang, Bao Pham, Rameswar Panda, Hendrik Strobelt, Duen Horng Chau, Mohammed J. Zaki, Dmitry Krotov.
NeurIPS 2023.
Robust Principles: Architectural Design Principles for Adversarially Robust CNNs.
ShengYun Peng, Weilin Xu, Cory Cornelius, Matthew Hull, Kevin Li, Rahul Duggal, Mansi Phute, Jason Martin, Duen Horng Chau.
British Machine Vision Conference (BMVC) 2023.
Best Poster
Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries.
Haekyu Park, Seongmin Lee, Benjamin Hoover, Austin P. Wright, Omar Shaikh, Rahul Duggal, Nilaksh Das, Kevin Li, Judy Hoffman, Duen Horng Chau.
CIKM 2023.
VisGrader: Automatic Grading of D3 Visualizations.
Matthew Hull, Vivan Pednekar, Hannah Murray, Nimisha Roy, Emmanuel Tung, Susanta Routray, Connor Guerin, Justin Chen, Zijie J. Wang, Seongmin Lee, Mahdi Roozbahani, Duen Horng (Polo) Chau .
VIS 2023.
DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models.
Zijie J. Wang, Evan Montoya, David Munechika, Haoyang Yang, Benjamin Hoover, Duen Horng (Polo) Chau.
ACL, Jul 2023.
Best Paper, Honorable Mention
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse.
Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng (Polo) Chau.
CHI, Apr 2023.
Lessons from the Development of an Anomaly Detection Interface on the Mars Perseverance Rover using the ISHMAP Framework.
Austin P Wright, Peter Nemere, Adrian Galvin, Duen Horng Chau, Scott Davidoff.
IUI, Mar 2023.
Explaining Website Reliability by Visualizing Hyperlink Connectivity.
Seongmin Lee, Sadia Afroz, Haekyu Park, Zijie J. Wang, Omar Shaikh, Vibhor Sehgal, Ankit Peshin, Duen Horng Chau.
VIS, Oct 2022.
Visual Auditor: Interactive Visualization for Detection and Summarization of Model Biases.
David Munechika, Zijie J. Wang, Jack Reidy, Josh Rubin, Krishna Gade, Krishnaram Kenthapadi, Duen Horng Chau.
VIS, Oct 2022.
TimberTrek: Exploring and Curating Trustworthy Decision Trees with Interactive Visualization.
Zijie J. Wang, Chudi Zhong, Rui Xin, Takuya Takagi, Zhi Chen, Duen Horng Chau, Cynthia Rudin, Margo Seltzer.
VIS, Oct 2022.
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values.
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana.
KDD, Aug 2022.
Hear No Evil: Towards Adversarial Robustness of Automatic Speech Recognition via Multi-Task Learning.
Nilaksh Das, Duen Horng Chau.
Interspeech, Sep 2022.
MalNet: A Large-Scale Image Database of Malicious Software.
Scott Freitas, Rahul Duggal, Duen Horng Chau.
CIKM 2022.
Context-aware Traffic Flow Forecasting in New Roads.
Namhyuk Kim, Dong-Kyu Chae, Jung Ah Shin, Sang-Wook Kim, Duen Horng Chau, Sunghwan Park.
CIKM 2022.
Listen, know and spell: Knowledge-infused subword modeling for improving ASR performance of out-of-vocabulary (OOV) named entities.
Nilaksh Das, Monica Sunkara, Dhanush Bekal, Duen Horng Chau, Sravan Bodapati, Katrin Kirchhoff.
ICASSP, 2022.
A Search Engine for Discovery of Scientific Challenges and Directions.
Dan Lahav, Jon Saad Falcon, Bailey Kuehl, Sophie Johnson, Sravanthi Parasa,
Noam Shomron, Duen Horng Chau, Diyi Yang, Eric Horvitz, Daniel S. Weld, Tom Hope.
AAAI, 2022.
A Large-Scale Database for Graph Representation Learning.
Scott Freitas, Yuxiao Dong, Joshua Neil, Duen Horng (Polo) Chau.
Neural Information Processing Systems (NeurIPS), 2021.
Oral Presentation
Evaluating Graph Vulnerability and Robustness using TIGER.
Scott Freitas, Diyi Yang, Srijan Kumar, Hanghang Tong, Duen Horng (Polo) Chau.
ACM International Conference on Information and Knowledge Management (CIKM), 2021.
Featured in Nvidia Data Science Toolkit
HAR: Hardness Aware Reweighting for Imbalanced Datasets.
Rahul Duggal, Scott Freitas, Sunny Dhamnani, Duen Horng Chau, Jimeng Sun.
IEEE BigData 2021.
CUP: Cluster Pruning for Compressing Deep Neural Networks.
Rahul Duggal, Cao Xiao, Richard Vuduc, Duen Horng Chau, Jimeng Sun.
IEEE BigData 2021.
Best of Both Worlds: Robust Accented Speech Recognition with Adversarial Transfer Learning.
Nilaksh Das, Sravan Bodapati, Monica Sunkara, Sundararajan Srinivasan, Duen Horng Chau.
Interspeech 2021.
AR-CF: Augmenting Virtual Users and Items in Collaborative Filtering for Addressing Cold-Start Problems.
Dong-Kyu Chae, Jihoo Kim , Duen Horng Chau, Sang-Wook Kim.
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 2020.
Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networks.
Nilaksh Das*, Haekyu Park*, Zijie Jay Wang, Fred Hohman, Robert Firstman, Emily Rogers, and Duen Horng Chau.
IEEE Visualization Conference (VIS) 2020.
* Authors contributed equally.
How Does Visualization Help People Learn Deep Learning? Evaluating GAN Lab with Observational Study and Log Analysis.
Minsuk Kahng, Duen Horng (Polo) Chau.
IEEE Visualization Conference (VIS) 2020.
Examining the Ordering of Rhetorical Strategies in Persuasive Requests.
Omar Shaikh, Jiaao Chen, Jon Saad-Falcon, Polo Chau, and Diyi Yang.
Findings of EMNLP (Conference on Empirical Methods in Natural Language Processing), 2020.
Argo Lite: Open-Source Interactive Graph Exploration and Visualization in Browsers.
Siwei Li, Zhiyan Zhou, Anish Upadhayay, Omar Shaikh, Scott Freitas, Haekyu Park, Zijie J. Wang, Susanta Routray, Matthew Hull, Duen Horng Chau.
Proceedings of the International Conference on Information and Knowledge Management (CIKM), 2020.
GOGGLES: Automatic Image Labeling with Affinity Coding.
Nilaksh Das, Sanya Chaba, Sakshi Gandhi, Renzi Wu, Duen Horng Chau, Xu Chu.
ACM SIGMOD 2020. Portland, Oregon. Jun 14-19, 2020.
D2M: Dynamic Defense and Modeling of Adversarial Movement in Networks.
Scott Freitas, Andrew Wicker, Duen Horng Chau, Joshua Neil
SIAM International Conference on Data Mining (SDM), 2020.
Cincinnati, Ohio. May 7-9, 2020.
REST: Robust and Efficient Neural Networksfor Sleep Monitoring in the Wild.
Scott Freitas, Rahul Duggal, Jimeng Sun, Duen Horng Chau.
The Web Conference (WWW), 2020.
Taipei, Taiwan. Apr 20-24, 2020.
FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning.
Ángel Alexander Cabrera, Will Epperson, Fred Hohman, Minsuk Kahng, Jamie Morgenstern, Duen Horng (Polo) Chau
IEEE Conference on Visual Analytics Science and Technology (VAST), 2019. Vancouver, Canada. Oct 2019.
ElectroLens: Understanding Atomistic Simulations through Spatially-resolved Visualization of High-dimensional Features.
Xiangyun Lei, Fred Hohman, Duen Horng (Polo) Chau, Andrew Medford.
IEEE Visualization Conference (VIS), 2019.
Vancouver, Canada. Oct 20-25, 2019.
Atlas: Local Graph Exploration in a Global Context.
Fred Hohman, James Abello, Varun Bezzam, Duen Horng (Polo) Chau.
ACM Conference on Intelligent User Interfaces (IUI) 2019.
Los Angeles, CA. Mar 16-20, 2019.
Local Partition in Rich Graphs.
Scott Freitas, Nan Cao, Yinglong Xia, Duen Horng Chau, and Hanghang Tong.
BigData 2018. Dec 10-13, 2018. Seattle, WA, USA.
Scalable K-Core Decomposition for Static Graphs Using a Dynamic Graph Data Structure.
Alok Tripathy, Fred Hohman, Duen Horng Chau, and Oded Green.
BigData 2018. Dec 10-13, 2018. Seattle, WA, USA.
ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector.
Shang-Tse Chen, Cory Cornelius, Jason Martin, Duen Horng (Polo) Chau. PKDD 2018. Sept 10–14, 2018. Dublin, Ireland.
SHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression.
Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Siwei Li, Li Chen, Michael E. Kounavis, Duen Horng Chau.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2018.
London, UK. Aug 19-23, 2018.
Won Audience Appreciation Award, Runner-up
Search Rank Fraud De-Anonymization in Online Systems. Mizanur Rahman, Nestor Hernandez, Bogdan Carbunar and Duen Horng Chau.
ACM Conference on Hypertext and Social Media (HT'18).
Approximate Query Matching for Graph-Based Holistic Image Retrieval.
Abhijit Suprem, Duen Horng Chau, Calton Pu.
IEEE International Conference on Big Data (BigData) 2018.
Seattle, Washington. December 10-13, 2018.
Predicting Cyber Threats with Virtual Security Products.
Shang-Tse Chen, Yufei Han, Duen Horng (Polo) Chau, Christopher Gates, Michael Hart, Kevin A. Roundy.
Annual Computer Security Applications Conference (ACSAC) 2017.
Analysis of Smoking and Drinking Relapse in an Online Community.
Acar Tamersoy, Munmun De Choudhury, Duen Horng Chau.
7th International conference on Digital
Health 2017.
July 2-5, 2017. London.
Facets: Adaptive Local Exploration of Large Graphs.
Robert Pienta, Minsuk (Brian) Kahng, Zhiyuan Lin, Jilles Vreeken, Partha Talukdar, James Abello, Ganesh Parameswaran, Duen Horng (Polo) Chau.
SIAM International Conference on Data Mining (SDM) 2017.
April 27-29, 2017. Houston, Texas.
Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta.
Michael Madaio, Shang-Tse Chen, Oliver Haimson, Wenwen Zhang, Xiang Cheng, Matthew Hinds-Aldrich, Duen Horng (Polo) Chau, Bistra Dilkina.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2016.
San Francisco, CA. Aug 13-17, 2016.
Won Best Student Paper award, runner up.
[ETable] Interactive Browsing and Navigation in Relational Databases.
Minsuk Kahng, Shamkant B. Navathe, John T. Stasko, Duen Horng (Polo) Chau.
VLDB 2016.
New Delhi, India. Sept 5-9, 2016.
M-Flash Fast Billion-scale Graph Computation Using a Bimodal
Block Processing Model.
Hugo Gualdron, Robson Cordeiro, Jose Rodrigues, Duen Horng (Polo) Chau, Minsuk Kahng, U Kang. PKDD 2016. Sept 19–23, 2016. Riva del Garda, Italy.
VISAGE: Interactive Visual Graph Querying.
Robert Pienta, Acar Tamersoy, Alex Endert, Shamkant B. Navathe, Hanghang Tong, Duen Horng (Polo) Chau
International Working Conference on Advanced Visual Interfaces (AVI 2016).
June 7-10, 2016.
Bari, Italy.
FairPlay: Fraud and Malware Detection in Google Play.
Mahmudur Rahman, Mizanur Rahman, Bogdan Carbunar, Duen Horng Chau.
SIAM International Conference on Data Mining (SDM) 2016.
May 5-7, 2016. Miami, Florida.
Communication Efficient Distributed Agnostic Boosting.
Shang-Tse Chen, Maria-Florina Balcan, Duen Horng Chau.
19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016).
May 9-11, 2016. Cadiz, Spain.
What's Hot in Intelligent User Interfaces 2015 .
Shimei Pan, Oliver Brdiczka, Giuseppe Carenini, Duen Horng Chau, Per Ola Kristensson.
13th AAAI Conference on Artificial Intelligence (AAAI) 2016.
Feb 12–17, 2016. Phoenix, Arizona, USA.
Invited
Characterizing Smoking and Drinking Abstinence from Social Media.
Acar Tamersoy, Munmun De Choudhury and Duen Horng Chau.
Proceedings of ACM Conference on Hypertext and Social Media (HT).
September 1-5, 2015.
explICU: A Web-based Visualization and Predictive Modeling Toolkit for Mortality in Intensive Care Patients.
Robert Chen, Vikas Kumar, Natalie Fitch, Jitesh Jagadish, Lifan Zhang, William Dunn, Duen Horng Chau.
37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
Milano, Italy, August 25-29, 2015.
Identifying and Prioritizing Fire Inspections: A Case Study of Predicting Fire Risk in Atlanta. Michael Madaio, Oliver L. Haimson, Wenwen Zhang, Xiang Cheng, Matthew Hinds-Aldrich, Bistra Dilkina, Duen Horng (Polo) Chau. Bloomberg Data for Good Exchange 2015.
Aurigo: an Interactive Tour Planner for Personalized Itineraries.
Alexandre Yahi, Antoine Chassang, Louis Raynaud, Hugo Duthil, Duen Horng (Polo) Chau.
ACM Conference on Intelligent User Interfaces (IUI).
Atlanta, GA, USA. March 29 - April 1, 2015.
Scalable Graph Exploration and Visualization: Sensemaking Challenges and Opportunities.
Robert Pienta, James Abello, Minsuk Kahng, Duen Horng Chau.
International Conference on Big Data and Smart Computing (BigComp).
Jeju Island, Korea. February 9-12, 2015.
Invited
MMap: Fast Billion-Scale Graph Computation on a PC via Memory Mapping.
Zhiyuan Lin, Minsuk Kahng, Kaeser Md. Sabrin, Duen Horng Chau, Ho Lee, and U Kang.
Proceedings of IEEE BigData 2014 conference.
Oct 27-30, Washington DC, USA.
MAGE: Matching Approximate Patterns in Richly-Attributed Graphs.
Robert Pienta, Acar Tamersoy, Hanghang Tong, and Duen Horng Chau.
Proceedings of IEEE BigData 2014 conference.
Oct 27-30, Washington DC, USA.
[AESOP] Guilt by Association: Large Scale Malware Detection by Mining File-relation Graphs
Acar Tamersoy, Kevin Roundy, Duen Horng (Polo) Chau.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2014.
New York City, NY, USA.
Aug 24-27, 2014.
Turning the Tide: Curbing Deceptive Yelp Behaviors.
Mahmudur Rahman, Bogdan Carbunar, Jaime Ballesteros, George Burri, Duen Horng (Polo) Chau.
Proceedings of SIAM International Conference on Data Mining (SDM) 2014. April 24-26, 2014. Philadelphia, PA, USA.
Won Best Student Paper award.
"Best of SDM 2014" paper. Invited to Statistical Analysis and Data Mining (SAM) Journal.
LatentGesture: Active User Authentication Through Background Touch Analysis.
Premkumar Saravana, Samuel Clarke, Duen Horng Chau, Hongyuan Zha.
The Second International Symposium of Chinese CHI (Chinese CHI 2014).
Apr 26-27, 2014. Toronto, Canada.
Featured in popular press: Wired, engadget, gizmodo, Yahoo!, business chronicle, GT press release, and many more...
Detecting Insider Threats in a Real Corporate Database of Computer Usage Activity.
Ted E. Senator, Henry G. Goldberg, Alex Memory, William Y. Young, Brad Rees, Robert Pierce, Daniel Huang, Matthew Reardon,
David A. Bader, Edmond Chow, Irfan Essa, Joshua Jones, Vinay Bettadapura, Duen Horng Chau, Oded Gree, Oguz Kaya, Anita Zakrzewska, Erica Briscoe, Rudolph L. Mappus IV, Robert McColl, Lora Weiss,
Thomas G. Dietterich, Alan Fern, Weng-Keen Wong, Shubhomoy Das, Andrew Emmott, Jed Irvine,
Jay-Yoon Lee, Danai Koutra, Christos Faloutsos,
Daniel Corkill, Lisa Friedland, Amanda Gentzel, David Jensen.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2013.
Chicago, Illinois, USA.
Aug 11-14, 2013.
Inside Insider Trading: Patterns & Discoveries from a Large Scale Exploratory Analysis.
Acar Tamersoy, Bo Xie, Stephen L. Lenkey, Bryan R. Routledge. Duen Horng Chau, Shamkant B. Navathe.
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) 2013.
Niagara Falls, Canada.
August 25-28, 2013.
Invited to Social Network Analysis and Mining journal (SNAM).
Spatio-temporal Mining of Software Adoption & Penetration.
Evangelos E. Papalexakis, Tudor Dumitras, Duen Horng (Polo) Chau, B. Aditya Prakash, Christos Faloutsos.
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) 2013.
Niagara Falls, Canada.
August 25-28, 2013.
Invited to Social Network Analysis and Mining journal (SNAM).
Inference-assisted Choosing by Advantages. John Haymaker, Duen Horng Chau, Bo Xie.
21th Conference of the International Group for Lean Construction (IGLC).
Fortaleza, Brazil.
Jul 29 - Aug 2, 2013.
Mining Connection Pathways for Marked Nodes in Large Graphs.
Leman Akoglu, Jilles Vreeken, Hanghang Tong, Duen Horng Chau, Nikolaj Tatti, and Christos Faloutsos. Proceedings of SIAM International Conference on Data Mining (SDM) 2013. May 2-4, 2013. Austin, Texas. [25% accept]
PEGASUS: Mining Billion-Scale Graphs in the Cloud.
U Kang, Duen Horng Chau, and Christos Faloutsos. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2012. Mar 25-30, 2012. Kyoto, Japan
Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithms.
Danai Koutra, Tai-You Ke, U Kang, Duen Horng (Polo) Chau, Hsing-Kuo Kenneth Pao, and Christos Faloutsos. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (PKDD) 2011. Sept 5-9, 2011. Athens, Greece. [20% acceptance rate]
Mining Large Graphs: Algorithms, Inference, and Discoveries.
U Kang, Duen Horng (Polo) Chau, Christos Faloutsos. IEEE International Conference of Data Engineering (ICDE) 2011. April 11-16. Hannover, Germany. [20% acceptance rate]
Apolo: Making Sense of Large Network Data by Combining Rich User Interaction and Machine Learning.
Duen Horng (Polo) Chau, Aniket Kittur, Jason I. Hong, Christos Faloutsos. ACM Conference on Human Factors in Computing Systems (CHI) 2011.
May 7-12, 2011. Vancouver, BC, Canada. [26% acceptance rate]
Polonium: Tera-Scale Graph Mining and Inference for Malware Detection.
Duen Horng (Polo) Chau, Carey Nachenberg, Jeffrey Wilhelm, Adam Wright, Christos Faloutsos. Proceedings of SIAM International Conference on Data Mining (SDM) 2011.
April 28-30, 2011. Mesa, Arizona. [25% acceptance rate]
On the Vulnerability of Large Graphs.
Hanghang Tong, B. Aditya Prakash, Charalampos Tsourakakis, Tina Eliassi-Rad, Christos Faloutsos, Duen Horng (Polo) Chau. IEEE International Conference on Data Mining (ICDM) 2010. Dec 14-17, 2010. Sydney, Australia. [19% acceptance rate]
What to Do When Search Fails: Finding Information by Association.
Duen Horng (Polo) Chau, Brad Myers, and Andrew Faulring. ACM Conference on Human Factors in Computing Systems (CHI) 2008. April 5-10, 2008. Florence, Italy. New York: ACM Press, Pages 999-1008. [22% acceptance rate]
The eBay Graph: How Do Online Auction Users Interact? Yordanos Beyene, Michalis Faloutsos, Duen Horng (Polo) Chau, Christos Faloutsos. Computer Communications Workshops, 2008. INFOCOM. April 13-18, 2008. Phoenix, AZ.
NetProbe: A Fast and Scalable System for Fraud Detection in Online Auction Networks.
Shashank Pandit, Duen Horng (Polo) Chau, Samuel Wang, Christos Faloutsos. International Conference on World Wide Web (WWW) 2007. May 8-12, 2007. Banff, Alberta, Canada. Pages 201-210. [15% acceptance rate]
Eyes on the Road, Hands on the Wheel: Thumb-based Interaction Techniques for Input on Steering Wheels.
Ivan E. Gonzalez, Jacob O. Wobbrock, Duen Horng (Polo) Chau, Andrew Faulring, Brad A. Myers. Graphics Interface (GI) 2007. May 28-30, 2007. Montreal, Quebec, Canada. Pages 95-102. [48% acceptance rate]
Demonstrating the Viability of Automatically Generated User Interfaces.
Jeffrey Nichols, Duen Horng (Polo) Chau, Brad A. Myers. ACM Conference on Human Factors in Computing Systems (CHI) 2007. April 28-May 3, 2007. San Jose, CA. Pages 1283-1292. [25% acceptance rate]
An Alternative to Push, Press, and Tap-tap-tap: Gesturing on an Isometric Joystick for Mobile Phone Text Entry.
Jacob O. Wobbrock, Duen Horng (Polo) Chau and Brad A. Myers. ACM Conference on Human Factors in Computing Systems (CHI) 2007. April 28-May 3, 2007. San Jose, CA. Pages 667-676. [25% acceptance rate]
Huddle: Automatically Generating Interfaces for Systems of Multiple Connected Appliances.
Jeffrey Nichols, Brandon Rothrock, Duen Horng (Polo) Chau, Brad A. Myers. ACM Symposium on User Interface Software and Technology (UIST) 2006. October 15-18, 2006. Montreux, Switzerland. Pages 279-288. [23% acceptance rate]
In-stroke Word Completion.
Jacob O. Wobbrock, Brad A. Myers, and Duen Horng (Polo) Chau. ACM Symposium on User Interface Software and Technology (UIST) 2006. October 15-18, 2006. Montreux, Switzerland. Pages 333-336. [23% acceptance rate]
Detecting Fraudulent Personalities in Networks of Online Auctioneers.
Duen Horng (Polo) Chau, Shashank Pandit, and Christos Faloutsos. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (PKDD) 2006. Sept 18-22, 2006. Berlin, Germany. Pages 103-114. [15% acceptance rate]
Best Presentation Award, 3rd place
A Linguistic Analysis of How People Describe Software Problems.
Andrew J. Ko, Brad A. Myers, and Duen Horng (Polo) Chau.
Proceedings of VL/HCC 2006. September 4-8, 2006, Brighton, UK. Pages 127-134. [28% acceptance rate]
Answering Why and Why Not Questions in User Interfaces.
Brad Myers, David A. Weitzman, Andrew J. Ko, and Duen Horng (Polo) Chau. ACM Conference on Human Factors in Computing Systems (CHI) 2006. April 22-27, 2006. Montreal, Canada. Pages 397-406. [23% acceptance rate]
Interactive Articles
Communicating with Interactive Articles.
Fred Hohman, Matthew Conlen, Jeffrey Heer, Duen Horng (Polo) Chau.
Distill, 2020.
Journal
An Interrogative Survey of Explainable AI in Manufacturing.
Zoe Alexander, Duen Horng Chau, Christopher Saldaña.
IEEE Transactions on Industrial Informatics. Volume: 20, Issue: 5, May 2024.
TrafficVis: Visualizing Organized Activity and Spatio-Temporal Patterns for Detecting Human Trafficking.
Catalina Vajiac, Duen Horng Chau, Andreas Olligschlaeger, Rebecca Mackenzie, Pratheeksha Nair, Meng-Chieh Lee, Yifei Li, Namyong Park, Reihaneh Rabbany, Christos Faloutsos.
IEEE Transactions on Visualization and Computer Graphics (Proc. VIS'22), 2023.
Best Paper, Honorable Mention
Back-calculation of soil parameters from displacement-controlled cavity expansion under geostatic stress by FEM and machine learning.
Fernando Patino-Ramirez, Zijie Jay Wang, Duen Horng Chau, Chloe Arson.
Acta Geotechnica. 18, 1755–1768. 2023.
Graph Vulnerability and Robustness: A Survey.
Scott Freitas, Diyi Yang, Srijan Kumar, Hanghang Rong, Duen Horng Chau.
IEEE Transactions on Knowledge and Data Engineering (TKDE) 2022.
A Cluster-then-label Approach for Few-shot Learning with Application to Automatic Image Data Labeling.
Renzhi Wu, Nilaksh Das, Sanya Chaba, Sakshi Gandhi, Duen Horng Chau, Xu Chu.
ACM Journal of Data and Information Quality (JDIQ). 14.3 (2022): 1-23.
The Role of Interactive Visualization in Fostering Trust in AI.
Emma Beauxis-Aussalet, Michael Behrisch, Rita Borgo, Duen Horng Chau, Christopher Collins, David Ebert, Mennatallah El-Assady, Alex Endert, Daniel A. Keim, Jörn Kohlhammer, Daniela Oelke, Jaakko Peltonen, Maria Riveiro, Tobias Schreck, Hendrik Strobelt, Jarke J. van Wijk.
IEEE Computer Graphics and Applications 41, no. 6 (2021): 7-12.
Detection of Emerging Drugs Involved in Overdose via Diachronic Word Embeddings of Substances Discussed on Social Media.
Austin P. Wright, Christopher M. Jones, Duen Horng Chau, Robert M. Gladden, Steven A. Sumner.
Journal of Biomedical Informatics (JBI), Volume 119, July 2021.
NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks.
Haekyu Park, Nilaksh Das, Rahul Duggal, Austin P. Wright, Omar Shaikh, Fred Hohman, Duen Horng (Polo) Chau.
IEEE Transactions on Visualization and Computer Graphics (Proc. VIS'21), 2022.
Invited to present at SIGGRAPH’22 as a top VIS'21 paper (1% of 442 submissions)
RECAST: Enabling User Recourse and Interpretability of Toxicity Detection Models with Interactive Visualization.
Austin P. Wright, Omar Shaikh, Haekyu Park, Will Epperson, Muhammed Ahmed, Stephane Pinel, Diyi Yang, Duen Horng (Polo) Chau.
Proceedings of the ACM on Human-Computer Interaction, Volume 5, Issue CSCW1, April 2021. Presented at The 24th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) 2021.
A Survey of Human-Centered Evaluations in Human-Centered Machine Learning.
Fabian Sperrle, Mennatallah El-Assady, Grace Guo, Rita Borgo, Duen Horng Chau, Alex Endert, Daniel Keim.
Computer Graphics Forum (CGF), Vol. 40. No. 3. 2021. Presented at EuroVis'21.
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization.
Zijie J. Wang, Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, and Duen Horng (Polo) Chau.
IEEE Transactions on Visualization and Computer Graphics (Proc. VIS'20), 2021.
Went viral! 7900+ Github stars — top of Github Trending
The only VAST'20 paper invited to SIGGRAPH
Towards De-Anonymization of Google Play Search Rank Fraud.
Mizanur Rahman, Nestor Hernandez, Bogdan Carbunar, Duen Horng (Polo) Chau.
IEEE Transactions on Knowledge and Data Engineering (TKDE). Feb, 2020.
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations.
Fred Hohman, Haekyu Park, Caleb Robinson, Duen Horng (Polo) Chau.
IEEE Transactions on Visualization and Computer Graphics (Proc. VAST'19). 2020.
GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation.
Minsuk Kahng, Nikhil Thorat, Duen Horng (Polo) Chau, Fernanda B. Viégas, and Martin Wattenberg.
IEEE Transactions on Visualization and Computer Graphics (Proc. VAST'18). 2019.
Went viral! Open sourced with Google AI
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers.
Fred Hohman, Minsuk Kahng, Robert Pienta, Duen Horng Chau.
IEEE Transactions on Visualization and Computer Graphics, 2018.
Chronodes: Interactive Multi-focus Exploration of Event Sequences.
Peter J. Polack, Shang-Tse Chen, Minsuk Kahng, Kaya De Barbaro, Rahul Basole, Moushumi Sharmin, Duen Horng (Polo) Chau.
ACM Transactions on Interactive Intelligent Systems (TiiS) Special Issue on Interactive Visual Analysis of Human and Crowd Behaviors. 2018.
ACM TiiS 2018 Best Paper, Honorable Mention
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models.
Minsuk Kahng, Pierre Andrews, Aditya Kalro, Duen Horng (Polo) Chau.
IEEE Transactions on Visualization and Computer Graphics (Proc. VAST'17). Jan 2018.
[21% acceptance rate]
Deployed on Facebook Machine Learning platform used by 25% engineers
Invited to present at SIGGRAPH 2018 as a top VAST'17 paper (4 total)
VIGOR: Interactive Visual Exploration of Graph Query Results.
Robert Pienta, Fred Hohman, Alex Endert, Acar Tamersoy, Kevin Roundy, Chris Gates, Shamkant Navathe, Duen Horng (Polo) Chau.
IEEE Transactions on Visualization and Computer Graphics (Proc. VAST'17), Jan 2018.
[21% acceptance rate]
Search Rank Fraud and Malware Detection in Google Play.
Mahmudur Rahman, Mizanur Rahman, Bogdan Carbunar, Duen Horng Chau.
IEEE Transactions on Knowledge and Data Engineering (TKDE) 29(6), 1329. 2017
Constraint based temporal event sequence mining for Glioblastoma survival prediction.
Kunal Malhotra, Shamkant Navathe, Duen Horng Chau, Costas Hadjipanayis and Jimeng Sun.
Journal of biomedical informatics, 16, 267-275. 2016
Center of excellence for mobile sensor Data-to-Knowledge (MD2K).
Santosh Kumar, Gregory D. Abowd, William T. Abraham, Mustafa al’Absi, J. Gayle Beck, Duen Horng Chau, Tyson Condie, David E. Conroy, Emre Ertin, Deborah Estrin, Deepak Ganesan, Cho Lam, Benjamin Marlin, Clay B. Marsh, Susan A. Murphy, Inbal Nahum-Shani, Kevin Patrick, James M. Rehg, Moushumi Sharmin, Vivek Shetty, Ida Sim, Bonnie Spring, Mani Srivastava and David W. Wetter.
Journal of the American Medical Informatics Association (JAMIA) Jul 2015.
DOI: 10.1093/jamia/ocv056
Node Immunization on Large Graphs: Theory and Algorithms.
Chen, C. and Tong, H. and Prakash, B.A. and Tsourakakis, C. and Eliassi-Rad, T. and Faloutsos, C. and Chau, D.H.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(1), 113-126. 2015
To Catch a Fake: Curbing Deceptive Yelp Ratings and Venues.
Mahmudur Rahman, Bogdan Carbunar, Jaime Ballesteros, Duen Horng (Polo) Chau.
Statistical Analysis and Data Mining: The ASA Data Science Journal, 8(3), 147-161. 2015.
Understanding variations in pediatric asthma care processes in the emergency department using visual analytics.
Rahul C. Basole, Mark L. Braunstein, Vikas Kumar, Hyunwoo Park, Minsuk Kahng, Duen Horng (Polo) Chau, Acar Tamersoy, Daniel A. Hirsh, Nicoleta Serban, James Bost, Burton Lesnick, Beth L. Schissel, Michael Thompson.
Journal of the American Medical Informatics Association (JAMIA) 2015.
DOI: 10.1093/jamia/ocu016
GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration.
Charles D. Stolper, Minsuk Kahng, Zhiyuan Lin, Florian Foerster, Aakash Goel, John Stasko, and Duen Horng Chau.
IEEE Transactions on Visualization and Computer Graphics, 20(12), 2320-2328. 2014.
SharkFin: Spatio-temporal mining of software adoption and penetration.
Evangelos E. Papalexakis, Tudor Dumitras, Duen Horng Chau, B. Aditya Prakash, Christos Faloutsos.
Social Network Analysis and Mining (SNAM), 4(1), 1-15. 2014.
Large Scale Insider Trading Analysis: Patterns and Discoveries.
Acar Tamersoy, Elias Khalil, Bo Xie, Stephen L. Lenkey, Bryan R. Routledge. Duen Horng Chau, Shamkant B. Navathe.
Social Network Analysis and Mining (SNAM), 4(1), 1-17. 2014.
Preprints
UniTable: Towards A Unified Framework For Table Structure Recognition Via Self-Supervised Pretraining.
ShengYun Peng , Seongmin Lee, Xiaojing Wang, Raji Balasubramaniyan, Duen Horng Chau.
Book Chapters
Exploratory Visual Analytics of Mobile Health Data: Sensemaking Challenges and Opportunities.
Peter J Polack Jr, Moushumi Sharmin, Kaya de Barbaro, Minsuk Kahng, Shang-Tse Chen, and Duen Horng Chau.
Mobile Health: Sensors, Analytic Methods, and Applications.
Springer. 2017.
Case study on fraud detection using social-network analysis.
Duen Horng (Polo) Chau and Christos Faloutsos. Encyclopedia of Social Network Analysis and Mining. Springer. 2014.
Edited Volumes
Catching Bad Guys with Graph Mining. Polo Chau. Crossroads: The ACM Magazine for Students - The Fate of Money. Volume 17 Issue 3, Spring 2011. Pages 16-18.
Workshop
ClickDiffusion: Harnessing LLMs for Interactive Precise Image Editing.
Alec Helbling, Seongmin Lee, Duen Horng Chau
CVPR 2024 Workshop on AI for Content Creation Workshop.
Mobile Fitting Room: On-device Virtual Try-on via Diffusion Models.
Justin Blalock, David Munechika, Harsha Karanth, Alec Helbling, Pratham Mehta, Seongmin Lee, Duen Horng Chau.
CVPR 24 Workshop on Virtual Try-On.
Self-Supervised Pre-Training For Table Structure Recognition Transformer.
ShengYun Peng , Seongmin Lee, Xiaojing Wang, Raji Balasubramaniyan, Duen Horng Chau
Association for the Advancement of Artificial Intelligence (AAAI) SDU Workshop 2024
High-Performance Transformers For Table Structure Recognition Need Early Convolutions.
ShengYun Peng , Seongmin Lee, Xiaojing Wang, Raji Balasubramaniyan, Duen Horng Chau
NeurIPS 2023 Workshop on Table Representation Learning (TRL).
ObjectComposer: Consistent Generation of Multiple Objects Without Fine-tuning.
Alec Helbling, Evan Montoya, Duen Horng (Polo) Chau.
NeurIPS 2023 Workshop on ML for Creativity and Design.
Energy Transformer.
Benjamin Hoover, Yuchen Liang, Bao Pham, Rameswar Panda, Hendrik Strobelt, Duen Horng Chau, Mohammed J Zaki, Dmitry Krotov.
NeurIPS 2023 Workshop on Associative Memory & Hopfield Networks (AMHN).
Memory in Plain Sight: A Survey of the Uncanny Resemblances between Diffusion Models and Associative Memories.
Benjamin Hoover, Hendrik Strobelt, Dmitry Krotov, Judy Hoffman, Zsolt Kira, Duen Horng Chau.
NeurIPS 2023 Workshop on Associative Memory & Hopfield Networks (AMHN).
ConceptEvo: Interpreting Concept Evolution in Deep Learning Training.
Haekyu Park, Seongmin Lee, Benjamin Hoover, Austin Wright, Omar Shaikh, Rahul Duggal, Nilaksh Das, Judy Hoffman, Duen Horng (Polo) Chau.
ICML 2023 Workshop on AI & HCI.
A Universal Abstraction for Hierarchical Hopfield Networks.
Benjamin Hoover, Duen Horng (Polo) Chau, Hendrik Strobelt, Dmitry Krotov.
The Symbiosis of Deep Learning and Differential Equations (DLDE) workshop, NeurIPS 2022.
Spotlight presentation
SkeleVision: Towards Adversarial Resiliency of Person Tracking with Multi-Task Learning.
Nilaksh Das, Sheng-Yun Peng, Duen Horng Chau.
Adversarial Robustness in the Real World (AROW) Workshop, ECCV 2022.
GAM Changer: Editing Generalized Additive Models with Interactive Visualizations.
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng (Polo) Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana.
NeurIPS 2021 Workshop on Bridging the Gap: From Machine Learning Research to Clinical Practice (Research2Clinics).
Best Paper Award
A Comparative Analysis of Industry Human-AI Interaction Guidelines.
Austin P. Wright, Zijie J. Wang, Haekyu Park, Grace Guo, Fabian Sperrle, Mennatallah El-Assady, Alex Endert, Daniel Keim, Duen Horng (Polo) Chau.
IEEE VIS 2020 Workshop on Trust and Expertise in Visual Analytics (TREX).
Toward a Bias-Aware Future for Mixed-Initiative Visual Analytics.
Adam Coscia, Duen Horng (Polo) Chau, Alex Endert.
IEEE VIS 2020 Workshop on Trust and Expertise in Visual Analytics (TREX).
Visual Analytics for Interpretability on Deep Neural Networks.
Haekyu Park, Fred Hohman, Nilaksh Das, Caleb Robinson, Duen Horng Chau.
NeurIPS Workshop on Women in Machine Learning (WiML), 2019.
Vancouver, Canada. Dec 9, 2019.
How Does Visualization Help People Learn Deep Learning? Evaluation of GAN Lab.
Minsuk Kahng, Duen Horng (Polo) Chau.
IEEE VIS 2019 Workshop on Evaluation of Interactive Visual Machine Learning Systems (EVIVA-ML).
Vancouver, Canada. Oct 21, 2019.
Extracting Knowledge For Adversarial Detection and Defense in Deep Learning.
Scott Freitas, Shang-Tse Chen, Duen Horng (Polo) Chau.
KDD 2019 Workshop on Learning and Mining for Cybersecurity (LEMINCS).
Anchorage, Alaska. Aug 5, 2019.
The Efficacy of SHIELD under Different Threat Models.
Cory Cornelius, Nilaksh Das, Shang-Tse Chen, Li Chen, Michael Kounavis, Duen Horng (Polo) Chau.
KDD 2019 Workshop on Learning and Mining for Cybersecurity (LEMINCS).
Anchorage, Alaska. Aug 5, 2019.
Discovery of Intersectional Bias in Machine Learning Using Automatic Subgroup Generation.
Ángel Alexander Cabrera, Minsuk Kahng, Fred Hohman, Jamie Morgenstern, Duen Horng (Polo) Chau.
ICLR 2019 Workshop on Debugging Machine Learning Models Workshop Debug-ML).
New Orleans, LA. May 6, 2019.
Towards the Realistic Evaluation of Evasion Attacks using CARLA.
Cory Cornelius, Shang-tse Chen, Jason Martin, Duen Horng (Polo) Chau.
The 2nd DSN Workshop on Dependable and Secure Machine Learning
(DSN-DSML'19).
Defense against Adversarial Attacks using JPEG Compression.
Nilaksh Das, Mahduri Shanbhogue, Shang-Tse Chen, Fred Hohman, Li Chen, Michael. E. Kounavis, Duen Horng (Polo) Chau.
NIPS Workshop on Women in Machine Learning (WiML), 2017.
Designing a Visual Analytics System for Industry-Scale Deep Neural Network Models.
Minsuk Kahng, Pierre Y. Andrews, Aditya Kalro, Duen Horng (Polo) Chau.
IEEE VIS'17 Workshop on Visual Analytics for Deep Learning.
Scalable Architecture for Anomaly Detection and Visualization in Power Generating Assets.
Paras Jain, Chirag Tailor, Sam Ford, Liexiao Ding, Michael Phillips, Fang Liu, Nagi Gebraeel, Duen Horng Chau.
The 3rd IEEE International Workshop on High-Performance Big Data Computing (HPBDC, at IPDPS 2017). May 29, 2017. Orlando, Florida.
[MLCube] Visual Exploration of Machine Learning Results using Data Cube Analysis.
Minsuk Kahng, Dezhi Fang, Duen Horng (Polo) Chau.
SIGMOD 2016 Workshop on Human-In-the-Loop Data Analytics (HILDA). Jun 26, 2016. San Francisco, USA.
Building a Research Data Science Platform from Industrial Machines.
Fang (Cherry) Liu, Fu Shen, Duen Horng Chau, Neil Bright and Mehmet Belgin.
IEEE Big Data 2016 Workshop on Advances in Software and Hardware for Big Data to Knowledge Discovery (ASH). Dec 5-8, 2016. Washington D.C.
Building a Data Science Platform from Scratch.
Fang (Cherry) Liu, Fu Shen, Duen Horng (Polo) Chau, Paras Jain.
Women in HPC Workshop at Super Computing (SC) 2016. Nov 13, 2016. Salt Lake City, USA.
ISPARK: Interactive Visual Analytics for Fire Incidents and Station Placement.
Subhajit Das, Andrea McCarter, Joe Minieri, Nandita Damaraju, Sriram Padmanabhan and Duen Horng Chau.
KDD 2015 Workshop on Interactive Data Exploration and Analytics (IDEA)
Aug 10, 2015. Sydney, Australia.
A Visual Analytics Approach to Understanding Care Process Variation and Conformance.
Rahul C. Basole, Hyunwoo Park, Mayank Gupta, Mark L. Braunstein, Polo Chau, Michael Thompson, Vikas Kumar, Robert Pienta, Minsuk Kahng.
2015 Workshop on Visual Analytics in Healthcare.
Oct 25, 2015. Chicago IL, USA.
Towards Scalable Graph Computation on Mobile Devices.
Yiqi Chen, Zhiyuan Lin, Robert Pienta, Minsuk Kahng, Duen Horng (Polo) Chau.
IEEE BigData 2014 Workshop on Scalable Machine Learning: Theory and Applications.
Oct 27, 2014. Washington DC, USA.
Bicentric Visualization of Pediatric Asthma Care Process Activities.
Rahul C. Basole, Hyunwoo Park, Vikas Kumar, Mark L. Braunstein, James Bost, Duen Horng (Polo) Chau, Minsuk Kahng.
IEEE VIS 2014 Workshop on Visualizing Electronic Health Record Data (EHRVis).
Nov 9, 2014. Paris, France.
Exploring Clinical Care Processes Using Visual and Data Analytics: Challenges and Opportunities.
Vikas Kumar, Hyunwoo Park, Rahul C. Basole, Mark Braunstein, Minsuk Kahng, Duen Horng Chau, Acar Tamersoy, Daniel A. Hirsh, Nicoleta Serban, James Bost, Burton Lesnick, Beth Schissel, Michael Thompson.
ACM KDD'14 Data Mining for Social Good Workshop.
Aug 24, 2014, New York City, NY.
Temporal Event Sequence Mining for Glioblastoma Survival Prediction.
Kunal Malhotra, Duen Horng (Polo) Chau, Jimeng Sun, Costas Hadjipanayis, Shamkant B. Navathe.
KDD 2014 Workshop on Health Informatics
(HI-KDD 2014).
Aug 24, 2014. New York City, NY. USA.
Leveraging Memory Mapping for Fast and Scalable Graph Computation on a PC.
Zhiyuan (Jerry) Lin, Duen Horng (Polo) Chau, U Kang.
IEEE BigData'13 Scalable Machine Learning: Theory and Applications.
Oct 6, Santa Clara, CA.
Exploring Large Scale Insider Trading Data: Network Patterns & Discoveries.
Acar Tamersoy, Bo Xie, Stephen Lenkey, Bryan R. Routledge, Duen Horng (Polo) Chau, Shamkant B. Navathe.
Workshop on Information in Networks (WIN 2013).
Oct 4-5, New York, NY.
Scalable, Minimalist Graph Computation on a PC via Memory Mapping.
Zhiyuan (Jerry) Lin, Duen Horng (Polo) Chau, U Kang.
Workshop on Information in Networks (WIN 2013).
Oct 4-5, New York, NY.
Augmenting MATLAB with Semantic Objects for an Interactive Visual Environment.
Changhyun Lee, Jaegul Choo, Duen Horng (Polo) Chau, Haesun Park.
KDD 2013 Workshop on Interactive Data Exploration and Analytics (IDEA 2013).
Aug 11, 2013. Chicago, Illinois.
Polonium: Tera-Scale Graph Mining for Malware Detection. Duen Horng (Polo) Chau, Carey Nachenberg, Jeffrey Wilhelm, Adam Wright, Christos Faloutsos. The 2nd Workshop on Large-scale Data Mining: Theory and Applications (LDMTA 2010). July 25, 2010. Washington, DC.
IBM Student Travel Fellowship
IBM Student Travel Fellowship
Inference of Beliefs on Billion-Scale Graphs.
U Kang, Duen Horng (Polo) Chau, Christos Faloutsos. The 2nd Workshop on Large-scale Data Mining: Theory and Applications (LDMTA 2010). July 25-28, 2010. Washington, DC.
Supporting Ad Hoc Sensemaking: Integrating Cognitive, HCI, and Data Mining Approaches.
Aniket Kittur, Duen Horng (Polo) Chau, Christos Faloutsos, Jason I. Hong. Sensemaking Workshop at CHI 2009. April 4-5, 2009. Boston, MA.
Feldspar: A System for Finding Information by Association. Duen Horng (Polo) Chau, Brad Myers, and Andrew Faulring. PIM 2008: CHI 2008 Workshop on Personal Information Management. April 5-6, 2008. Florence, Italy.
Fraud Detection in Electronic Auction.
Duen Horng (Polo) Chau and Christos Faloutsos.
Proceedings of EWMF'05: European Web Mining Forum, at ECML/PKDD'05. October 3-7, 2005. Porto, Portugal.
Tiny Papers (ICLR)
LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked.
Mansi Phute, Alec Helbling, Matthew Daniel Hull, ShengYun Peng, Sebastian Szyller, Cory Cornelius, Duen Horng (Polo) Chau.
ICLR 2024 Tiny Paper.
Adopted by ADP, the leading company in human capital management (HCM) solutions, for content moderation
Revamp: Automated Simulations of Adversarial Attacks on Arbitrary Objects in Realistic Scenes.
Matthew Daniel Hull, Zijie J. Wang, Duen Horng Chau.
ICLR 2024 Tiny Paper.
Poster Papers
Managing Project Teams in an Online Class of 1000+ Students.
Tabatabaei Anaraki, Nazanin, Taneisha Ng, Gaurav Verma, Yu Fu, Martin O'Connell, Matthew Hull, Susanta Routray, Max Mahdi Roozbahani, Duen Horng Chau.
SIGCSE 2025, Poster.
Transformer Explainer: Interactive Learning of Text-Generative Models.
Aeree Cho, Grace C. Kim, Alexander Karpekov, Alec Helbling, Zijie J. Wang, Seongmin Lee, Benjamin Hoover, Duen Horng Chau.
Poster, IEEE VIS 2024.
Went viral on X (5000+ "likes"), LinkedIn (1500+ reactions), HuggingFace (#1 paper of the day)!
4000+ GitHub stars
LLM Attributor: Interactive Visual Attribution for LLM Generation.
Seongmin Lee, Zijie J. Wang, Aishwarya Chakravarthy, Alec Helbling, ShengYun Peng, Mansi Phute, Duen Horng Chau, Minsuk Kahng.
Poster, IEEE VIS 2024.
SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebooks.
Zijie J. Wang, David Munechika, Seongmin Lee, Duen Horng Chau.
Extended Abstracts, CHI 2024.
ARCollab: Towards Multi-User Interactive Cardiovascular Surgical Planning in Mobile Augmented Reality.
Pratham Darrpan Mehta, Harsha Karanth, Haoyang Yang, Timothy C Slesnick, Fawwaz Shaw, Duen Horng Chau.
Extended Abstracts, CHI 2024.
ManimML: Communicating Machine Learning Architectures with Animation.
Alec Helbling, Duen Horng Chau.
Poster, IEEE VIS 2023.
IEEE VIS 2023 Best Poster
Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion.
Seongmin Lee, Benjamin Hoover, Hendrik Strobelt, Zijie J. Wang, ShengYun Peng, Austin Wright, Kevin Li, Haekyu Park, Haoyang Yang, Duen Horng (Polo) Chau.
Poster, IEEE VIS 2023.
TrafficBoard: Digital Spatio-Temporal Pinboard for Human Trafficking Detection.
Catalina Vajiac, Duen Horng Chau, Andreas Olligschlaeger, Pratheeksha Nair, Meng-Chieh Lee, Mirela Cazzolato, Reihaneh Rabbany, Cara Jones, Christos Faloutsos.
Poster, IEEE VIS 2023.
NOVA: A Practical Method for Creating Notebook-Ready Visual Analytics.
Zijie J. Wang, David Munechika, Seongmin Lee, Duen Horng Chau.
Poster, IEEE VIS 2022.
Evaluation of Argo Scholar with Observational Study.
Kevin Li, Haoyang Yang, Evan Montoya, Anish Upadhayay, Zhiyan Zhou, Jon Saad-Falcon, Duen Horng Chau.
Poster, IEEE VIS 2022.
NeuroMapper: In-browser Visualizer for Neural Network Training.
Zhiyan Zhou, Kevin Li, Haekyu Park, Megan Dass, Austin P Wright, Nilaksh Das, Duen Horng Chau.
Poster, IEEE VIS 2022.
Evaluating Cardiovascular Surgical Planning in Mobile Augmented Reality.
Haoyang Yang, Pratham Darrpan Mehta, Jonathan Leo, Zhiyan Zhou, Megan Dass, Anish Upadhayay, Timothy C Slesnick, Fawwaz Shaw, Amanda Randles, Duen Horng Chau.
Poster, IEEE VIS 2022.
VisPaD: Visualization and Pattern Discovery for Fighting Human Trafficking.
Pratheeksha Nair, Yifei Li, Catalina Vajiac, Andreas Olligschlaeger, Meng-Chieh Lee, Namyong Park, Duen Horng Chau, Christos Faloutsos, Reihaneh Rabbany.
Poster, WWW 2022.
MisVis: Explaining Web Misinformation Connections via Visual Summary.
Seongmin Lee, Sadia Afroz, Haekyu Park, Zijie J. Wang, Omar Shaikh, Vibhor Sehgal, Ankit Peshin, Duen Horng (Polo) Chau. Extended Abstracts, CHI 2022.
Erasing Labor with Labor: Dark Patterns and Lockstep Behaviors on Google Play.
Ashwin Singh, Arvindh Arun, Pulak Malhotra, Pooja Desur, Ayushi Jain, Duen Horng Chau, Ponnurangam Kumaraguru.
Extended Abstract, ACM Hypertext 2022.
Towards Automatic Grading of D3.js Visualizations.
Matthew Hull, Connor Guerin, Justin Lu Chen, Susanta Kumar Routray, Duen Horng Chau.
Poster Abstract. IEEE VIS 2021.
IEEE VIS 2021 Best Poster
Argo Scholar: Interactive Visual Exploration of Literature in Browsers.
Kevin Li, Haoyang Yang, Anish Upadhayay, Zhiyan Zhou, Jon Saad-Falcon, Duen Horng Chau.
Poster Abstract. IEEE VIS 2021.
IEEE VIS 2021 Best Poster, Honorable Mention
TrafficVis: Visualizing Suspicious Meta-Clusters for Human Trafficking Detection.
Catalina Vajiac, Andreas Olligschlaeger, Yifei Li, Pratheeksha Nair, Meng-Chieh Lee, Namyong Park, Reihaneh Rabbany, Duen Horng Chau, Christos Faloutsos.
Poster Abstract. IEEE VIS 2021.
IEEE VIS 2021 Best Poster, Honorable Mention
Interactive Cardiovascular Surgical Planning via Augmented Reality.
Jonathan Leo, Zhiyan Zhou, Haoyang Yang, Anish Upadhayay, Timothy C. Slesnick, Fawwaz Shaw, Duen Horng Chau.
Asian CHI Symposium 2021.
EnergyVis: Interactively Tracking and Exploring Energy Consumption for ML Models.
Omar Shaikh, Jon Saad-Falcon, Austin P. Wright, Nilaksh Das, Scott Freitas, Omar Isaac Asensio, Duen Horng (Polo) Chau.
Extended Abstracts, CHI 2021.
Mapping Researchers with PeopleMap.
Jon Saad-Falcon, Omar Shaikh, Zijie J. Wang, Austin P. Wright, Sasha Richardson, Duen Horng (Polo) Chau.
Poster Abstract, IEEE VIS 2020.
IEEE VIS 2020 Best Poster Research Award, Honorable Mention (VAST track)
CNN 101: Interactive Visual Learning for Convolutional Neural Networks.
Zijie J. Wang, Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, Duen Horng (Polo) Chau.
Extended Abstracts, CHI 2020.
Apr 25-30, Honolulu, Hawaii, USA.
Massif: Interactive Interpretation of Adversarial Attacks on Deep Learning.
Nilaksh Das, Haekyu Park, Zijie J. Wang, Fred Hohman, Robert Firstman, Emily Rogers, Duen Horng (Polo) Chau.
Extended Abstracts, CHI 2020.
Apr 25-30, Honolulu, Hawaii, USA.
Mixed Reality for Learning Programming.
Joonyoung Kim, Sudeep Agarwal, Kristina Marotta, Siwei Li, Jonathan Leo, Duen Horng Chau.
Proceedings of the 18th ACM International Conference on Interaction Design and Children (IDC), 2019.
Boise, ID. Jun 12-15, 2019.
Won Best Work-in-Progress, Honorable Mention
NeuralDivergence: Exploring and Understanding Neural Networks by Comparing Activation Distributions.
Haekyu Park, Fred Hohman, Duen Horng (Polo) Chau.
IEEE Pacific Visualization Symposium (PacificVis) 2019.
Bangkok, Thailand. Apr 23-26, 2019.
Augmenting Coding: AugmentedReality for Learning Programming.
Nathan Dass, Joonyoung Kim, Sam Ford, Sudeep Agarwal, Duen Horng Chau.
The Sixth International Symposium of Chinese CHI (Chinese CHI 2018). Apr 21-22, 2018. Montreal, Canada.
Won Best Poster Award
3D Exploration of Graph Layers via Vertex Cloning.
James Abello, Fred Hohman, Duen Horng (Polo) Chau.
Poster Abstract, IEEE VIS 2017.
Atomic Operations for Specifying Graph Visualization Techniques.
Charles D. Stolper, Will Price, Matt Sanford, Duen Horng (Polo) Chau, John Stasko.
Poster Abstract, IEEE VIS 2017.
ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation.
Fred Hohman, Nathan Hodas, Duen Horng (Polo) Chau. Extended Abstracts, CHI 2017 May 6-11, 2017. Denver, CO, USA.
Carina: Interactive Million-Node Graph Visualization using Web Browser Technologies.
Dezhi (Andy) Fang, Mahew Keezer, Jacob Williams, Kshitij Kulkarni, Robert Pienta, Duen Horng (Polo) Chau.
26th International World Wide Web Conference (WWW) 2017 Companion. April 3-7, 2017. Perth, Australia.
Making Sense of Graph Query Results: Interactive Summarization and Exploration.
Robert Pienta, Alex Endert, Shamkant Navathe, Duen Horng Chau.
Poster Abstract, IEEE VIS 2016.
Oct 23 - 28, 2016. Baltimore, Maryland, USA.
NaturalMotion: Exploring Gesture Controls for Visualizing Time-Evolving Graphs.
Samuel Clarke, Nathan Dass, Duen Horng Chau.
Poster Abstract, IEEE VIS 2016.
Oct 23 - 28, 2016. Baltimore, Maryland, USA.
M3: Scaling Up Machine Learning via Memory Mapping.
Dezhi Fang, Duen Horng (Polo) Chau.
SIGMOD/PODS’16.
Generating Graph Snapshots from Streaming Edge Data.
Sucheta Soundarajan, Acar Tamersoy, Elias Khalil, Tina
Eliassi-Rad, Duen Horng Chau, Brian Gallagher and Kevin Roundy
25th International World Wide Web Conference 2016. Apr 11-15, 2016. Montreal, Canada
STEPS: A Spatio-temporal Electric Power Systems Visualization.
Robert Pienta, Leilei Xiong, Santiago Grijalva, Duen Horng Chau, Minsuk Kahng.
ACM Conference on Intelligent User Interfaces (IUI).
March 7-10, 2016. Sonoma, GA, USA.
Effort-based Detection of Comment Spammers.
Acar Tamersoy, Hua Ouyang and Duen Horng Chau
36th IEEE Symposium on Security and Privacy 2015. May 18-20, 2015. San Jose, CA, USA.
Spotting Suspicious Reviews via (Quasi-)clique Extraction.
Paras Jain, Shang-Tse Chen, Mozhgan Azimpourkivi, Duen Horng Chau and Bogdan Carbunar
36th IEEE Symposium on Security and Privacy 2015. May 18-20, 2015. San Jose, CA, USA.
TimeStitch: Interactive Multi-focus Cohort Discovery and Comparison.
Peter J. Polack, Jr., Shang-Tse Chen, Minsuk Kahng, Moushumi Sharmin, Duen Horng (Polo) Chau.
Poster Abstract, IEEE VIS 2015.
Oct 25 - 30, 2015. Chicago, IL, USA.
AdaptiveNav: Adaptive Discovery of Interesting and Surprising Nodes in Large Graphs.
Robert Pienta, Zhiyuan Lin, Minsuk Kahng, Jilles Vreeken, Partha P. Talukdar, James Abello, Ganesh Parameswaran, Duen Horng (Polo) Chau.
Poster Abstract, IEEE VIS 2015.
Oct 25 - 30, 2015. Chicago, IL, USA.
Interactive Querying over Large Network Data: Scalability, Visualization, and Interaction Design.
Robert Pienta, Acar Tamersoy, Hanghang Tong, Alex Endert, Duen Horng (Polo) Chau.
ACM Conference on Intelligent User Interfaces (IUI).
Atlanta, GA, USA. March 29 - April 1, 2015.
Identifying Successful Investors in the Startup Ecosystem.
Srishti Gupta, Robert Pienta, Acar Tamersoy, Duen Horng Chau, Rahul C. Basole.
International Conference on World Wide Web (WWW) 2015, May 18 -22, 2015. Florence, Italy
GLOs: Graph-Level Operations for Exploratory Network Visualization. Charles D. Stolper, Florian Foerster, Minsuk Kahng, Zhiyuan Lin, Aakash Goel, John Stasko, Duen Horng (Polo) Chau. Extended Abstracts, CHI 2014. Apr 26 - May 1, 2014. Toronto, Canada.
Interactive Multi-resolution Exploration of Million Node Graphs.
Zhiyuan (Jerry) Lin, Duen Horng (Polo) Chau. Poster Abstract, IEEE VIS 2013 Oct 13 - 18, 2013. Atlanta, GA, USA.
Fast Interactive Visualization for Multivariate Data Exploration.
Changhyun Lee, Wei Zhuo, Jaegul Choo, Duen Horng (Polo) Chau. Extended Abstracts, CHI 2013 Apr 27- May 2, 2013. Paris, France.
TopicViz: Semantic Navigation of Document Collections.
Jacob Eisenstein, Duen Horng (Polo) Chau, Aniket Kittur, Eric P. Xing. Extended Abstracts, CHI 2012. May 5-10, 2012. Austin, TX, USA.
Parallel Crawling for Online Social Networks.
Duen Horng (Polo) Chau, Shashank Pandit, Samuel Wang, and Christos Faloutsos. International Conference on World Wide Web (WWW) 2007. May 8-12, 2007. Banff, Alberta, Canada. Pages 201-210.
Integrating Isometric Joysticks into Mobile Phones for Text Entry. Duen Horng (Polo) Chau, Jacob O. Wobbrock, Brad A. Myers, Brandon Rothrock. Extended Abstracts, CHI 2006. April 22-27, 2006. Montreal, Canada. Pages 640-645.
Demos
Wordflow: Social Prompt Engineering for Large Language Models.
Zijie J. Wang, Aishwarya Chakravarthy, David Munechika, Duen Horng Chau.
Demo, ACL 2024.
MeMemo: On-device Retrieval Augmentation for Private and Personalized Text Generation.
Zijie J. Wang, Duen Horng Chau.
Demo, SIGIR 2024.
Best Short Paper, Honorable Mention
WizMap: Scalable Interactive Visualization for Exploring Large Machine Learning Embeddings.
Zijie J. Wang, Fred Hohman, Duen Horng Chau.
Demo, ACL 2023.
Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion
Seongmin Lee, Ben Hoover, Hendrik Strobelt, Zijie J. Wang, Anthony Peng, Austin Wright, Kevin Li, Haekyu Park, Alex Yang, Polo Chau.
Demo, CVPR 2023.
WebSHAP: Towards Explaining Any Machine Learning Models Anywhere.
Zijie J. Wang, Duen Horng (Polo) Chau.
Demo, WWW 2023.
DetectorDetective: Investigating the Effects of Adversarial Examples on Object Detectors.
Sivapriya Vellaichamy, Matthew Hull, Zijie Jay Wang, Nilaksh Das, ShengYun Peng, Haekyu Park, Duen Horng Polo Chau.
Demo, CVPR 2022.
VisCUIT: Visual Auditor for Bias in CNN Image Classifier.
Seongmin Lee, Zijie J. Wang, Judy Hoffman, Duen Horng (Polo) Chau.
Demo, CVPR 2022.
Visual Exploration of Literature with Argo Scholar.
Kevin Li, Haoyang Yang, Evan Montoya, Anish Upadhayay, Zhiyan Zhou, Jon Saad-Falcon and Duen Horng Chau.
Demo, CIKM 2022.
Dodrio: Exploring Transformer Models with Interactive Visualization.
Zijie J. Wang, Robert Turko, Duen Horng Chau.
Demo, ACL 2021
SkeletonVis: Interactive Visualization for Understanding Adversarial Attacks on Human Action Recognition Models.
Haekyu Park, Zijie J. Wang, Nilaksh Das, Anindya S. Paul, Pruthvi Perumalla, Zhiyan Zhou, Duen Horng Chau.
Demo, AAAI 2021.
MLsploit: A Framework for Interactive Experimentation with Adversarial Machine Learning Research.
Nilaksh Das, Siwei Li, Chanil Jeon, Jinho Jung, Shang-Tse Chen, Carter Yagemann, Evan Downing, Haekyu Park, Evan Yang, Li Chen, Michael Kounavis, Ravi Sahita, David Durham, Scott Buck, Duen Horng Chau, Taesoo Kim, Wenke Lee.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2019 Project Showcase.
Ankorage, Alaska. Aug 4-8, 2019.
MLsploit: A Cloud-Based Framework for Adversarial Machine Learning Research.
Nilaksh Das, Siwei Li, Chanil Jeon, Jinho Jung, Shang-Tse Chen, Carter Yagemann, Evan Downing, Haekyu Park, Evan Yang, Li Chen, Michael Kounavis, Ravi Sahita, David Durham, Scott Buck, Polo Chau, Taesoo Kim, Wenke Lee.
Black Hat Asia - Arsenal, 2019.
Singapore. Mar 26-29, 2019.
ADAGIO: Interactive Experimentation with Adversarial Attack and Defense for Audio.
Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Li Chen, Michael E. Kounavis, Duen Horng (Polo) Chau.
European Conference on Machine Learning & Principles & Practice of Knowledge Discovery in Databases (ECML-PKDD), 2018.
Dublin, Ireland. Sep 10-14, 2018.
Compression to the Rescue: Defending from Adversarial Attacks Across Modalities.
Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Siwei Li, Li Chen, Michael E Kounavis, Duen Horng Chau.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2018 Project Showcase.
London, United Kingdom. Aug 19-23, 2018.
Interactive Classification for Deep Learning Interpretation.
Ángel Alexander Cabrera, Fred Hohman, Jason Lin, Duen Horng (Polo) Chau.
Demo, Conference on Computer Vision and Pattern Recognition (CVPR).
June 18, 2018. Salt Lake City, USA.
mHealth Visual Discovery Dashboard.
Dezhi Fang, Fred Hohman, Peter Polack, Hillol Sarker, Minsuk Kahng, Moushumi Sharmin, Mustafa al'Absi, Duen Horng (Polo) Chau.
Demo, ACM International Joint Conference on Pervasive and Ubiquitous Computing (UBICOMP)
Sept 11-15, 2017. Maui, USA.
Visual Graph Query Construction and Refinement.
Robert Pienta, Fred Hohman, Acar Tamersoy, Alex Endert, Shamkant Navathe, Hanghang Tong, Duen Horng Chau.
SIGMOD 2017.
May 14-19, 2017.
Chicago, IL, USA.
Best Demo, Honorable Mention
Demonstrating Interactive Multi-resolution Large Graph Exploration.
Zhiyuan (Jerry) Lin, Nan Cao, Hanghang Tong, Fei Wang, U Kang, and Duen Horng (Polo) Chau.
ICDM 2013.
Dec 7 - 10, 2013. Dallas, Texas, USA.
Interactive Data Analysis Tool by Augmenting MATLAB with Semantic Objects.
Changhyun Lee, Jaegul Choo, Duen Horng (Polo) Chau, and Haesun Park.
ICDM 2013.
Dec 7 - 10, 2013. Dallas, Texas, USA.
Interactively and Visually Exploring Tours of Marked Nodes in Large Graphs.
Duen Horng (Polo) Chau, Leman Akoglu, Jilles Vreeken, Hanghang Tong, Christos Faloutsos.
ASONAM 2012.
Aug, 2012. Istanbul, Turkey
TourViz: Interactive Visualization of Connection Pathways in Large Graphs.
Duen Horng (Polo) Chau, Leman Akoglu, Jilles Vreeken, Hanghang Tong, Christos Faloutsos. KDD 2012.
Aug, 2012. Beijing, China
Large Graph Mining System for Patterns, Anomalies & Visualization.
Leman Akoglu, Duen Horng (Polo) Chau, U Kang, Danai Koutra, Christos Faloutsos.
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2012.
May 29-Jun 1, 2012. Kuala Lumpur, Malaysia
OPAvion: Mining and visualization in large graphs.
Leman Akoglu, Duen Horng (Polo) Chau, U Kang, Danai Koutra, Christos Faloutsos.
ACM SIGMOD Conference 2012.
May 20-24, 2012. Scottsdale, Arizona, USA
Apolo: Interactive Large Graph Sensemaking by Combining Machine Learning and Visualization.
Duen Horng (Polo) Chau, Aniket Kittur, Jason I. Hong, Christos Faloutsos.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2011.
Aug 21-21, 2011. San Diego, California, USA.
SHIFTR: A Fast and Scalable System for Ad Hoc Sensemaking of Large Graphs.
Duen Horng (Polo) Chau, Aniket Kittur, Christos Faloutsos, Hanghang Tong, Jason I. Hong.
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2009.
June 28-July 1, 2009. Paris, France.
GRAPHITE: A Visual Query System for Large Graphs.
Duen Horng (Polo) Chau, Christos Faloutsos, Hanghang Tong, Jason I. Hong, Brian Gallagher, Tina Eliassi-Rad.
International Conference on Data Mining (ICDM) 2008.
Dec 15-19, 2008. Pisa, Italy.
Video
SHIFTR: a user-directed, link-based system for ad hoc sensemaking
of large heterogeneous data collections.
Duen Horng (Polo) Chau, Aniket Kittur, Christos Faloutsos, Jason I. Hong.
Extended Abstracts of CHI 2009.
Apr 4-9, 2009. Boston, MA.
Ph.D. Students
Advisor
Aeree Cho, ML PhD
Fall 2024 - present.
Fall 2024 - present.
Rising Star Doctoral Student Research Award (Outstanding 1st year PhD student)
Mansi Phute, CS PhD
Summer 2024 - present.
Summer 2024 - present.
Shengyun (Anthony) Peng, CS PhD
Spring 2022 - present.
Spring 2022 - present.
Seongmin Lee, CS PhD
Fall 2021 - present.
Fall 2021 - present.
Ben Hoover, ML PhD
Fall 2021 - present.
Fall 2021 - present.
Rahul Duggal, CS PhD
Fall 2019 - Summer 2022. Co-adv: Jimeng Sun.
Thesis: Robust Efficient Edge AI: New Principles and Frameworks for Empowering AI on Edge Device
Proposal: 10/22/21. Defense: 07/14/22
Fall 2019 - Summer 2022. Co-adv: Jimeng Sun.
Thesis: Robust Efficient Edge AI: New Principles and Frameworks for Empowering AI on Edge Device
Proposal: 10/22/21. Defense: 07/14/22
Amazon Post Internship Fellowship
Now: Applied Scientist II, AWS AI Computer Vision Group
Austin Wright, ML PhD
Fall 2019 - present.
Fall 2019 - present.
ORISE Fellow, National Center for Injury Prevention and Control
GT-GSU Public Interest Technology (PIT) Fellow, 2020
Georgia Tech President's Fellowship
Zijie (Jay) Wang, ML PhD
Fall 2019 - Fall 2024.
Fall 2019 - Fall 2024.
SIGCHI Outstanding Dissertation Award
Outstanding Doctoral Dissertation Award, College of Computing, Georgia Tech
Georgia Tech Sigma Xi Best Ph.D. Thesis Award
Forbes 30 Under 30 in Science
Apple Scholar, 2023. Only 22 awardees in AI/ML PhD fellowship worldwide.
JPMorgan AI PhD Fellowship, 2022
Now: Researcher, OpenAI
Haekyu Park. CS PhD.
Fall 2018 - Fall 2023.
Thesis: Interactive Scalable Discovery of Concepts, Evolutions, and Vulnerabilities in Deep Learning
Proposal: 11/15/22.
Fall 2018 - Fall 2023.
Thesis: Interactive Scalable Discovery of Concepts, Evolutions, and Vulnerabilities in Deep Learning
Proposal: 11/15/22.
Rising Star in EECS 2022
JPMorgan AI PhD Fellowship, 2021
Now: Machine Learning Engineer, Stripe
Scott Freitas. ML PhD.
Fall 2018 - Fall 2021.
Thesis: Developing Robust Models, Algorithms, Databases, and Tools with Applications to Cybersecurity and Healthcare
Proposal: 05/12/21. Defense: 12/07/21
Fall 2018 - Fall 2021.
Thesis: Developing Robust Models, Algorithms, Databases, and Tools with Applications to Cybersecurity and Healthcare
Proposal: 05/12/21. Defense: 12/07/21
IBM PhD Fellowship, 2021
NSF Graduate Research Fellowship, 2018-2021
Raytheon Graduate Research Assistantship, 2019. $25k.
Now: Senior Applied Scientist, Microsoft
Nilaksh Das. CSE PhD.
Fall 2017 - Spring 2022.
Thesis: Understanding, Fortifying and Democratizing AI Security
Proposal: 04/14/21. Defense: 04/13/22
Fall 2017 - Spring 2022.
Thesis: Understanding, Fortifying and Democratizing AI Security
Proposal: 04/14/21. Defense: 04/13/22
Best Dissertation Award, College of Computing, Georgia Tech
Now: Applied Scientist, Amazon Web Services (AWS)
Fred Hohman. CSE PhD.
Summer 2016 - Fall 2020.
Thesis: Interactive Scalable Interfaces for Machine Learning Interpretability
Proposal: 12/02/19. Defense: 10/06/20
Summer 2016 - Fall 2020.
Thesis: Interactive Scalable Interfaces for Machine Learning Interpretability
Proposal: 12/02/19. Defense: 10/06/20
SIGCHI Outstanding Dissertation Award, 2022
Best Dissertation Award, College of Computing, Georgia Tech
NASA Space Technology Research Fellowship 2018-2021. ~$80k/yr
Georgia Tech President's Fellowship
Now: Research Scientists, Apple
Shang-Tse Chen. CS PhD. Co-adv: Nina Balcan.
Fall 2014 - Fall 2019.
Thesis: AI-infused Security: Robust Defense by Bridging Theory and Practice
Proposal: 11/16/18. Defense: 08/19/19
Fall 2014 - Fall 2019.
Thesis: AI-infused Security: Robust Defense by Bridging Theory and Practice
Proposal: 11/16/18. Defense: 08/19/19
IBM PhD Fellowship, 2018-2020
Symantec Research Labs (SRL) Graduate Fellowship 2016, runner-up
Now: Assistant Professor, National Taiwan University (NTU)
Minsuk (Brian) Kahng. CS PhD.
Fall 2013 - Fall 2019.
Thesis: Human-Centered AI through Scalable Visual Data Analytics
Proposal: 10/15/18. Defense: 10/08/19
Fall 2013 - Fall 2019.
Thesis: Human-Centered AI through Scalable Visual Data Analytics
Proposal: 10/15/18. Defense: 10/08/19
Best Dissertation Award, College of Computing, Georgia Tech
Google PhD Fellowship, 2018-2020
NSF Graduate Research Fellowship, 2014-2017
Now: Research Scientist, Google
Robert Pienta. CSE PhD.
Spring 2013 - Fall 2017.
Thesis: Adaptive Visual Network Analytics: Algorithms, Interfaces, and Systems for Exploration and Querying
Proposal: 4/6/16. Defense: 6/27/17
Spring 2013 - Fall 2017.
Thesis: Adaptive Visual Network Analytics: Algorithms, Interfaces, and Systems for Exploration and Querying
Proposal: 4/6/16. Defense: 6/27/17
Now: Data Science Manager, Intuit
Acar Tamersoy. CS PhD. Co-adv: Sham Navathe.
Spring, 2013 - Spring 2016.
Thesis: Graph-based Algorithms and Models for Security, Healthcare, and Finance
Proposal: 11/6/15. Defense: 3/11/16.
Spring, 2013 - Spring 2016.
Thesis: Graph-based Algorithms and Models for Security, Healthcare, and Finance
Proposal: 11/6/15. Defense: 3/11/16.
Symantec Research Labs (SRL) Graduate Fellowship, 2014-2015
Now: Principal Applied Scientist, Microsoft
Co-advisor
Chad Stolper. CS PhD. Adv: John Stasko.
Spring 2014 - Summer 2016.
Thesis: Graph-Level Operations: A High-Level Interface for Graph Visualization Specification
Proposal: 5/1/15. Defense: 7/1/16.
Spring 2014 - Summer 2016.
Thesis: Graph-Level Operations: A High-Level Interface for Graph Visualization Specification
Proposal: 5/1/15. Defense: 7/1/16.
Now: Software Engineer, Google
Research Project Advisor
Abhijit Suprem. CS. Fall 2017.
Liexiao (Richard) Ding. ISyE. Adv: Nagi Gebraeel. Fall 2016.
Oliver Haimson. Ph.D. Informatics Department. UC Irvine. Co-adv: Bistra Dilkina, Matt Hinds-Aldrich. Summer 2015.
Wenwen Chang. Ph.D. City and Regional Planning. Co-adv: Bistra Dilkina, Matt Hinds-Aldrich. Summer 2015.
Can Hantas. Co-adv: Sham Navathe. Spring 2014
Dr. Jaegul Choo. CSE. Adv: Haesun Park. Spring 2013 - Fall 2014.
Now: Assistant Professor, Korea University
Kunal Malhotra. CS. Adv: Sham Navathe. Spring 2013 - Spring 2014.
Kaeser Puryear Sabrin. CS. Fall, 2013.
Wei (Tina) Zhou. IC. Adv: Jarek Rossignac. Spring 2013 - Fall 2013.
Bo Xie. CSE. Fall 2012 - Spring 2013.
Post Docs
Dongkyu Chae. Fall 2019 - Summer 2020
Now: Assistant Professor, Hanyang University, South Korea
Masters Students
MS Thesis Advisor
Elias Khalil. CSE. Spring 2013 - Spring 2014.
Thesis: Optimizing the Structure of Diffusion Networks: Theory and Algorithms
Now: Assistant Professor, University of Toronto
Marshall D. Williamson Fellowship, for well-rounded second-year Masters' students, Spring 2014
Donald V. Jackson Fellowship, for well-rounded first year Masters' students, Spring 2013
Now: CSE/CoC PhD student
Research Proj Advisor
Aeree Cho, CS MS. Spring 2024 - present.
Now: ML PhD student, Georgia Tech
Alex Karpekov, CS MS. Spring 2024.
Now: CS PhD student, Georgia Tech
Justin Blalock, CS MS. Fall 2023 - Spring 2024.
Now: Software Engineer, Meta
Harsha Karanth, CS MS. Fall 2023 - Spring 2024.
Now: Deep Learning Engineer, Toyon Research Corporation
Mansi Phute, CS MS. Summer 2023 - Spring 2024.
Marshall D. Williamson Fellowship, for well-rounded second year Masters' students, Spring 2024
Now: CS PhD student, Georgia Tech
Nemath Ahmed. CS MS. Spring 2023.
Chakri RVK. Analytics MS. Summer 2022 - Spring 2023.
Shengyun (Anthony) Peng. CSE MS. Summer 2021 - Fall 2021.
Sivapriya Vellaichamy. Analytics MS. Summer 2021 - Spring 2022.
Now: AI Research Tech - Senior Associate, JP Morgan Chase
Soo Hyung Park. MS CS. Summer 2021.
Isha Shah. MS CS. Summer 2021.
Jonathan Leo. MS CS. Spring 2021 - Spring 2022.
Sushanto Praharaj. MS CSE. Summer 2020, Spring 2021.
Marshall D. Williamson Fellowship, for well-rounded second year Masters' students, Spring 2021
Now: Software Engineer, Salesforce
Aiswarya Bhagavatula. MS CSE. Summer 2020, Spring 2021.
Now: Analyst, Goldman Sachs
Pruthvi Perumalla. MS CS. Summer 2020.
Now: Software Engineer, Microsoft
Anmol Chhabria. MS CSE. Spring 2019.
Donald V. Jackson Fellowship, for well-rounded first year Masters' students, Spring 2019
Now: Senior Data Scientist, Shopify
Kristina Marotta. OMS CS. Fall 2018.
Varun Bezzam. MS CS. Fall 2017 - Fall 2018
Now: Senior Software Engineer, Lyft
Madhuri Shanbhogue. MS CS. Spring 2017 - Spring 2018
Now: Software Engineer ML, Google
Prasenjeet Biswal. MS CS. Spring 2017 - Fall 2018
Now: Software Engineer II (Machine learning), Yahoo
Nilaksh Das. MS CSE. Spring 2017
Chirag Tailor. MS CS. Summer 2016 - Spring 2017.
Michael Phillips. MS Analytics. Fall 2016.
Peter Polack. MS CS. Fall 2015 - Fall 2016.
Now: PhD student, UCLA
Meera Kamath. MS CS. Spring 2016.
Now: Microsoft
Apurv Verma. MS CS. Spring 2016.
Michael Madaio. MS Digital Media. Summer 2015. Co-adv: Bistra Dilkina, Matt Hinds-Aldrich.
Now: HCI Ph.D. student, Carnegie Mellon
Xiang (Sean) Cheng. MS Computer Science & Physics. Emory University. Summer 2015. Co-adv: Bistra Dilkina, Matt Hinds-Aldrich.
Now: Nokia Technologies
Alexandre Yahi. MS CS Summer 2014 - Spring 2015
Now: PhD student, Biomedical Informatics, Columbia University
Antoine Chassang. MS CS. Summer 2014 - Spring 2015
Louis Raynaud. MS CS. Summer 2014 - Spring 2015
Now: Wavestone
Hugo Duthil. MS CS. Summer 2014 - Spring 2015
Now: Criteo
Mayank Gupta. Co-adv: Rahul Basole. MS CS. Fall 2014 - Spring 2015.
Now: Apple
Florian Foerster. MS HCI. Spring 2014 - Fall 2014.
Now: Facebook software engineer
Ganesh Parameswaran. MS CSE. Fall 2013.
Now: Yahoo! software engineer
Changhyun Lee. MS CSE. Adv: Haesun Park. Fall 2012 - Spring 2013.
Now: Google software engineer
Neha Reddy. MS Info Networking, CMU. 2009.
Now: Cvent software engineer
Karthik Thiyagarajan. MS Info Networking, CMU. 2009.
Now: QuantFind software engineer
Masters Project
Shan Li. MS HCI. Fall 2014 - Spring 2015.
Project: A Course/Major Recommendation System for Georgia Tech Students
Placed: Oracle
Srishti Gupta. MS CS. Spring 2014 - Spring 2015.
Project: A Study of Venture Capitalists through Graph Analysis
Now: Apple
Aakash Goel. MS CSE. Spring, Fall 2013.
Project: Improvements to Apolo (a Machine Learning Based Graph Visualization and Analysis System for Large Network Data)
Placed: Google software engineer
MS Special Problem
Vivek Nahbi. MS CS. Spring 2014 - Summer 2014.
Project: Systematic Integration of Large Data Sets for Improved Decision-Making.
Jon Greg. MS CSE. Fall 2012.
Project: Anomaly detection for graphs
Zhen (Henry) Wang. MS CSE. Fall 2012.
Project: Large graph decomposition
Ziaohui Luo. IC. Fall 2012.
Project: Graph visualization on mobile devices
Instructional Associate Researcher
Matthew Hull, Instructional Associate, Georgia Tech. May 2021 - May 2023.
Undergraduate Students
Research Advisor
Vidhi Kulkarni. CS. Spring 2025 - present.
Elliott Faa. CS. Spring 2025 - present.
Kunal Mohindra. CS. Fall 2024 - present.
Rahul Narayanan. CS. Spring 2024 - present.
President's Undergraduate Research Travel Award
Chae Yeong (Grace) Kim. CS. Spring 2024 - present.
Aishwarya Chakravarthy. CS. Fall 2023 - present.
Sri Ranganathan Palaniappan. CS. Fall 2023 - present.
Outstanding Legacy Leadership Award, Spring 2025
Mahesh Natamai. CS. Spring 2023.
Sagar Sadak. CS. Fall 2022 - Spring 2023.
Shirling Xu. CS. Fall 2022.
David Munechika. CS BS/MS. Fall 2021 - Spring 2024.
Stamps President's Scholar
Now: Machine Learning Engineer, Apple
Pratham Mehta. CS BS/MS. Fall 2021 - present.
Donald V. Jackson Fellowship (Outstanding 1st year MS student), Spring 2025
Outstanding Legacy Leadership Award, Spring 2024
Outstanding Second Year Leadership Award, Spring 2023
Evan Montoya. CS. Fall 2021 - Summer 2023.
Stamps President's Scholar
Carter Coté. CS. Fall 2021.
Megan Dass. CS. Fall 2020 - Spring 2023.
2022 Adobe Women in Technology (WIT) Scholar
Outstanding Freshman Award, College of Computing
Featured in Georgia Tech Compiler news story Cropping Made Easy, for the MagicCrop system that automatically crop headshot photos using AI.
Alex Yang. CS BS/MS. Fall 2020 - Spring 2023.
Donald V. Jackson Fellowship Award (outstanding 1st year MS)
Kevin Li. CS. Fall 2020 - Spring 2023.
Undergraduate Teaching Assistant of the Year, Georgia Tech.
Outstanding Undergraduate Teaching Assistant, College of Computing, Georgia Tech.
Provost’s Academic Excellence Award, Georgia Tech.
Now: ML PhD student, Carnegie Mellon
Sasha Richardson. CS undergraduate student, Fayetteville State University. Summer 2020.
Robert Firstman. CS. Fall 2019 - Spring 2020.
Now: Software Engineer, Meta
Robert Turko. CS. Fall 2019 - Spring 2021.
Now: Software Engineer, Google
Outstanding Senior Award, College of Computing.
Jon Saad-Falcon. CS. Fall 2019 - Fall 2020.
Now: CS PhD student, Stanford
Donald V. Jackson Fellowship, for well-rounded first year Masters' students, Spring 2021
Zhiyan (Frank) Zhou. CS. Fall 2019 - Spring 2022.
Anish Upadhayay. CS. Fall 2019 - Spring 2022.
Omar Shaikh. CS. Fall 2018 - Spring 2022.
Now: CS Ph.D. student, Stanford
Awarded Sigma Xi Best Undergraduate Research Award (Spring 2021)
Outstanding Freshman, College of Computing, Georgia Tech. 2020.
Awarded President's Undergraduate Research Travel Award (PURA) ($1500, Spring'20)
Will Epperson. CS. Spring 2019 - Spring 2020.
Now: CS Ph.D. student, Carnegie Mellon University
Stamps President's Scholar, Aug 2016-May 2020. Full-ride scholarship, awarded to 40 students.
Awarded President's Undergraduate Research Travel Award (PURA) ($1500, Fall'19)
Jonathan Leo. CS. Spring 2019 - Fall 2020.
Awarded President's Undergraduate Research Travel Award (PURA) ($1500, Fall'19)
Ángel (Alex) Cabrera. CS. Spring 2018 - Spring 2019.
Now: HCI Ph.D. student, Carnegie Mellon University
NSF Graduate Research Fellowship, 2019-
Co-repicient of Love Family Scholarship ($10,000 total), highest award Georgia Tech gives to a graduating senior. 2019.
Stamps President's Scholar, Aug 2015-May 2019. Full-ride scholarship, awarded to 10 students.
Siwei (Bob) Li. CS. Fall 2017 - Spring 2020.
Now: Software Engineer, Google
Outstanding Undergraduate Research, College of Computing, Georgia Tech. 2020.
Awarded President's Undergraduate Research Travel Award (PURA) ($1500, Fall'19)
Sudeep Agarwal. CS. Fall 2017 - Fall 2018.
Now: Machine Learning Engineer, Apple
Dezhi (Andy) Fang. CS. Fall 2015 - Spring 2018.
Now: Software Engineering, Citadel
Outstanding Undergraduate Research, College of Computing, Georgia Tech. 2018.
Outstanding Undergraduate Researcher, Georgia Tech. 2018.
Research supported by Faculty Materials, Supplies and Travel Grants for Undergraduate Research ($1000, Summer'17)
Awarded President's Undergraduate Research Travel Award (PURA) ($1500, Fall'16)
SIGMOD'16 Undergraduate Research Poster Competition Finalist
Yili Hui. CS. Fall 2017 - Spring 2018.
Now: Software Engineer, Microsoft
Joon Kim. CS. Fall 2017 - Spring 2019.
Now: Mailchimp
Joseph Spall. CS. Fall'17.
Now: MS ECE student, Georgia Tech
Michael Aki. CS. Fall'17.
Now: Software Engineer, Amazon
D'arcy (Quintin) Roper. CS. Fall'17.
Now: Technology Solutions Senior Consultant, Credera
Kshitij Kulkarni. EE. Fall 2016 - Spring 2017.
Now: EECS PhD student, UC Berkeley
Jake Williams. CS. Spring 2016 - Spring 2017.
Now: Machine Learning Engineer, Square
Fu Shen. CS. Summer 2016. Co-adv: Fang (Cherry) Liu.
Now: MS CSE student, Georgia Tech
Matthew Keezer. CS. Fall 2015 - Spring 2017.
Now: Staff Software Engineer, IBM
Jay Kamat. CS. Fall 2015 - Spring 2016.
Now: Performance and Capacity Engineer, Meta
Neil Goel. CS. Fall 2015.
Now: Software Engineer, Google
Francisco Zampieri. CS. Fall 2015.
Now: Application Developer Lead, Fiserv
Mika Munch. CS. Fall 2015.
Now: Service Design Lead, Banking, NCR
Goutam Venkatramanan. CS. Fall 2015.
Now: Software Engineer, Meta
Sam Ford. CS. Summer 2015 - Fall 2017.
Now: Machine Learning Engineer, Cash App
Ryan Birmingham. CS. Summer - Fall 2015.
Now: Systems Software Engineer, Emory University School of Medicine
Junxian (Rupert) Wu. CS. Summer 2015.
Now: Software Engineer, Google
Arman Rye. ISyE. Fall 2014 - Spring 2015.
Now: Cloud Customer Engineer, Google
Gustavo Oliver. ISyE. Fall 2014 - Spring 2015.
Now: Senior Data Engineer, Orchard
Nathan Dass. CS. Fall 2014 - Fall 2017.
Now: Senior Software Engineer, Google AI
2nd Place InVenture Prize 2017. $10,000 award
Research supported by Faculty Materials, Supplies and Travel Grants for Undergraduate Research ($1000, Summer'17)
Wearable Computing Center Grant (with Samuel Clarke) (~$1000, Fall 2014)
Paras Jain. CS. Fall 2014 - Spring 2017.
Now: EECS PhD student, UC Berkeley
Awarded President's Undergraduate Research Travel Award (PURA) twice (Spring'16: $1000; Spring'17: $1500)
Yiqi (Victor) Chen. CS. Fall 2013 - Spring 2016.
Now: Software Engineer, Meta
Awarded President's Undergraduate Research Travel Award (PURA) ($1000, Spring'15)
Zhiyuan (Jerry) Lin. CS. Spring 2013 - Spring 2016.
Now: Research Scientist, Meta (after CS PhD, Stanford)
Computing Research Association's (CRA) Outstanding Undergraduate Researcher Award, finalist
Outstanding Undergraduate Research in Computing Award (2015)
Chosen as Georgia Tech representative for 10th Annual ACC Meeting of the Minds Conference at NC State University
Awarded President's Undergraduate Research Travel Award (PURA) ($1000, Fall'14)
1st place, 9th Undergraduate Research Kaleidoscope (URK). Oct 2014.
Awarded Sigma Xi Best Undergraduate Research Award ($200, plaque, certificate, Spring 2014)
2nd Place, 9th Annual Undergraduate Research Symposium at Georgia Tech's College of Computing, Spring 2014
Awarded President's Undergraduate Research Salary Award (PURA) ($1500, Fall'13)
Funded by Faculty Materials, Supplies and Travel Grants for Undergraduate Research ($1000, Summer'13)
Awarded to attend the prestigious SC13 (SuperComputing) Experiencing HPC for Undergraduates program. 25 total awardees worldwide.
Samuel Clarke. CS. Co-adv: Hongyuan Zha. Spring 2013 - Fall 2016.
Now: CS Ph.D. student, Stanford
Astronaut Scholarship (2015) -- among the most prestigious scholarships awarding the best and brightest undergraduate students pursuing education in STEM across the nation.
LatentGesture research featured in popular press
Wearable Computing Center Grant (with Nathan Dass) (~$1000, Fall 2014)
Premkumar (Prem) Saravanan. CS. Co-adv: Hongyuan Zha. Summer 2013 - Spring 2014.
Awarded President's Undergraduate Research Salary Award (PURA) ($1500, Spring'14)
LatentGesture research featured in popular press
Samarth Agarwal. CS. Spring 2013.
Now: Software Engineer, Google
Sahil Jolly. CS, CMU. 2010.
Sam Wang. CS, CMU. 2006 - 07.
Project: eBay fraud detection
→ PhD student at MIT
High School Students
Research Advisor
Ergin John (EJ) Ozyazgan, Walton high school. Spring 2015 - Summer 2015.
Visiting Scholars
Hugo Armando Gualdron Colmenares, visiting from Universidade de São Paulo. Oct 2014 - Mar 2015.
Keynotes & Invited Talks
Mar 4, 2024
Apple. Host: Dominik Moritz.
Oct 3, 2023
[Keynote] GSU Scientific Computing Day.
Mar 3, 2023
[As ACM Distinguished Speaker] California State University, Chico. Host: David Zeichick.
Sept 19, 2022
Carnegie Mellon University CyLab Seminar. Host: Prof. Bryan Routledge.
Sept 8, 2022
Cisco Responsible AI Summit. Host: Dr. Ali Payani.
UniTable: Towards a Unified Table Foundation Model
Mar 8, 2024
ADP. Host: Xiaojing Wang. Presenters: ShengYun (Anthony) Peng, Polo Chau
Towards Safe and Interpretable AI
Oct 24, 2021
[Keynote] Visualization in Data Science (VDS) at IEEE VIS 2021
Interactive Scalable Visualizations for Data Discoveries and Interpretable AI
June 24, 2021
[Keynote] SIGMOD 2021 Curated Session of Interactive Data Exploration. [YouTube]
Towards Secure and Interpretable AI: Scalable Methods, Interactive Visualizations, and Practical Tools
Aug 23, 2021
[As ACM Distinguished Speaker] San Francisco Bay ACM Chapter. Host: Greg Makowski.
Jul 8, 2021
Square. Host: Omar Shaikh.
May 25, 2021
American Statistical Association (ASA), Statistical Learning and Data Science
May 14, 2021
Megagon Labs. Host: Estevam Hruschka.
Jan 21, 2021
PNNL-GT workshop
Jun 4, 2020
SDSS Symposium on Data Science & Statistics
Dec 6, 2019
New York University. Host: Enrico Bertini
Nov 15, 2019
Chick-fil-A. Hosts: Jae Cha, Jon Hadacek, Melinda Borrero, Cameron Bradley
Nov 6, 2019
IEEE Data Mining Series, Georgia State University
Aug 29, 2019
GVU Center Brown Bag Seminar, Georgia Tech.
Aug 13, 2019
Jun 27, 2019
Intel Tech Talk
Secure AI: The Next Frontiers
Oct 9, 2019
Intel Labs Open House
Adversarial Machine Learning: Perspectives & Recent Developments
Jul 29, 2019
Intel
Human-centered AI: Scalable Interactive Tools for Interpretation & Attribution
Jun 11, 2019
Apr 23, 2019
Strategic Partnership Program meeting
Explaining Machine Learning Models Using Interactive Visualization
Mar 14, 2019
NASA Jet Propulsion Lab (JPL). Host: Scott Davidoff
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
Aug 12, 2018
ACM SIGGRAPH. Delivered by Minsuk Kahng.
Jun 10, 2018
SIGMOD Workshop on Human-in-the-Loop Data Analytics (HILDA). Delivered by Minsuk Kahng.
Data Mining meeting HCI: Human-Machine Sensemaking of Large Graphs
Apr 14, 2017
Rutgers University. Host: James Abello
Apr 7, 2017
Southern Data Science Conference, Atlanta.
Machine Learning meets Visualization: Human-machine Sensemaking of Large Network Data
Feb 5, 2016
Centers for Disease Control and Prevention (CDC), Atlanta. Host: Robin Wagner.
Data Mining Meets HCI: Interactive Visual Tools for Large Graphs
Feb 16, 2017
Machine Learning Data Analysis Webminar. South Big Data Hub.
May 17, 2016
MIT Lincoln Lab Graph Exploitation Symposium 2016
Jan 29, 2016
Carnegie Mellon University, Human-computer Interaction Institute (HCII) Seminar Series. Host: Brad Myers, Queenie Kravitz
June 21, 2017
June 8, 2016
Data and Visual Analytics 101
Summer, 2015
Atlanta Data Science for Social Good 2015.
Faculty advisor student team. Co-advisors: Bistra Dilkina, Matt Hinds-Aldrich (Atlanta Fire Rescue Department)
Catching Bad Guys with Graph Mining and Visualization
Dec 17, 2015
Yahoo Labs, New York
Oct 10, 2015
Emory University Institute for Quantitative Theory and Methods, Data Visualization seminar series
Mar 9-10, 2015
Machine Learning and Data Analytics Symposium (MLDAS). Doha, Qatar. Host: Dragos Margineantu
Human-in-the-loop Graph Sensemaking: Bridging HCI and Data Mining
Dec 12, 2014
HCI meets Data Mining: Interactive Graph Visualization, Exploration, and Sensemaking
Jun 12, 2016
Computer Society International Conference on Computers, Software & Applications (COMPSAC) 2016
Interactive Graph Visualization, Exploration, and Sensemaking
Dec 10, 2014
FLAMEL workshop
Scalable, Interactive Tools for Large Graph Analytics
Oct 27, 2014
[Keynote] Scalable Machine Learning: Theory and Applications workshop at IEEE International Conference on Big Data (IEEE BigData 2014)
Oct 2, 2014
[Keynote] Undergraduate Research Kaleidoscope. Jointly hosted by Georgia Tech Library and the Undergraduate Research Opportunities Program.
Data Mining Meets HCI: Scalable, Interactive and Comprehensible Tools for Data Analytics
Nov 18, 2015
Career Builder Distinguished Speaker Series. Host: Khalifeh Al Jadda
Oct 17, 2015
Northwestern University, SONIC Speaker Series. Host: Noshir Contractor
Feb 13, 2015
Twitter. Host: Shuang Yang.
Jun 24, 2014
PARC (Palo Alto Research Center Incorporated). Hosts: Oliver Brdiczka, David Gunning.
Jun 6, 2014
Search Technology Forum, eBay.
Apr 26, 2014
2014 SIAM Data Mining (SDM) Workshop on Exploratory Data Analysis.
Mar 13, 2014
Jan 16, 2014
Big Data Chalk & Talk/Brown Bag. Georgia Tech.
Data Mining Meets HCI: Scalable, Interactive Tools for Large Graphs
Nov 5, 2013
Rutgers University. Host: Prof. Tina Eliassi-Rad.
Nov 4, 2013
Bell Labs. Host: Chun-Nam (John) Yu.
Data Mining Meets HCI: Making Sense of Large Graphs
Jun 28, 2013
Goodreads. Host: Jeff Wong.
Mar 15, 2013
Stanford HCI seminar. Host: Prof. Jeff Heer.
Feb 11, 2013
LogicBlox. Host: Nikolaos (Nick) Vasiloglou II.
Nov 28, 2012
UC Berkeley iSchool Dean's Lecture. Host: Prof. Marti Hearst
Oct 25, 2012
Linkedin. Host: Dr. Daniel Tunkelang, Dr. Monica Rogati
Sept 26, 2012
Hong Kong University, School of Business. Host: Prof. Michael Chau
Oct 11, 2012
IBM (T.J. Watson Research Center). Host: Dr. Hanghang Tong.
June 11, 2012
Huawei Noah Ark Research Lab, Hong Kong. Host: Prof. Qiang Yang.
May 28, 2012
Hong Kong University of Science and Technology. Host: Lionel Li
Apr 16, 2012
University of Pittsburgh, School of Information. Pittsburgh, PA, USA. Host: Prof. Peter Brusilovsky.
Apr 6, 2012
Georgia Tech, School of Computational Science & Engineering. Atlanta, Georgia, USA.
Apr 2, 2012
Virginia Tech, Computer Science Department. Blacksburg, Virginia, USA.
Mar 26, 2012
University of Rochester, Computer Science Department. Rochester, New York, USA.
Mar 20, 2012
Stony Brook University, Computer Science Department. Stony Brook, New York, USA.
Mar 13, 2012
Brown University, Computer Science Department. Providence, Rhode Island, USA.
Mar 7, 2012
University of Michigan, School of Information. Ann Arbor, Michigan, USA.
Feb 27, 2012
Pennsylvania State University, College of Information Sciences and Technology. State College, Pennsylvania, USA.
Feb 24, 2012
Carnegie Mellon University, Tepper School of Business. Pittsburgh, Pennsylvania, USA.
Exploiting Network Effects for Fraud and Malware Detection
Aug 2, 2013
The Third EITA Young Investigator Conference (EITA-YIC 2013), MIT. Invited
Large Graph Analytics: Anomaly Detection & Visualization
Mar 24, 2013
SIAM SEAS mini symposium on Anomaly Detection Methods and Applications. Invited by Dr. Blair Sullivan, Dr. Robert Bridges.
June 4, 2012
Singapore Management University. Host: Kyriakos Mouratidis
Mining Billion-Node Graphs: Ideas & Tools
May 28, 2012
Carnegie Mellon University, Tepper School of Business. Pittsburgh, Pennsylvania, USA. Invited.
Mining Massive Graphs: Visualization and Anomaly Detection
May 13, 2011
Google. Mountain View, CA, USA
May 10, 2011
Simon Fraser University. Vancouver, Canada. Host: Prof. Jian Pei. Invited.
Detecting Fraudulent Personalities in Networks of Online Auctioneers
Feb 16, 2007
eBay. Palo Alto, CA, USA. Invited.
Professional Recognition
Since Jun, 2020
Invited Panelist
Oct 26, 2023
IEEE VIS'23 panel: How should VIS4ML Redefine Itself in the Rapid Evolution of AI?
Sept 8, 2022
Cisco Responsible AI Summit
Jul 25, 2022
Vis for AI: How can Vis help build better AI models? panel at Opportunities between AI and Visualization workshop. Host: Prof. Enrico Bertini, Northeastern University.
Nov 11, 2021
Explainable vs. Ethical AI: Just Semantics? Panel, 2021 CATT Global Analytics Summit on Explainable AI (XAI), University of Texas
May 5, 2021
TAG Data Science & Analytics Explainable AI
Nov 10, 2020
IDEaS panel on Getting Started in Data Science and Machine Learning (panelist), Georgia Tech
May 27, 2020
Education panel on Visualization for Data Science (panelist), Eurographis & EuroVis 2020
Apr 7, 2020
Keep Teaching: Advice from Thank a(n Online) Teacher Recipients
Dec 12, 2019
Ask A Prof! inaugural blog post of On Teaching and Learning @ Georgia Tech
Jul 9, 2019
Undergraduate Research Faculty Panel (panelist), Georgia Tech
Jun 10, 2018
SIGMOD 2018 Workshop on Human-In-the-Loop Data Analytics (HILDA).
Mar 4, 2016
FLAMEL (NSF IGERT) Workshop.
Feb 5, 2016
Seeing for Action - Using Maps and Graphs to Protect the Public’s Health.
Centers for Disease and Prevention (CDC). Host: Robin Wagner.
Sept 22, 2015
Technology Association of Georgia (TAG) Big Data Panel on
Topic: What are we teaching in Big Data in our universities?
Oct 16, 2013
IEEE Vis'2013 Workshop on Using Visual Analytics to Foster Lateral Thinking About Business Problems. Host: Chandan Gokhale (Infosys)
Apr 30, 2013
PACE Town Hall panel, on HPC, visualization
Dec 11, 2012
SAMSI-FODAVA Workshop on Interactive Visualization and Analysis of Massive Data
Nov 13, 2012
Big Data Meets Social Media at Georgia Tech's Institute for People and Technology (iPaT)'s annual People & Technology Forum
Invited Panel Chair
Oct 31, 2023
Science in the Age of Generative AI, ORNL Core Universities AI Workshop 2023
Mar 21, 2015
Georgia Tech Business Analytics and Big Data Forum: Visual Analytics Session, with Rahul Basole
Apr 15, 2013
Center for Data Analytics workshop, Georgia Tech
Invited Participant
Jun 14-15, 2017
Pacific Northwest National Laboratory (PNNL) Faculty Summit
Theme: Machine Learning and Human Computer Interaction for Science and Security
Theme: Machine Learning and Human Computer Interaction for Science and Security
Feb 15, 2017
Forum on Synthetic Identity Fraud, National Academies of Sciences
Jul 13-14, 2016
Microsoft Faculty Summit
Aug 1-2, 2016
Google Faculty Institute
Jun 17-18, 2014
Pacific Northwest National Laboratory (PNNL) Analysis in Motion (AIM) Workshop
Grants & Funding
RI: Medium: Democratizing Visual AI: Enhancing Efficiency and Usability of Large Vision Models for Fostering Under-Resourced Access
NSF RI 2403297
PI: Judy Hoffman
Co-PIs: Duen Horng (Polo) Chau, Yingyan (Celine) Lin
Amount: $1.2 milion
Period: 10/1/2024 – 9/30/2028
NSF RI 2403297
PI: Judy Hoffman
Co-PIs: Duen Horng (Polo) Chau, Yingyan (Celine) Lin
Amount: $1.2 milion
Period: 10/1/2024 – 9/30/2028
NAIRR Pilot: VizFold: Visualizing & Interpretable Protein Folding in AlphaFold and Similar Protein Models
NSF EAGER 2502793
PI: Giri Prashanth Krishnan
Co-PIs: Duen Horng (Polo) Chau
Amount: $300,000
Period: 2/1/2025 – 1/31/2027
NSF EAGER 2502793
PI: Giri Prashanth Krishnan
Co-PIs: Duen Horng (Polo) Chau
Amount: $300,000
Period: 2/1/2025 – 1/31/2027
Object Sensing and Cognition for Adversarial Robustness
DARPA Guaranteeing AI Robustness Against Deception (GARD). Agreement number HR00112030001
Prime PI: Jason Martin (Intel)
Georgia Tech PI: Duen Horng (Polo) Chau
Georgia Tech amount: $1.3 million
Period: 1/28/2020 – 2/29/2024
News Release
DARPA Guaranteeing AI Robustness Against Deception (GARD). Agreement number HR00112030001
Prime PI: Jason Martin (Intel)
Georgia Tech PI: Duen Horng (Polo) Chau
Georgia Tech amount: $1.3 million
Period: 1/28/2020 – 2/29/2024
News Release
Research Initiation: Developing Technical Identity of Construction Engineering Students with Mixed Reality
NSF 2306226
PI: Omobolanle Ogunseiju
Co-PI: Duen Horng (Polo) Chau
Amount: $199,997
Period: 8/1/2023 – 7/31/2025
NSF 2306226
PI: Omobolanle Ogunseiju
Co-PI: Duen Horng (Polo) Chau
Amount: $199,997
Period: 8/1/2023 – 7/31/2025
Collaborative Research: IRES Track I: Artificial Intelligence and Human Designer - Research Experience in Singapore (AIHD Singapore)
NSF 2246298
PI: Baabak Ashuri
Co-PI: Duen Horng (Polo) Chau
Amount: $150,000
Period: 9/1/2023 – 8/26/2026
NSF 2246298
PI: Baabak Ashuri
Co-PI: Duen Horng (Polo) Chau
Amount: $150,000
Period: 9/1/2023 – 8/26/2026
Updating the GDOT’s Risk-based Programmed Contingencies Through Development of a Data-Driven Decision Tree Model
Georgia Department of Transportation (GDOT)
PI: Baabak Ashuri
Co-PI: Duen Horng (Polo) Chau
Amount: $300,000
Period: 1/31/2024 – 5/1/2026
Georgia Department of Transportation (GDOT)
PI: Baabak Ashuri
Co-PI: Duen Horng (Polo) Chau
Amount: $300,000
Period: 1/31/2024 – 5/1/2026
SitS NSF-UKRI: Rapid Deployment of Multi-Functional Modular Sensing Systems in the Soil
NSF 1935548
PI: Chloé Arson
Co-PIs: David Frost, Daniel Goldman, Duen Horng (Polo) Chau, Frank Hammond
Amount: $1.7 million (with Imperial College London via UK Research and Innovation); Georgia Tech amount: $800,000
Period: 9/1/2019 – 8/31/2024
News Release
NSF 1935548
PI: Chloé Arson
Co-PIs: David Frost, Daniel Goldman, Duen Horng (Polo) Chau, Frank Hammond
Amount: $1.7 million (with Imperial College London via UK Research and Innovation); Georgia Tech amount: $800,000
Period: 9/1/2019 – 8/31/2024
News Release
SPARC-X: Quantum simulations at extreme scale - reactive dynamics from first principles
DE-SC0019410
PI: Phanish Suryanarayana
Co-PI: Andrew J. Medford, Edmond Chow, John E. Pask (Lawrence Livermore National Laboratory)
Senior Personnel: Duen Horng (Polo) Chau
Amount: $2.8 million
Period: 09/15/2018 - 09/14/2024
News release
DE-SC0019410
PI: Phanish Suryanarayana
Co-PI: Andrew J. Medford, Edmond Chow, John E. Pask (Lawrence Livermore National Laboratory)
Senior Personnel: Duen Horng (Polo) Chau
Amount: $2.8 million
Period: 09/15/2018 - 09/14/2024
News release
ADP-GT Research
ADP
PI: Polo Chau
Co-PIs: Chao Zhang, Srijan Kumar
Amount: $250,000
Period: 10/5/2022 – 12/31/2023
ADP
PI: Polo Chau
Co-PIs: Chao Zhang, Srijan Kumar
Amount: $250,000
Period: 10/5/2022 – 12/31/2023
Interactive Scalable Interpretable Monitoring of AI Training
Cisco Systems
PI: Polo Chau
Amount: $150,000
Period: 10/3/2022 – 12/2/2023
Cisco Systems
PI: Polo Chau
Amount: $150,000
Period: 10/3/2022 – 12/2/2023
Interactive Scalable Auditing of AI Biases with Interpretable Mitigation
Cisco Systems
PI: Judy Hoffman
Co-PI: Duen Horng (Polo) Chau
Amount: $307,514
Period: 10/1/2020 – 8/31/2022
Cisco Systems
PI: Judy Hoffman
Co-PI: Duen Horng (Polo) Chau
Amount: $307,514
Period: 10/1/2020 – 8/31/2022
Analyzing and using large pretrained language models for societal good
Microsoft
PI: Munmun De Choudhury
Co-PI: Alan Ritter, Diyi Yang, Polo Chau
Amount: $300k Microsoft Azure credit
Period: 2/1/2021 – 6/1/2021
Microsoft
PI: Munmun De Choudhury
Co-PI: Alan Ritter, Diyi Yang, Polo Chau
Amount: $300k Microsoft Azure credit
Period: 2/1/2021 – 6/1/2021
SaTC: CORE: Medium: Understanding and Fortifying Machine Learning Based Security Analytics
NSF CNS 1704701
PI: Polo Chau
Co-PIs: Taesoo Kim, Wenke Lee, Le Song
Amount: $1.2 milion
Period: 8/1/2017 – 7/31/2021
NSF CNS 1704701
PI: Polo Chau
Co-PIs: Taesoo Kim, Wenke Lee, Le Song
Amount: $1.2 milion
Period: 8/1/2017 – 7/31/2021
Understanding Deep Neural Networks Through Attribution and Interactive Experimentation
NASA
PI: Polo Chau
Amount: $235,000
Period: 8/1/2018 - 12/31/2020
NASA
PI: Polo Chau
Amount: $235,000
Period: 8/1/2018 - 12/31/2020
III: Medium: Collaborative Research: Human-computer Graph Exploration and Tele-discovery
NSF IIS 1563816 (& 1563971)
PIs: Polo Chau, James Abello
Amount: $1.2 million
Period: 8/1/2016 – 7/31/2020
NSF IIS 1563816 (& 1563971)
PIs: Polo Chau, James Abello
Amount: $1.2 million
Period: 8/1/2016 – 7/31/2020
Intel Science & Technology Center for Adversary-Resilient Security Analytics (ISTC-ARSA)
Intel
PI: Wenke Lee
Co-PIs: Polo Chau, Taesoo Kim, Le Song
Gift: $1.5 million
7/27/2016 – 6/30/2019
Intel
PI: Wenke Lee
Co-PIs: Polo Chau, Taesoo Kim, Le Song
Gift: $1.5 million
7/27/2016 – 6/30/2019
Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K)
National Institute of Health (NIH: 1-U54EB020404-01)
Amount: $10.8 million (Prime: Univ. of Memphis); Georgia Tech amount: $1,250,035
PI: Jim Rehg
Co-PIs: Gregory Abowd, Polo Chau
Period: 9/29/2014 – 09/30/2018
National Institute of Health (NIH: 1-U54EB020404-01)
Amount: $10.8 million (Prime: Univ. of Memphis); Georgia Tech amount: $1,250,035
PI: Jim Rehg
Co-PIs: Gregory Abowd, Polo Chau
Period: 9/29/2014 – 09/30/2018
TWC: Small: Collaborative: Cracking Down Online Deception Ecosystems
NSF TWC 1526254
PIs: Bogdan Carbunar, Duen Horng (Polo) Chau
Amount: $499,413
Period: 9/1/2015 – 8/31/2018
NSF TWC 1526254
PIs: Bogdan Carbunar, Duen Horng (Polo) Chau
Amount: $499,413
Period: 9/1/2015 – 8/31/2018
EAGER: Scaling up Machine Learning with Virtual Memory
NSF IIS 1551614
PIs: Polo Chau, Rich Vuduc
Amount: $184,904
Period: 10/1/2015 – 9/30/2017
NSF IIS 1551614
PIs: Polo Chau, Rich Vuduc
Amount: $184,904
Period: 10/1/2015 – 9/30/2017
Scalable Architecture for Anomaly Visualization in Power Generating Assets
Strategic Energy Institute (SEI), Georgia Tech
PI: Polo Chau
Amount: $52,344
Period: 1/1/2016 - 12/31/2017
Strategic Energy Institute (SEI), Georgia Tech
PI: Polo Chau
Amount: $52,344
Period: 1/1/2016 - 12/31/2017
Data Science Platform for Strategic Industry Partnerships, Innovations, & Talent Development
Institute for Data Engineering and Science (IDEaS), Georgia Tech
PI: Polo Chau
Co-PIs: Le Song, Hongyuan Zha, Sridhar Narasimhan, Jeffrey Hu, John Stasko, Cherry Liu
Amount: $75,000
Period: 1/1/2016 - 6/30/2016
Institute for Data Engineering and Science (IDEaS), Georgia Tech
PI: Polo Chau
Co-PIs: Le Song, Hongyuan Zha, Sridhar Narasimhan, Jeffrey Hu, John Stasko, Cherry Liu
Amount: $75,000
Period: 1/1/2016 - 6/30/2016
CGV: Small: Making Sense out of Large Graphs - Bridging HCI with Data Mining
NSF IIS-1217559
PI: Christos Faloutsos
Co-PI Duen Horng Chau, Aniket Kittur
Amount: $528,578.00
Period: 8/25/2012 - 8/31/2015
NSF IIS-1217559
PI: Christos Faloutsos
Co-PI Duen Horng Chau, Aniket Kittur
Amount: $528,578.00
Period: 8/25/2012 - 8/31/2015
Identifying Risks to Psychological Distress in University Student Populations from Online Interaction Data
James Edenfield Faculty Fellowship, with Munmun De Choudhury (IC). One graduate student support for one academic year, co-advised by two College of Computing faculty.
Amount: ~$25k
Period: Fall 2015 - Spring 2016
James Edenfield Faculty Fellowship, with Munmun De Choudhury (IC). One graduate student support for one academic year, co-advised by two College of Computing faculty.
Amount: ~$25k
Period: Fall 2015 - Spring 2016
Illuminating Paths to Success: Mining Common Sequences of Courses
Georgia Tech Professional Education
PI: Polo Chau
Amount: $18,625
Period: 5/11/2015 - 8/1/2015
Georgia Tech Professional Education
PI: Polo Chau
Amount: $18,625
Period: 5/11/2015 - 8/1/2015
Data-Driven Decision-Making via Visual Analytics on the Microsoft Surface Hub
Microsoft
PI: John Stasko
Co-PIs: Rahul Basole, Alex Endert, Polo Chau
Amount: $25,000 and received an 84-inch Surface Hub.
Microsoft
PI: John Stasko
Co-PIs: Rahul Basole, Alex Endert, Polo Chau
Amount: $25,000 and received an 84-inch Surface Hub.
Reimagining Humanities Visualization: A Research-Through-Design Workshop for Civic and Cultural Data
GVU research and engagement grant
PI: Lauren Klein
Co-PIs: Rahul Basole, Polo Chau, Carl DiSalvo, Alex Endert, Jim Foley, Nassim JafariNaimi, Yanni Loukissas, John Stasko, Jimeng Sun
GVU research and engagement grant
PI: Lauren Klein
Co-PIs: Rahul Basole, Polo Chau, Carl DiSalvo, Alex Endert, Jim Foley, Nassim JafariNaimi, Yanni Loukissas, John Stasko, Jimeng Sun
Discovery, Analysis, & Visualization of Pediatric Asthma Careflow
Children's Healthcare of Atlanta
PI: Rahul Basole
Co-PIs: Mark Braunstein, Nicoleta Serban, Duen Horng Chau Amount: $202,867
Period: 9/1/2014 – 8/31/2015
Children's Healthcare of Atlanta
PI: Rahul Basole
Co-PIs: Mark Braunstein, Nicoleta Serban, Duen Horng Chau Amount: $202,867
Period: 9/1/2014 – 8/31/2015
Proactive Detection of Insider Threats with Graph Analysis at Multiple Scales
PIs: T. Senator (SAIC) and D.A. Bader (GTRI)
Defense Advanced Research Projects Agency
Anomaly Detection at Multiple Scales (ADAMS) Program
Amount: $2,927,976 (GT portion)
Period: 5/1/2011 - 4/30/2013
PIs: T. Senator (SAIC) and D.A. Bader (GTRI)
Defense Advanced Research Projects Agency
Anomaly Detection at Multiple Scales (ADAMS) Program
Amount: $2,927,976 (GT portion)
Period: 5/1/2011 - 4/30/2013
Discovery, Analysis, and Visualization of Pediatric Careflow Processes
Raytheon Faculty Fellowship, with Rahul Basole (IC). One graduate student support for one academic year, co-advised by two College of Computing faculty. Amount: ~$25k
Period: Fall 2014 - Spring 2015
Raytheon Faculty Fellowship, with Rahul Basole (IC). One graduate student support for one academic year, co-advised by two College of Computing faculty. Amount: ~$25k
Period: Fall 2014 - Spring 2015
Gift
Avast Software. $100,000. Aug, 2021.
Fiddler Labs. $80,000. Aug, 2021.
Bosch. $37,000. Jan, 2021.
NVIDIA. DGX A100 640GB (~$200,000) + $79,000. Nov, 2020.
NVIDIA. Donation of a Titan V GPU. 2018.
Google Faculty Research Award. 2015. $52,000.
200 server donation from Yahoo Labs, as part of Yahoo Servers to Academic Researchers program (Y-STAR). Thanks Seth Tropper!
Intel. Spring 2015. $40,000. Support for big data curriculum.
LogicBlox. Fall 2013 - Spring 2014: $12,500.
Symantec. Summer 2013: $10,000. April 2014: $26,000. Spring 2015: $40,000.
eBay. Summer 2014: $15,000.
Yahoo Faculty Research Engagement (FREP) award. 2014 - 2015: $10,000.
Yahoo sponsoring student seminars and distinguished lectures. 2014 - 2015: $13,500.
Georgia Tech Wearable Computing Center Mentorship Grant. $1000, Fall 2014. Advising undergraduate students Samuel Clarke and Nathan Dass
MS&T
Faculty Materials, Supplies and Travel Grants for Undergraduate Research, advising Mr. Dezhi (Andy) Fang and Nathan Dass. Awarded: $1000, summer 2017
Faculty Materials, Supplies and Travel Grants for Undergraduate Research, advising Mr. Yiqi (Victor) Chen. Awarded: $800, summer 2014
Faculty Materials, Supplies and Travel Grants for Undergraduate Research, advising Mr. Zhiyuan (Jerry) Lin. Awarded: $1000, summer 2013
Fellowship
Research proposals led to two full years of research funding from Symantec. Awarded:$140,000.
Co-author
$35 million DARPA proposal on Anomaly Detection at Multiple Scales (ADAMS). CMU funded ~$500,000. Co-authored the winning proposal, represented CMU and led research efforts.
Education Grant
Microsoft Azure Grant
2016 - 2017
$20,000 for CSE 6242 / CX 4242 Data and Visual Analytics
Amazon Web Services (AWS) Machine Learning Grant
Fall 18
$5000 credits for distributed machine learning research
Spring 15
$2500 credits for distributed machine learning research
Amazon Web Services (AWS) Teaching Grant
Spring 2015
$12000 credits for CSE 6242 / CX 4242 Data and Visual Analytics
Fall 2014
$14000 credits for CSE 6242 / CX 4242 Data and Visual Analytics
Spring 2014
$10000 credits for CSE 6242 / CX 4242 Data and Visual Analytics
Spring 2013
$4000 credits to CSE 6242 A / CS 4803 DVA Data and Visual Analytics
Unfunded
Helped in creating an NEC proposal for University Awards from NEC Labs Data Management. $75,000
Professional Activities
Program Co-chair
ACM Intelligent User Interfaces Conference (IUI) 2019
USENIX Security and AI Networking Conference (ScAINet) 2019
General Co-Chair
Workshop Co-Chair
VIS workshop on Visualization for AI Explainability (VISXAI) 2018, 2019, 2020
KDD workshop on Interactive Data Exploration and Analytics (IDEA): 2013, 2014, 2015, 2016, 2017, 2018
ICML workshop on Visualization for Deep Learning: 2016, 2017
Co-Organizer
Dagstuhl Seminar on Interactive Visualization for Fostering Trust in ML. Organizers: Daniela Oelke, Alex Endert, Daniel A. Keim, Polo Chau. Aug 28 – Sept 2, 2022.
Steering Committee
IEEE VIS workshop on Visualization for AI Explainability (VISxAI). 2021, 2022.
ACM Intelligent User Interfaces (IUI) Conference. Since 2016.
ICLR 2021 workshop on Beyond static papers: Rethinking how we share scientific understanding in ML
Associate Editor
IEEE Transactions on Visualization and Computer Graphics (TVCG). 2020 - 2022.
ACM Transactions on Interactive Intelligent Systems (TIIS). 2020 - 2021.
Publicity Chair
Advisory Board
Journal Co-editor
ACM TKDD Special Issue on Interactive Data Exploration and Analytics (IDEA), 2015
NSF Review Panelist
Information and Intelligent Systems (IIS) Division. 2014, 2015, 2016, 2018, 2019
Secure and Trustworthy Cyberspace (SaTC). 2018
(CISE) Research Initiation Initiative (CRII). 2016.
Conf Area Chair
ECML-PKDD 2020 (Research Track), 2022, 2023
Session Chair
VIS 2020
SDM 2017: Classification
KDD 2015: Social Good
KDD 2014: Scaling-up Graph Algorithms
Conf Associate Chair
Conf Senior Program Committee
PKDD 2020-22
SIAM SDM 2019-23
ACM IUI 2019-21
Conf Program Committee
IEEE VIS 2018-2023
KDD 2013-2020
SDM 2014-2020 (SIAM International Conference on Data Mining)
ICDCS 2017
WSDM 2015, WSDM 2016
ACM IUI 2016
ECML/PKDD 2013-2019
ASONAM 2015
SC14 (SuperComputing 2014) - Data Analytics, Visualization and Storage
Workshop Program Committee
KDD 2019 Workshop on
Learning and Mining for Cybersecurity (LEMINCS)
IEEE VIS 2017 Workshop on Visualization in Data Science (VDS)
WWW 2015 Workshop on
Diffusion, Activity and Events in Networks: Models, Methods & Applications
WWW 2015 Workshop on
Modeling Social Media - Behavioral Analytics in Social Media, Big Data and the Web
IEEE International Conference on Data Mining (ICDM 2014) workshop on Scalable Machine Learning: Theory and Applications
IEEE International Conference on Big Data (IEEE BigData 2014) workshop on Scalable Machine Learning: Theory and Applications
ICDM workshop on Scalable Data Analytics: Theory and Applications
WWW 2014 workshop on Mining Big Data in Social Media and the Web (MSM)
ACM SAC 2014 (Symposium On Applied Computing)
KDD 2013 workshop on Outlier Detection and Description (ODD)
KDD 2014 workshop on Outlier Detection & Description under Data Diversity (ODD^2)
ICDM 2012 (Demo Session)
ECML PKDD 2012 Workshop on Instant Interactive Data Mining
NIPS 2011 workshop on parallel and large-scale machine learning (Big Learning)
CSCW 2012 workshop on Personal Information Management (PIM)
ASIST 2009 workshop on Personal Information Management (PIM)
Symposium Org.
The First Student Research Symposium. CMU/Machine Learning Department. 2009.
Journal Reviewer
TOCHI, 2015
IEEE’s Transactions on Knowledge and Data Engineering (TKDE), 2014
ACM Computing Surveys, 2014
Statistical Analysis and Data Mining journal Special Issue of "Best of SDM 2014"
International Journal on Human-Computer Interaction (2014)
Data & Knowledge Engineering (DKE) Journal (2013)
IEEE Journal of Biomedical and Health Informatics (2013)
Software: Practice and Experience (2013)
IEEE Intelligent Systems (2012)
Parallel Computing (2011)
IBM Systems Journal (2007)
Conference Reviewer
SDM 2014-17
KDD 2013-17
ECML/PKDD 2008-09, 2013, 2015-17
ICDM 2012
WSDM 2015-16
WWW 2008-10
IEEE BigData 2014
IEEE Vis 2017
CHI 2007-16
UIST 2007-10, 2014
IUI 2012-16
AVI 2014
SuperComputing (SC) 2014
NIPS 2013
VLDB 2008-09
HICSS 2013
International Cross Domain Conference and Workshop (CD-ARES 2013)
Seminar Organizer
Machine Learning Lunch Seminar. CMU/Machine Learning Department. 2008-2011.
CSE Seminar Co-organizer. GT/CSE. 2012–2013 AY.
Member
Association for Computing Machinery (ACM). Since 2006.
The Institute of Electrical and Electronics Engineers (IEEE). Since 2006.
HCIC (Human Computer Interaction Consortium)
Machine Learning Department (CMU) website committee
Services At Georgia Tech
Institute
Georgia Tech Vice President for Commercialization & Chief Commercialization Officer (CCO) Search Committee, 2021.
Georgia Tech's Strategic Planning Steering Committee, Oct 2019 - May 2020.
Director of Industry Relations, The Institute for Data Engineering and Science. Since Oct 2019.
Associate Director of Corporate Relations, The Center for Machine Learning. Since Oct 2019.
Provost learning and teaching fellow. 2018-2022 AY
Associate Director, Masters of Science in Analytics. Since 8/2014.
Machine Learning Faculty Advisory Committee. May 2017 - Aug 2021.
Academic Faculty Senate Representative for CSE, 2015-2018 AY
Institute for Information Security & Privacy (IISP) faculty council member. Since 6/2015
Strategic Energy Institute (SEI) Faculty Advisory Council (FAC) member. July 2018 - Oct 2021.
Strategic Energy Institute (SEI) faculty member
Institute for Data Engineering and Science (IDEaS) faculty member
Center for Machine Learning (ML@GT) faculty member
College of Computing
Faculty Advisory Board for Communications. 2022- AY.
Machine Learning Area Leader. 2018-2021 AY.
Advisory board member of GT DataWorks, a new data literacy program to broaden participating in data science. Sep 2019 - Dec 2020.
CSE
Chair, Faculty Recruiting Committee, 2023- AY
School Web Committee (Co-Chair with Bryant Wine), 2022-2023 AY
School Web Committee (Co-Chair with Kristen Perez), 2020–2021 AY
School Honors Committee, 2019–2020 AY, 2020–2021 AY, 2021–2022 AY
School Reappointment, Promotion, and/or Tenure (RPT) Committee, since 2018–2019 AY
School Advisory Committee (SAC), 2013-2014 AY, 2014-2015 AY, 2015–2016 AY, 2016–2017 AY
Graduate Admissions Committee (CS, CSE programs), 2012–2013, 2013–2014 AY (Chair of CSE), 2015–2016 AY, 2017–2018 AY, 2018–2019 AY
PhD Recruiting Committee (Chair of CSE), 2012–2013 AY, 2013–2014 AY
CSE Chair Search Committee Member, 2012–2013 AY, 2019-2020 AY
CSE Seminar Co-organizer, 2012–2013 AY
Space Planning Committee, 2012–2013 AY
Created State of CSE info graphics
IC + CSE
Visual Analytics area coordinator (with Alex Endert of IC), MS CS, 2014-2017
Student Club
Faculty advisor, Data Science @ Georgia Tech (DSGT), a data science club for Georiga Tech students.
PhD Thesis
Xiao Jing. GT/CSE-AE. Adv: Dimitri Mavris. Proposal: MM/DD/YY. Defense: MM/DD/YY.
Michael Herman. GT/AE. Adv: Dimitri Mavris. Defense: 12/12/24.
Yonggan Fu. GT/CS. Adv: Yingyan (Celine) Lin. Proposal: 08/14/24. Defense: MM/DD/YY.
Ruijia Wang, GT/CSE-CEE. Advs: David Frost, Mahdi Roozbahani. Proposal: 10/25/24. Defense: MM/DD/YY.
Qinghao Zeng. GT/College of Design. Adv: Pardis Pishdad. Proposal: 10/03/24. Defense: MM/DD/YY.
Adam Coscia. GT/HCC. Adv: Alex Endert. Proposal: 08/22/24. Defense: MM/DD/YY.
Gaurav Verma. GT/CS. Adv: Srijan Kumar. Proposal: 05/02/24. Defense: MM/DD/YY.
Mingshu Li. GT/CEE Adv: Baabak Ashuri. Proposal: 03/29/24. Defense: MM/DD/YY.
Wenxin Zhang. GT/AE. Adv: Dimitri Mavris. Proposal: 04/01/24. Defense: MM/DD/YY.
Jacob Logas. GT/Computer Interaction. Adv: Rosa Arriaga, Sauvik Das. Proposal: 12/01/23. Defense: MM/DD/YY.
Kaan Sancak. GT/CSE. Adv: Umit Ümit V. Çatalyürek. Proposal: 11/21/23. Defense: MM/DD/YY.
Zoe Klesmith. GT/CSE-MechE. Adv: Christopher Saldana. Proposal: 12/11/23. Defense: 12/22/24.
Yue Yu. GT/CSE. Adv: Chao Zhang. Proposal: 12/03/23. Defense: MM/DD/YY.
Dongjin Choi. GT/CSE. Adv: Haesun Park. Proposal: 11/10/23. Defense: MM/DD/YY.
Hyungu Choi, GT/CSE-AE. Adv: Dimitri Mavris. Proposal: 06/27/23.
Qinghai Zhou. UIUC. Adv: Hanghang Tong. Proposal: 05/02/23. Defense: 08/28/23.
Irfan Al-Hussaini, GT/ECE. Adv: Cassie Mitchell. Co-Adv: Justin Romberg. Defense: 06/27/23.
Arpit Narechania, GT/CS. Adv: Alex Endert. Proposal: 12/07/22.
Danrong Zhang, GT/CSE-CEE. Adv: David Frost. Proposal: 12/01/22. Defense: 10/31/24.
Caleb Harris. GT/CSE-AE. Adv: Dimitri Mavris. Proposal: 12/09/21. Defense: 09/23/22.
Rodrigo Borela. GT/CSE-CEE. Adv: David Frost. Defense: 11/29/21.
Sooji (Susie) Ha. GT/CSE-CEE. Adv: Emily Grubert, Omar Asensio. Proposal: 01/19/2021.
Shahrokh (Shah) Shahi. GT/CSE. Adv: Elizabeth Cherry. Proposal: 12/16/20. Defnese: 07/22/22.
Luis Fernando Patino Ramirez. GT/CEE. Adv: Chloé Arson. Defense: 10/29/20.
Majid Ahadi Dolatsara. GT/ECE. Adv: Madhavan Swaminathan. Defense: 01/27/21.
Aroua Gharbi. GT/AE. Adv: Dimitri Mavris. Proposal: 12/15/20. Defense: 04/14/22.
Rodrigo Borela Valente. GT/CSE-CEE. Adv: David Frost. Defense: 11/29/2021
Junghyun (Andy) Kim. GT/CSE-AE. Adv: Dimitri Mavris. Proposal: 04/06/20. Defense: 03/29/21.
Hanjun Dai. GT/CSE. Adv: Le Song. Proposal: 7/10/19. Defense: 12/3/19.
Po Ming (Terrance) Law. GT/CS. Adv: Alex Endert, John Stasko. Proposal: 05/04/20. Defense: 04/10/21.
Karl Gemayel. GT/CSE. Adv: Mark Borodovsky. Proposal: 12/27/19. Defense: 10/26/20.
Weiyang Liu. GT/CSE. Adv: Le Song. Proposal: 10/11/19. Defense: 07/15/20.
Rakshit Trivedi. GT/CSE. Adv: Rakshit Trivedi. Proposal: 10/3/19. Defense: 06/25/20.
Yuzhi Guo. GT/CSE. Adv: David Frost. Proposal: 12/26/19. Defense: 05/07/20.
Julia Deeb-Swihart. GT/CS. Adv: Amy Bruckman, Alex Endert. Proposal: 10/30/19. Defense: 05/26/22.
Amrita Gupta. GT/CSE. Adv: Bistra Dilkina. Proposal: 12/17/19. Defense: 01/05/2021.
Hang Wu. GT/ML. Adv: May Wang. Proposal: 12/12/19.
Xiangyun (Ray) Lei. GT/Chem Eng . Adv: AJ Meford. Proposal: 11/30/18. Defense: 06/28/21.
Xinghua Gao. GT/College of Design . Adv: Pardis Pishdad. Proposal: 04/30/18. Defense: 03/27/19.
Hanna Kim. GT/CSE. Adv: Haesun Park. Proposal: 8/27/19. Defense: 11/18/20.
Payam Siyari. GT/CS. Adv: Konstantinos Dovrolis. Proposal: 4/25/18. Defense: 10/17/18.
Leilei Xiong. GT/ECE. Adv: Santiago Grijalva. Defense: 12/14/18.
Xiaochen Zhang. GT/ECE. Adv: Santiago Grijalva. Defense: 7/24/17.
Ahmet Cecen. GT/CSE. Adv: Surya Kalidindi. Proposal: 2/1/17. Defense: 7/20/17
Mengmeng (Helen) Liu. GT/CSE. Adv: David Frost. Proposal: 4/18/17. Defense: 8/14/17.
Young Jin Kim. GT/CSE. Adv: Dimitri Mavris. Co-adv: Richard Fujimoto. Proposal: 2/9/17. Defense: 7/28/17.
Youngchul Park. GT/CSE. Adv: Dimitri Mavris. Proposal: 11/18/16.
Hillol Sarker. Univ. of Memphis/CS. Adv: Santosh Kumar. Proposal: 4/8/16. Defense: 11/4/16.
James Fairbanks. GT/CSE. Adv: David Bader. Defense: 3/28/16.
Kunal Malhotra. GT/CS. Adv: Sham Navathe. Co-adv: Jimeng Sun. Proposal: 12/8/15. Defense: 11/7/16.
Ramakrishnan (Ramki) Kannan. GT/CS. Adv: Haesun Park. Proposal: 5/5/15. Defense: 2/22/16.
Joonseok Lee. GT/CSE. Adv: Guy Lebanon, Hongyuan Zha. Defense: 2/19/15.
Long Tran. GT/CSE. Adv: Hongyuan Zha, Alex Gray. Proposal: 9/10/14. Defense: 1/6/15, GT/CSE
Saeideh Bakhshi, GT/IC. Adv: Eric Gilbert. Defense: 7/1/14
Da Kuang, GT/CSE. Adv: Haesun Park. Defense: 6/12/14
Albert Brzeczko, GT/ECE. Adv: John Copeland. Defense: 4/2/14
Liangda Li, GT/CSE. Adv: Hongyuan Zha. Proposal: 4/9/2014. Defense: 4/22/15
Mengdie Hu. GT/IC. Adv: John Stasko. Proposal: 12/11/13. Defense: 4/5/17
Zhaoming Yin. GT/CSE. Adv: David Bader. Proposal: 4/26/2013.
Oded Green. GT/CSE. Adv: David Bader. Proposal: 3/26/2013. Defense: 3/14/2014.
Ke Zhou. GT/CSE. Adv: Hongyuan Zha. Proposal: 1/24/2013. Defense: 8/6/13
Soumitry Ray. GT/Civil Eng. Adv: Jochen Teizer. Proposal: 11/21/2012. Defense: 3/24/2014
PhD Qualifying Exam
Sonakshi Gupta. GT/CSE-MSE. Adv: Rampi Ramprasad. Spring 2025.
Honglai (Matthew) Peng. GT/CSE. Advs: David Frost, Rodrigo Borela. 11/05/24
Yingchen (Eric) Ma. GT/CS. Adv: Srijan Kumar. MM/DD/YY
Rijul Magu. GT/CS. Advs: Amy Bruckman, Diyi Yang. 04/26/24
Mohit Chandra. GT/CS. Adv: Munmun De Choudhury. 04/15/24
Xin He. GT/CSE-CE. Advs: Armistead Russell, Jennifer Kaiser. 04/26/24
Anthony Peng. GT/CS. Adv: Polo Chau. 12/06/23
Ben Hoover, GT/ML-CSE. Adv: Polo Chau. 04/11/23
Seongmin Lee, GT/CS-CSE. Adv: Polo Chau. 04/17/23
Michael Buzzy, GT/CSE-ME. Adv: Surya Kalidindi. 04/27/23
Grayson Harrington, GT/CSE-ME. Adv: Surya Kalidindi. 04/26/23
Zoe Klesmith, GT/CSE-ME. Adv: Christopher Saldana. 12/13/22
Johnie Sublett. GT/CSE-AE. Adv: Dimitri Mavris. 06/24/22
Yu Fu. GT/HCC. Adv: John Stasko. 04/15/22
Adam Coscia. GT/HCC. Adv: Alex Endert. 04/11/22
Takahiro Furuya, GT/CSE-CEE. Adv: Aris P. Georgakakos. 12/10/21
Ruijia Wang, GT/CSE-CEE. Adv: David Frost. 12/06/21
Fernando Vasconcelos Da Senhora. GT/CSE-CSS. Adv: Glaucio Paulino. 11/19/21
Danrong Zhang, GT/CSE-CEE. Adv: David Frost. 11/12/21
Arpit Ajay Narechania. GT/IC. Adv: Alex Endert. 05/16/21
Austin Wright. GT/ML. Adv: Polo Chau. 04/21/21
Zijie (Jay) Wang. GT/ML. Adv: Polo Chau. 04/21/21
Caleb Harris. GT/CSE-AE. Adv: Dimitri Mavris. 04/05/21
Shenyu Xu. GT/IC. Adv: Alex Endert. 04/19/22
Yue Yu. GT/CSE. Adv: Chao Zhang. 12/08/20
Arpit Ajay Narechania. GT/IC. Adv: Alex Endert
Yuqin Yang. GT/ML. Adv: Negar Kiyavash. 11/06/20
Hayeong Song. GT/IC. Adv: John Stasko. 04/20/20
Dongjin Choi. GT/CSE. Adv: Haesun Park. 04/22/20
James Pagan. GT/CSE. Adv: Dimitri Mavris. 12/12/19
Rodrigo Borela. GT/CSE. Adv: David Frost. 11/06/2020
Ali Siahkoohi. GT/CSE. Adv: Felix Herrmann. 11/13/19
Junghyun (Andy) Kim. GT/CSE. Adv: Dimitri Mavris.12/12/19
Weiyang Liu. GT/CSE. Adv: Le Song. 10/11/19
Rakshit Trivedi. GT/CSE. Adv: Hongyuan Zha. 11/9/19
Xiaojing (Jing) An. GT/CSE. Adv: David Bader. 10/16/18
Sarmistha Dutta. GT/CS. Adv: Munmun De Choudhury. 4/13/18
Subhajit Das. GT/CS. Adv: Alex Endert. 4/8/19
Apaar Shanker. GT/CSE. Adv: Surya Kalidindi. 5/4/19
Po Ming (Terrance) Law. GT/CS. Adv: Rahul Basole. 3/31/19
Yuzhi Guo. GT/CSE. Adv: David Frost. 3/12/18
Srinivas Eswar. GT/CSE. Adv: Rich Vuduc, Haesun Park. 1/26/18
Hanjun Dai. GT/CSE. Adv: Le Song. 1/25/18
Harsh Shrivastava. GT/ML. Adv: Srinivas Aluru. 5/2/18
David Betancourt. GT/CSE. Adv: Rafi Muhanna. 11/12/19
Siddharth Biswal. GT/CSE. Adv: Jimeng Sun. 12/11/17
Sungtae An. GT/CSE. Adv: Jimeng Sun. 11/28/17
Robert Chen. GT/CSE. Adv: Jimeng Sun. 3/15/17
Amrita Gupta. GT/CSE. Adv: Bistra Dilkina. 11/30/16
Caleb Robinson. GT/CSE. Adv: Bistra Dilkina. 11/22/16
Hyunjee Jin. GT/CSE. Adv: Dimitri Mavris. 11/21/16
Fred Hohman. GT/CSE. Adv: Polo Chau. 11/17/16
Edward Choi. GT/CSE. Adv: Jimeng Sun. 11/9/16
Saman Yarmohammadi. GT/School of Building Construction. Adv: Baabak Ashuri. 12/16
Shang-Tse Chen. GT/CS. Adv: Polo Chau. 3/29/16
Sarah Karamanti. GT/CSE. Adv: Rich Vuduc. 12/3/15
Young Jin Kim. GT/CSE. Adv: Dimitri Mavris. 11/23/15
Youngchul Park. GT/CSE. Adv: Dimitri Mavris. 11/23/15
Bo Dai. GT/CSE. Adv: Le Song. 4/22/15
Minsuk (Brian) Kahng. GT/CS. Adv: Polo Chau. 4/29/15
Mehrdad Farajtabar. GT/CSE. Adv: Edmond Chow. 11/25/2014
Lluis Miquel Munguia. GT/CSE. Adv: David Bader. 11/8/13
James Fairbanks. GT/CSE. Adv: David Bader. 10/9/13.
Bo Xie. GT/CS. Adv: Haesun Park, Le Song. 11/5/14
Kunal Malhotra. GT/CS. Adv: Sham Navathe. 4/22/13
Ramakrishnan (Ramki) Kannan. GT/CSE. Adv: Haesun Park. 3/29/13
Chad Stolper. GT/IC. Adv: John Stasko. 3/27/13
Anita Zakrzewska. GT/CSE. Adv: David Bader. 12/6/12
Robert Pienta. GT/CSE. Adv: Richard Fujimoto. 10/5/12
Masters Thesis
Marc-Henri Bleu-Laine. GT/AE. Dimitri Mavris. Proposal: 04/12/21.
Aroua Gharbi. GT/CSE. Adv: Dimitri Mavris. Defense: 11/18/16
Kevin flansburg. GT/CS. Adv: Taesoo Kim. Defense: 11/23/15
Kaushik Patnaik. GT/CSE. Adv: Le Song
Adam Coulon. GT/CSE (Aerospace Eng). Scott Duncan (Chair), Dimitri Mavris. Proposal: 4/2/14. Defense: 11/10/14.
Misc
Mascot Task Force committee member. Carnegie Mellon University. 2006.
The Chinese University of Hong Kong 40th Anniversary Concert committee. 2004.
Patents
Inferring File and Website Reputations by Belief Propagation Leveraging Machine Reputation. Adam Wright (Symantec), Duen Horng Chau. U.S. Patent No. 8,341,745. 25 Dec. 2012.
Media Coverage
The Strange Physics That Gave Birth to AI. Quanta Magazine. April 30, 2025. Elise Cutts.
The AI industry is hot right now. 5 experts share 4 tips for finding a job in the sector. Business Insider. February 25, 2023. Rebecca Knight, Beatrice Nolan, and Lakshmi Varanasi.
What Zillow’s failed algorithm means for the future of data science. Fortune. February 01, 2022. Erick Sherman.
Why is This New Deep Learning Visualization Going Viral?. Georgia Tech. October 30, 2020.
Finally, A Site that Crops Headshots Instantly (Without Sharing Your Photos). Georgia Tech. September 17, 2020.
How Do Neural Networks Learn? episode of Two Minute Papers (102k+ view; 790k+ subsribers) featuring CNN Explainer. June 27, 2020.
Machine Learning Technique Helps Wearable Devices Get Better at Diagnosing Sleep Disorders and Quality. Georgia Tech. April 15, 2020.
Intel Joins Georgia Tech in DARPA Program to Mitigate Machine Learning Deception Attacks.
Cal Jeffrey.
TechSpot.
April 9, 2020.
Intel Joins Georgia Tech in DARPA Program to Mitigate Machine Learning Deception Attacks.
Barron's.
April 9, 2020.
Intel and Georgia Tech join DARPA program to thwart attacks against machine learning.
Kyt Dotson.
Silicon Angle.
April 9, 2020.
Intel Joins Georgia Tech in DARPA Program to Mitigate Machine Learning Deception Attacks.
Yahoo! Finance.
April 9, 2020.
The Critical Importance Of The Intel DARPA GARD AI Initiative: DARPA has defined a program called GARD, and both Intel and Georgia Tech have stepped up to help make us safe.
Datamation.
Rob Enderle.
April 10, 2020.
Intel takes the lead on DARPA effort to end machine-learning spoofing.
Jim Nash.
April 10, 2020.
DARPA is pouring millions into a new AI defense program. Here are the companies leading the charge.
Protocol.
Hayden Field.
April 9, 2020.
Intel involved in AI defence programme.
Fudzilla.
Nick Farrell.
April 10, 2020.
DARPA snags Intel to lead its machine learning security tech.
TechCrunch.
Zack Whittaker.
April 9, 2020.
Also see the Japanese Tech Crunch version.
Intel, Georgia Tech join multimillion-dollar DARPA project.
Seeking Alpha.
Brandy Betz.
April 9, 2020.
Intel Joins Georgia Tech in DARPA Program to Mitigate Machine Learning Deception Attacks.
Business Wire.
April 9, 2020.
Intel Joins Georgia Tech in DARPA Program to Mitigate Machine Learning Deception Attacks. Intel News Bytes. April 9, 2020
Georgia Tech and Intel Awarded Multimillion-Dollar Program to Defend Against Attacks on AI. Kristen Perez. Georgia Tech CSE. April 8, 2020
Virtual, augmented reality platforms emerge as computer science teaching tool. Lauren Barack. Education Dive. March 13, 2019
K–12 Teachers Use Virtual and Augmented Reality Platforms to Teach Coding. Eli Zimmerman. EdTech. Feb 28, 2019.
These Wearables Detect Health Issues Before They Happen.
Elizabeth Woyke. MIT Technology Review. 11/30/16.
Feature: Can your mobile phone make you healthier?. Kelly Servick. Science Magazine. 12/10/2015.
The Secret World of Stolen Smartphones, Where Business Is Booming. Matthew Shaer. Wired, 12/18/14.
LatentGesture: Active Mobile Device Authentication
- Personal Touch Signature Makes Mobile Devices More Secure. Georgia Tech Press Release. April 7, 2014. Jason Maderer.
- Forget fingerprints: Your phone could lock out thieves by learning your 'touch signature'. Digital Trends. April 9, 2014. Christian Brazil Bautista.
- Researchers teach smartphones to recognize your activity, lock out everyone else. Engadget. Apr 7, 2014. Billy Steele.
- LatentGesture learns your unique touch signature, keeps everyone else out. Android Authority. Apr 9, 2014. Elmer Montejo.
- LatentGesture Recognizes Touch for Added Security Display Central. Apr 18, 2014. Arthur Berman.
- Georgia Tech researchers want to kill the smartphone passcode with "touch signature." Atlanta Business Chronicle. Apr 9, 2014. Urvaksh Karkaria.
- LatentGesture learns a smartphone's owner by touch and can lock the phone if it's used by another. Pocket-lint. Apr 9, 2014. Luke Edwards.
- LatentGesture: A Promising Future For Smartphone Security. Information Security Buzz. Apr 8, 2014. David Bisson.
- New innovation could put an end to smartphone thefts forever Yahoo News. Apr 9, 2014. Brad Reed.
- LatentGesture to make mobile devices more secure. Digit. Apr 9, 2014. Silky Malhotra.
- LatentGesture Uses Your Screen Taps & Swipes To Provide Security. Crazy Engineers. Apr 8, 2014. Ankita Katdare.
- LatentGesture Makes Smartphones Recognize You By Touch. Engismo. April 10, 2014. Mansoora Mubashra.
- The LatentGesture App Works Behind the Scenes to Keep Phones Safe Trend Hunter Apr 9, 2014. Jamie Danielle Munro.
- Inkblots and gestures: Getting creative about security. GCN. May 27, 2014. Patrick Marshall.
- Tap And Swipe On Your Mobile, LatentGesture Will Identify You! RTT News. Apr 9, 2014.
Yahoo Faculty Research and Engagement Program (FREP) Award by Yahoo! Labs. (GT press releases 1 & 2)
"Fraudsters on Internet Auction Sites Often Leave Trail Leading to Crimes", Lee Gomes, The Wall Street Journal, December 6, 2006.
"Researchers: Software Can Nip eBay Fraud in The Bud", Bob Sullivan, MSNBC, December 8, 2006.
KQV Radio live interview, Host: Frank Gottlieb, December 10, 2006.
"Researchers Developing Anti-Fraud Tool", Joe Mandak, The Associated Press, December 11, 2006. Also appeared in over 100 newspapers around the world, including USA Today, Los Angeles Times, The Washington Post.
"CMU Develops Program To Online Auction Fraud", Keith Jones, KDKA-TV News, originally aired December 12, 2006.
BizRadio live interview, Host: Brent Clenton, December 13, 2006
"Online Auction Frauds Not As Clever As They Think, Researchers Say", Alpha Doggs, Network World, December 5, 2006.
Design Awards & Leadership
2006
2005
Design lead, HCI Masters capstone project. Client: Office of Naval Research.
2004
1999-2000
Art Director of school yearbook. Diocesan Boys' School (Hong Kong).
Art Installations
Butterflies
Installed at the Pittsburgh Children’s Museum on March 5, 2009
Team: Jesse Chorng, Joanna Ricou, Polo Chau
Installed at the Pittsburgh Children’s Museum on March 5, 2009
Team: Jesse Chorng, Joanna Ricou, Polo Chau
The Curator
Installed at the Pittsburgh Children's Museum on April 25, 2009
Team: Polo Chau François Chu, Sue Ann Hong, Patrick Gage Kelley
Installed at the Pittsburgh Children's Museum on April 25, 2009
Team: Polo Chau François Chu, Sue Ann Hong, Patrick Gage Kelley
Skills
HCI
- Contextual inquiry
- Think-aloud protocol
- Cognitive walkthrough
- Heuristic evaluation
- GOMS
- Persona
- Focus groups
- Rapid paper prototyping
Programming
- Java
- C++
- C
- SQL
- VB
- Assembly
- JavaScript
- ActionScript
- CSS
- PHP
- ASP
- XML
- HTML
Design
- Affinity Designer
- Photoshop
- Illustrator
- Premiere
- InDesign
- Flash
- Lightwave 3D
- 3D Studio MAX
Music
- Pianist (30+ years)
- Cellist (30+ years)
- High school string orchestra conductor
- Chamber music group member
- Choir member
Languages
- English
- Mandarin
- Cantonese (native)