Scalable. Interactive. Interpretable.
At Georgia Tech, we innovate scalable, interactive, and interpretable tools that amplify human's ability to understand and interact with billion-scale data and machine learning models. Our current research thrusts: human-centered AI (interpretable, fair, safe AI; adversarial ML); large graph visualization and mining; cybersecurity; and social good (health, energy).
Minsuk
CS PhD
Shang
CS PhD
Fred
CSE PhD
Nilaksh
CSE PhD
Haekyu
CS PhD
Scott
ML PhD
Anmol
MS CSE
Bob
CS Undergrad
Kristina
Analytics Master
Matthew
CS Master
Joon
CS Undergrad
Jonathan
CS Undergrad
Alex
CS Undergrad
Will
CS Undergrad
Omar
CS Undergrad
Sudeep
CS Undergrad
Polo
Associate Prof
See all Polo Club members and alum

Human-Centered AI

Interpretable, fair, and safe artificial intelligence, through interactive intelligent visualization, with application in adversarial machine learning (how protect AI from harm, and from doing harm).

Gamut: Understanding How Data Scientists Understand Machine Learning Models
Gamut
Understanding How Data Scientists Understand Machine Learning Models
Microsoft Research
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
Visual Analytics in Deep Learning
An Interrogative Survey for the Next Frontiers
ActiVis: Visual Exploration of Facebook Deep Neural Network Models
ActiVis
Visual Exploration of Facebook Deep Neural Network Models
Deployed
Facebook
GAN Lab: Playing with Generative Adversarial Networks in Browser
GAN Lab
Playing with Generative Adversarial Networks in Browser
Google
NeuralDivergence: Exploring and Understanding Neural Networks by Comparing Activation Distributions
NeuralDivergence
Exploring and Understanding Neural Networks by Comparing Activation Distributions
Discovering Intersectional Bias: Discovery of Intersectional Bias in Machine Learning Using Automatic Subgroup Generation
Discovering Intersectional Bias
Discovery of Intersectional Bias in Machine Learning Using Automatic Subgroup Generation
SHIELD: Fast, practical defense for deep learning
SHIELD
Fast, practical defense for deep learning
Audience Appreciation Award, Runner-up
Intel
ShapeShifter: 1st Targeted Physical Attack on Faster R-CNN Object Detector
ShapeShifter
1st Targeted Physical Attack on Faster R-CNN Object Detector
Intel
ShapeShop: Understanding Deep Learning Representations via Interactive Experimentation
ShapeShop
Understanding Deep Learning Representations via Interactive Experimentation
PNNL
The Beginner's Guide to Dimensionality Reduction: Explore the methods that data scientists use to visualize high-dimensional data
The Beginner's Guide to Dimensionality Reduction
Explore the methods that data scientists use to visualize high-dimensional data
Best Paper, Honorable Mention
Protect AI with JPEG: Simple, powerful defense for deep learning
Protect AI with JPEG
Simple, powerful defense for deep learning
Intel
Interactive Classification: For Deep Learning Interpretation
Interactive Classification
For Deep Learning Interpretation
ADAGIO: Interactive experimentation with adversarial attack and defense for audio
ADAGIO
Interactive experimentation with adversarial attack and defense for audio
Intel
ML Cube: Visual Exploration of Machine Learning Results Using Data Cube Analysis
ML Cube
Visual Exploration of Machine Learning Results Using Data Cube Analysis
Facebook
Mixed Reality: MR for Learning Programming
Mixed Reality
MR for Learning Programming
Augmenting Coding: AR for Learning Programming
Augmenting Coding
AR for Learning Programming
Best Poster

Large Graph Exploration & Visualization

Atlas: Local Graph Exploration in a Global Context
Atlas
Local Graph Exploration in a Global Context
VIGOR: Interactive Visual Exploration of Graph Query Results
VIGOR
Interactive Visual Exploration of Graph Query Results
Symantec
Graph Playground: Graph Decompositions in 3D
Graph Playground
Graph Decompositions in 3D
Carina: Million-scale Graph Visualization in Web Browsers
Carina
Million-scale Graph Visualization in Web Browsers
FACETS: Adaptive graph exploration
FACETS
Adaptive graph exploration
ETable: Interactive Browsing and Navigation in Relational Databases
ETable
Interactive Browsing and Navigation in Relational Databases
VISAGE: Interactive Visual Graph Querying
VISAGE
Interactive Visual Graph Querying
Scalable Graph Exploration & Visualization: A survey
Scalable Graph Exploration & Visualization
A survey
TourViz: Interactive Visualization of Connection Pathways in Large Graphs
TourViz
Interactive Visualization of Connection Pathways in Large Graphs
Apolo: Explore million-node graphs in real time
Apolo
Explore million-node graphs in real time
GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration
GLO-STIX
Graph-Level Operations for Specifying Techniques and Interactive eXploration
BubbleNet: Multi-resolution Large Graph Exploration
BubbleNet
Multi-resolution Large Graph Exploration
NaturalMotion: Exploring Gesture Controls for Visualizing Time-Evolving Graphs
NaturalMotion
Exploring Gesture Controls for Visualizing Time-Evolving Graphs

Scalable Graph Mining

AttriPart: Local Partition in Rich Graphs
AttriPart
Local Partition in Rich Graphs
Scalable K-Core Decomposition: For Static Graphs Using a Dynamic Graph Data Structure
Scalable K-Core Decomposition
For Static Graphs Using a Dynamic Graph Data Structure
M-Flash: Billion-Scale Graph Computation by Bimodal Block Processing
M-Flash
Billion-Scale Graph Computation by Bimodal Block Processing
M3: billion-scale ML on a PC using virtual memory
M3
billion-scale ML on a PC using virtual memory
MMap: Easy billion-scale graph computation on a PC using virtual memory
MMap
Easy billion-scale graph computation on a PC using virtual memory
Mobile MMap: Scalable Algorithms on the Go
Mobile MMap
Scalable Algorithms on the Go
PEGASUS: Billion-Scale Graph Mining on Hadoop
PEGASUS
Billion-Scale Graph Mining on Hadoop
Open Source Software World Challenge, Silver Award
MAGE: Matching Approximate Patterns in Richly-Attributed Graphs
MAGE
Matching Approximate Patterns in Richly-Attributed Graphs

Cyber Security & Fraud

Cyber MoneyBall: Predicting Cyber Threats with Virtual Security Products
Cyber MoneyBall
Predicting Cyber Threats with Virtual Security Products
Symantec
FairPlay: Fraud and Malware Detection in Google Play
FairPlay
Fraud and Malware Detection in Google Play
MARCO: Fake Review Detection
MARCO
Fake Review Detection
SDM'14 Best Student Paper
AESOP: 99%-accurate Malware Detection
AESOP
99%-accurate Malware Detection
Patented
Deployed
Symantec
Polonium: Malware Detection over 37 Billion File Relationships
Polonium
Malware Detection over 37 Billion File Relationships
Patented
Deployed
Symantec
Latent Gesture: Mobile Protection with Touch Signatures
Latent Gesture
Mobile Protection with Touch Signatures
NetProbe: Auction Fraud Detection
NetProbe
Auction Fraud Detection
Quasi Clique: Uncovering Suspicious Links
Quasi Clique
Uncovering Suspicious Links
Insider Trading Pattern Discovery:
Insider Trading Pattern Discovery
Securities and Exchange Commission

Social Good & Health

DeepPop: Deep Learning on Satellite Imagery for Population Estimation
DeepPop
Deep Learning on Satellite Imagery for Population Estimation
Microsoft AI for Earth
Chronodes: Multi-focus mHealth Visual Data Exploration
Chronodes
Multi-focus mHealth Visual Data Exploration
mHealth Visual Discovery Dashboard: Making Sense of Mobile Health Data
mHealth Visual Discovery Dashboard
Making Sense of Mobile Health Data
Firebird: Predicting Fire Risk in Atlanta
Firebird
Predicting Fire Risk in Atlanta
KDD'16 Best Student Paper, runner-up
Deployed
Atlanta Fire Rescue Department
Scalable Architecture in Power Generating Assets: For Anomaly Detection and Visualization
Scalable Architecture in Power Generating Assets
For Anomaly Detection and Visualization
TimeStitch: Interactive Multi-focus Cohort Discovery and Comparison
TimeStitch
Interactive Multi-focus Cohort Discovery and Comparison
Characterizing Smoking and Drinking Abstinence: Using Social Media Communities
Characterizing Smoking and Drinking Abstinence
Using Social Media Communities
Understanding Pediatric Asthma Care: Using Visual Analytics
Understanding Pediatric Asthma Care
Using Visual Analytics
Children's Healthcare of Atlanta

Club Members

Minsuk (Brian) Kahng
CS PhD
Vis + AI: Human-centered AI Understanding.
Shang-Tse Chen
CS PhD
AI-infused Security: theory + applications for deep learning attack and defense.
Fred Hohman
CSE PhD
Drummer and frisbee thrower.
Nilaksh Das
CSE PhD
Haekyu Park
CS PhD
Scott Freitas
ML PhD
Anmol Chhabria
MS CSE
Siwei "Bob" Li
CS Undergrad
Kristina Marotta
Analytics Master
Matthew Keezer
CS Master
Joon Kim
CS Undergrad
Jonathan Leo
CS Undergrad
Ángel (Alex) Cabrera
CS Undergrad
Will Epperson
CS Undergrad
Omar Shaikh
CS Undergrad
Sudeep Agarwal
CS Undergrad
Duen Horng (Polo) Chau
Associate Prof
Covert designer, photographer. Rusty cellist & pianist.

Alumni

Dr. Acar Tamersoy
CS PhD
Research Scientist, Symantec Research Labs
Dr. Robert Pienta
CSE PhD
Research Scientist, Symantec
Dr. Chad Stolper
CS PhD
Software Engineer, Google
Jaegul Choo
CSE PhD
Assistant Prof, Korea University
Zhiyuan "Jerry" Lin
CS Undergrad
CS PhD, Stanford
Ramen lover and hackathon hacker.
Elias Khalil
CSE Master
CSE PhD, Georgia Tech
Paras Jain
CS Undergrad
CS PhD, UC Berkeley
Peter Polack
MS Digital Media
PhD Information Studies, UCLA
Samuel Clarke
CS Undergrad
CS Master, Carnegie Mellon
Srishti Gupta
CS Master
Data Engineer, Hike Messenger
Dezhi “Andy” Fang
CS Undergrad
Software Engineer, Airbnb
Madhuri Shanbhogue
CS Master
Software Engineer, FAcebook
Varun Bezzam
CS Master
Software Engineer, Salesforce
Prasenjeet Biswal
CS Master
Software Engineer, Oath
Meera Kamath
CS Master
Software Engineer, Microsoft
Florian Foerster
HCI Master
User Experience Researcher, Facebook
Yiqi (Victor) Chen
CS Undergrad
Software Engineer, Facebook
Aakash Goel
CS Master
Google
Shan Li
HCI Master
User Experience Designer, Oracle
Jake Williams
CS Undergrad
Kshitij Kulkarni
ECE Undergrad
Hugo Armando Gualdron Colmenares
CS Master, University of São Paulo
Changhyun Lee
CS Master
Software Enginner, Google
Kaeser Sabrin
CS PhD

CSE 6242: Data and Visual Analytics (DVA)

CSE 6242: Data and Visual Analytics (DVA) is graduate-level data science course at Georgia Tech. Polo has been teaching the campus section since Spring 2013. The course is also cross-listed as a senior undergraduate course, CX 4242. CSE 6242 is a required core course of the Master of Science in Analytics (MSA). In Spring 2018, the campus course was "mirrored" and offered as a core course of the Online Master of Science in Analytics (OMS Analytics) program. In Fall 2018, the online offering was further expanded to the Online Master of Science in Computer Science (OMS CS) program.

Year Semester Course Websites Students
2019 Spring Campus Online 1000
2018 Fall Campus Online 677
2018 Spring Campus Online 287
2017 Fall Campus 273
2017 Spring Campus 214
2016 Fall Campus 215
2016 Spring Campus 187
2015 Fall Campus 146
2015 Spring Campus 113
2014 Fall Campus 118
2014 Spring Campus 95
2013 Spring Campus 35

KDD IDEA Workshop

Interactive Data Exploration and Analytics. Great IDEAs, 6 years in a row!

Sponsors

Our research has been made possible by support and funding from: NSF (CNS1704701, IIS1563816, IIS1551614, TWC1526254, IIS1217559), NIH (1-U54EB020404-01), DARPA, NASA, Children's Healthcare of Atlanta, Google, Symantec, Yahoo, Intel, Microsoft, eBay, Amazon, LogicBlox, LexisNexis Dean's Award, James C. Edenfield Faculty Fellowship, Raytheon Faculty Fellowship.