Scalable. Interactive. Interpretable.
At Georgia Tech, we innovate at the intersection of data mining and human-computer interaction (HCI) to synthesize scalable, interactive, and interpretable tools that amplify human’s ability to understand and interact with billion-scale data and machine learning models. Our focus application areas include cybersecurity (e.g., fraud detection, malware detection, and adversarial machine learning), health, and social good.

Machine Learning Visualization & Interpretation

Interpretable deep learning and machine Learning through interactive visualization, with application in adversarial machine learning.

ActiVis
Visual Exploration of Industry-Scale Deep Neural Network Models
Deployed
Facebook
ShapeShop
Towards Understanding Deep Learning Representations via Interactive Experimentation
PNNL
Protect AI with JPEG
Simple, powerful defense for attack on deep learning
Intel
ML Cube
Visual Exploration of Machine Learning Results Using Data Cube Analysis
Facebook

Large Graph Exploration & Visualization

VIGOR
Interactive Visual Exploration of Graph Query Results
Symantec
Graph Playground
Graph Decompositions in 3D
Carina
Interactive Million-Node Graph Visualization using Web Browser Technologies
FACETS
Adaptive graph exploration
eTable
Interactive Browsing and Navigation in Relational Databases
VISAGE
Interactive Visual Graph Querying
Scalable Graph Exploration & Visualization
A survey
Apolo
Explore million-node graphs in real time
GLO-STIX
Graph-Level Operations for Specifying Techniques and Interactive eXploration
BubbleNet
Multi-resolution Large Graph Exploration
NaturalMotion
Exploring Gesture Controls for Visualizing Time-Evolving Graphs

Scalable Graph Mining

M-Flash
Billion-Scale Graph Computation by Bimodal Block Processing
M3: Easy Billion-scale Machine Learning
Scale up algorithms using virtual memory
MMap: Easy Billion-scale Graph Computation
Scale up algorithms using virtual memory
Mobile MMap
Scalable Algorithms on the Go
Scalable Architecture in Power Generating Assets
For Anomaly Detection and Visualization
PEGASUS
Mining Billion-Scale Graphs
Open Source Software World Challenge, Silver Award
MAGE
Matching Approximate Patterns in Richly-Attributed Graphs

Cyber Security & Fraud

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

Social Good & Health

Chronodes
Multi-focus mHealth Visual Data Exploration
mHealth Visual Discovery Dashboard
Making Sense of Mobile Health Data
Firebird
Predicting Fire Risk in Atlanta
KDD'16 Best Student Paper, runner-up
Deployed
Atlanta Fire Rescue Department
PASSAGE
A Travel Safety Assistant with Safe Path Recommendations for Pedestrians
TimeStitch
Interactive Multi-focus Cohort Discovery and Comparison
Characterizing Smoking and Drinking Abstinence
Using Social Media Communities
Understanding Pediatric Asthma Care
Usign Visual Analytics
Children's Healthcare of Atlanta

KDD IDEA Workshop

Interactive Data Exploration and Analytics. Great IDEAs, 5 years in a row!

Club Members

Acar Tamersoy

Research Scientist, Symantec Research Labs

Robert Pienta

PhD Candidate, GT CSE

Minsuk (Brian) Kahng

PhD Student, GT CS

Shang-Tse Chen

PhD Student, GT CS

Fred Hohman

PhD Student, GT CSE

Maker, techie, and drummer.

Nilaksh Das

PhD Student, GT CSE

Dezhi “Andy” Fang

Undergraduate Student, GT CS

Siwei "Bob" Li

Undergraduate Student, GT CS

Matthew Keezer

Masters Student, GT CS

Madhuri Shanbhogue

Masters Student, GT CS

Prasenjeet Biswal

Masters Student, GT CS

Zhiyuan "Jerry" Lin

PhD Student, Stanford CS

Ramen lover and hackathon hacker.

Nathan Dass

Undergraduate Student, GT CS

Sam Ford

Undergraduate Student, GT CS

Joon Kim

Undergraduate Student, GT CS

Paras Jain

Engineer, DeepScale

Peter Polack

PhD Student, UCLA

Srishti Gupta

Apple

Samuel Clarke

Masters Student, Stanford CS

Elias Khalil

PhD Student, GT CSE

Meera Kamath

Software Engineer, Microsoft

Florian Foerster

User Experience Researcher, Facebook

Yiqi (Victor) Chen

Software Engineer, Facebook

Aakash Goel

Google

Shan Li

User Experience Designer, Oracle

Jake Williams

Undergraduate Student, GT CS

Kshitij Kulkarni

Undergraduate Student, GT ECE

Hugo Armando Gualdron Colmenares

Changhyun Lee

Software Enginner, Google

Kaeser Sabrin

PhD Student, GT CS

Jaegul Choo

Assistant Professor, Korea University

Duen Horng (Polo) Chau

Assistant Prof, GT CSE

Covert designer, photographer. Rusty cellist & pianist.

Sponsors

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