His research bridges machine learning and visualization to synthesize scalable interactive tools for making sense of massive datasets, interpreting complex AI models and decisions, and solving real world problems in cybersecurity, human-centered AI, graph visualization and mining, and social good. His Ph.D. in Machine Learning from Carnegie Mellon University won CMU's Computer Science Dissertation Award, Honorable Mention.
He received awards and grants from NSF, NIH, NASA, DARPA, Intel, Symantec, Google, Nvidia, IBM, Yahoo, Amazon, Microsoft, eBay, Children's Healthcare of Atlanta, LogicBlox, LexisNexis; Raytheon Faculty Fellowship; Edenfield Faculty Fellowship; Outstanding Junior Faculty Award; The Lester Endowment Award; Symantec fellowship (twice); Best student papers at SDM'14 and KDD'16 (runner-up); Best demo at SIGMOD'17 (runner-up); Chinese CHI'18 Best paper.
His research led to open-sourced or deployed technologies by Google (GAN Lab), Facebook (ActiVis), Symantec (Polonium, AESOP protect 120M people from malware), Intel (SHIELD, ShapeShifter) and Atlanta Fire Rescue Department (FireBird). His security and fraud detection research made headlines (Science Magazine, The Wall Street Journal, Wired, MIT Technology Review, MSNBC, USA Today, Los Angeles Times, The Washington Post, Engadget, Gizmodo).
He is a steering committee member of ACM IUI conference, IUI’15 co-chair, and IUI’19 program co-chair. He co-organized the popular IDEA workshop (at KDD) that catalyzes cross-pollination across HCI and data mining. He is also an award-winning designer.