Bio:
Duen Horng (Polo) Chau is an Associate Professor of Computing at Georgia Tech. He co-directs Georgia Tech's MS Analytics program. He is the Director of Industry Relations of The Institute for Data Engineering and Science (IDEaS), and the Associate Director of Corporate Relations of The Center for Machine Learning. His research group bridges machine learning and visualization to synthesize scalable interactive tools for making sense of massive datasets, interpreting complex AI models, 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 (Intel Outstanding Researcher), Symantec, Google, NVIDIA, IBM, Yahoo, Amazon, Microsoft, eBay, 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; ACM TiiS 2018 Best Paper, Honorable Mention. His research led to open-sourced or deployed technologies by Intel (for ISTC-ARSA: ShapeShifter, SHIELD, ADAGIO, MLsploit), Google, Facebook, Symantec (Polonium, AESOP protect 120M people from malware), and Atlanta Fire Rescue Department. His security and fraud detection research made headlines.
He is a steering committee member of ACM IUI conference, IUI’15 co-chair, and IUI’19 program co-chair. He is an Associate Editor for ACM TIIS. He was publicity chair for ACM KDD'14 and ACM WSDM'16 He co-organized the popular IDEA workshop at ACM KDD that catalyzes cross-pollination across HCI and data mining.
Website: https://www.cc.gatech.edu/~dchau/
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Secure and Interpretable AI: Scalable Interactive and Practical Tools
We have witnessed tremendous growth in Artificial intelligence (AI) and machine learning (ML) recently. However, research shows that AI and ML models are often vulnerable to...
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