Pin-Yu Chen

Research Staff Member

Who they work with

Categories

Robustness

Dr. Pin-Yu Chen is a Research Staff Member at IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA. He is also the chief scientist of RPI-IBM AI Research Collaboration and PI of ongoing MIT-IBM Watson AI Lab projects. Dr. Chen received his Ph.D. degree in electrical engineering and computer science and M.A. degree in Statistics from the University of Michigan, Ann Arbor, USA, in 2016. He received his M.S. degree in communication engineering from National Taiwan University, Taiwan, in 2011 and B.S. degree in electrical engineering and computer science (undergraduate honors program) from National Chiao Tung University, Taiwan, in 2009.

Dr. Chen’s recent research is on adversarial machine learning and robustness of neural networks. His long-term research vision is building trustworthy machine learning systems. He has published more than 20 papers on trustworthy machine learning at major AI and machine learning conferences, given tutorials at CVPR’20, ECCV’20, ICASSP’20, KDD’19 and Big Data’18, and co-organized several workshops for adversarial machine learning. His research interest also includes graph and network data analytics and their applications to data mining, machine learning, signal processing, and cyber security. He was the recipient of the Chia-Lun Lo Fellowship from the University of Michigan Ann Arbor. He received the NIPS 2017 Best Reviewer Award, and was also the recipient of the IEEE GLOBECOM 2010 GOLD Best Paper Award. Dr. Chen is currently on the editorial board of PLOS ONE.

At IBM Research, Dr. Chen has co-invented more than 20 U.S. patents. In 2019, he received two Outstanding Research Accomplishments on research in adversarial robustness and trusted AI, and one Research Accomplishment on research in graph learning and analysis.