Pin-Yu Chen

Pin-Yu Chen is a principal research scientist 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.

Chen received his PhD in electrical engineering and computer science from the University of Michigan, Ann Arbor, USA, in 2016. Chen’s recent research focuses on adversarial machine learning of neural networks for robustness and safety. His long-term research vision is to build trustworthy machine learning systems. He received the IJCAI Computers and Thought Award in 2023. He is a co-author of the book “Adversarial Robustness for Machine Learning”. At IBM Research, he received several research accomplishment awards, including IBM Master Inventor, IBM Corporate Technical Award, and IBM Pat Goldberg Memorial Best Paper. His research contributes to IBM open-source libraries including Adversarial Robustness Toolbox (ART 360) and AI Explainability 360 (AIX 360). He has published more than 50 papers related to trustworthy machine learning at major AI and machine learning conferences, given tutorials at NeurIPS’22, AAAI (’22,’23,’24), IJCAI ’21, CVPR (’20,’21,’23), ECCV ’20, ICASSP (’20,’22,’23,’24), KDD ’19, and Big Data ’18, and organized several workshops for adversarial machine learning. He is currently on the editorial board of Transactions on Machine Learning Research and IEEE Transactions on Signal Processing. He is also an Area Chair or Senior Program Committee member for NeurIPS, ICML, AAAI, IJCAI, and PAKDD, and a Distinguished Lecturer of ACM. He received the IEEE GLOBECOM 2010 GOLD Best Paper Award and UAI 2022 Best Paper Runner-Up Award.