Pin-Yu Chen

Department
IBM Research AI
Job Title
Principal Research Scientist
INSTRUCTION LANGUAGES
Mandarin, English

PERSONAL BIO

Dr. 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. Dr. Chen received his Ph.D. in electrical engineering and computer science from the University of Michigan, Ann Arbor, USA, in 2016. Dr. 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), IJCAI’21, CVPR(’20,’21,’23), ECCV’20, ICASSP(’20,’22,’23), 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 serves as an Area Chair or Senior Program Committee member for NeurIPS, ICML, AAAI, IJCAI, and PAKDD. He received the IEEE GLOBECOM 2010 GOLD Best Paper Award and UAI 2022 Best Paper Runner-Up Award.

Personal Website: https://sites.google.com/site/pinyuchenpage

WORK EXPERIENCE AND AWARDS

Work Experience

  • Principal Research Scientist, IBM Research, USA (2022-present)
  • Research Scientist, IBM Research, USA (2016-2022)

Awards

  • IEEE GLOBECOM 2010 GOLD Best Paper Award (2010)
  • Best Paper Runner-Up Award, Conference on Uncertainty in Artificial Intelligence (UAI) (2022)

EDUCATIONAL BACKGROUND

  • PhD in Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, USA
  • Master in Statistics, University of Michigan, Ann Arbor, USA
  • Master in Communication Engineering, National Taiwan University, Taiwan
  • Bachelor in Electrical Engineering and Computer Science, National Chiao Tung University, Taiwan

VacancIES