Dennis Wei is a Research Staff Member in the Trusted AI department, IBM Research AI at the Thomas J. Watson Research Center. His research interests lie broadly in machine learning, signal processing, statistics, and optimization. Current interests center around trustworthy machine learning, including interpretability of machine learning models, algorithmic fairness, causal inference and graphical models, and data science for social good. Past areas include health insurance, adaptive sampling, and sparse filter design.
He received S.B. degrees in electrical engineering and in physics in 2006, the M.Eng. degree in electrical engineering in 2007, and the Ph.D. degree in electrical engineering in 2011, all from the Massachusetts Institute of Technology. From 2011 to 2013 he was a Post-Doctoral Research Fellow in the EECS Department at the University of Michigan.
Dennis was a co-winner of the FICO Explainable Machine Learning Challenge in 2018. He received a Best Paper Honorable Mention at the 2015 SIAM International Conference on Data Mining (SDM), a Notable Paper Award at the 2013 International Conference on Artificial Intelligence and Statistics (AISTATS) and co-authored a Best Student Paper at the 2013 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). He is also a recipient of the William Asbjornsen Albert Memorial Fellowship at MIT and a Siebel Scholarship. He is a senior member of IEEE and a member of Phi Beta Kappa, Eta Kappa Nu, and Sigma Pi Sigma.