Dennis Wei is a Research Staff Member in the AI Learning group, IBM Research AI at the Thomas J. Watson Research Center. His research interests lie broadly in machine learning, signal processing, statistics, and optimization. Current areas of focus include interpretability of machine learning models, algorithmic fairness, privacy-preserving data release, and data science for social good. Other areas include graphical and other low-dimensional models, 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.
Dr. Wei 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 member of Phi Beta Kappa, Eta Kappa Nu, and Sigma Pi Sigma.