Prasad Raghavendra Division of Computer Science (EECS) theory(THY), optimization, complexity theory, approximation algorithms
Alper Atamturk Dept of Industrial Engineering & Operations Research sparse learning, integer programming, computational optimization, robust optimization, logistics
Rajan Udwani Dept of Industrial Engineering & Operations Research algorithms, optimization under uncertainty, revenue management, pricing, online platforms
Ying Cui Dept of Industrial Engineering & Operations Research continuous optimization, optimization under uncertainty, statistical estimations, machine learning, artificial intelligence
Jason Lee Dept of Statistics Division of Computer Science (EECS) machine learning theory, optimization, statistics, deep learning
Paul Grigas Dept of Industrial Engineering & Operations Research optimization, machine learning, data-driven decision-making
Huiwen Jia Dept of Industrial Engineering & Operations Research stochastic and robust optimization, machine learning, online learning algorithms, transportation, revenue management, service system design
Dorit Hochbaum Dept of Industrial Engineering & Operations Research data mining, integer programming, discrete optimization, network flow techniques, clustering, image segmentation, machine vision, pattern recognition
Venkatesan Guruswami Dept of Mathematics Division of Computer Science (EECS) theoretical computer science, coding theory, approximate optimization, randomness in computation, computational complexity
Haiyan Huang Dept of Statistics applied statistics, functional genomics, translational bioinformatics, high dimensional and integrative genomic/genetic data analysis, network modeling, hierarchical multi-lable classification
Francesco Borrelli Dept of Mechanical Engineering automotive control systems, distributed and robust constrained control, manufacturing control systems, energy efficient buildings, model predictive control