Students

Students

Wonho Bae

active learning, meta learning, semi-weakly supervised learning

Jiaming Cheng

Optimization under uncertainty, Network economics, Market design

Zhenan Fan

Structured optimization and federated learning

Curtis Fox

Adaptive Stochastic Optimization Methods for Machine Learning

Emily Gong

Optimal Transport

Dylan Green

Deep Generative Models for Video

Emma Hansen

Optimisation theory, duality

Jonas J├Ąger

Intersection of Quantum Computing and Machine Learning

Milad Jalai

Statistical Learning Theory, Differential Privacy

Yorker Lin

Numerical Methods for Differential Geometry, Information Geometry, Manifold Optimization

Michael Liu

Graph Neural Networks and Deep Learning

Alan Milligan

Machine Learning & Optimization

Bahareh Najafi

Representation Learning in Dynamic Graphs

Yi Ren

Learning dynamics and systematic generalization problems

Nicholas Richardson

Signal Processing, Machine Learning, Musical Applications

Victor Sanches Portella

Online learning, optimization, and algorithm design

Matthew Scott

Generative Compressed Sensing and High-Dimensional Probability

Betty Shea

Optimization and algorithms

Hamed Shirzad

Graph Neural Networks, Evaluating Generative Models for the Graphs

Qi Yan

Generative model for graphs, self-driving

Helen Zhang

My research area is optimization in safe reinforcement learning