Niao He

Prof. Dr. Niao He is an Associate Professor in the Department of Computer Science at ETH Zurich. His research focuses on large-scale optimization, machine learning, reinforcement learning, and probabilistic inference. He is affiliated with ETH Zurich and contributes to academic discourse through his work in these areas. His profile page provides additional details about his research and academic activities.

Niao He is an Associate Professor at ETH Zürich, specializing in Optimization, Machine Learning, and Reinforcement Learning. His research focuses on developing efficient algorithms for nonconvex and nonconcave optimization problems, with applications in reinforcement learning and Bayesian inference. He has contributed to the design of stochastic optimization methods, such as the Stochastic Alternating Direction Method of Multipliers and Variance-Reduced Optimization techniques. His work also includes the development of convergent reinforcement learning algorithms with nonlinear function approximation and the analysis of sample complexity in conditional stochastic optimization. He has explored the intersection of optimization and machine learning, particularly in the context of scalable kernel methods and robust deep learning for fault diagnosis.