Dr. Yingzhen Li

Biography

Yingzhen Li is currently a Senior Lecturer in the Department of Computing at Imperial College London. He is passionate about building reliable machine learning systems that generalize to unseen environments. His approach combines Bayesian statistics with deep learning. His current research interests are two-fold: the development of trustworthy machine learning models which include uncertainty quantification, robustness, explainable machine learning, decision-making, and adaptive methods such as continual learning and model editing; and generative modeling, focusing on sequential generative models that handle static data like video and time-series data, along with causal representation learning in generative models. He has worked extensively on approximate inference applications in Bayesian deep learning and deep generative models, contributing to industrial systems by implementing deep learning frameworks like TensorFlow Probability and Pyro. Prior to joining Imperial, he was a senior researcher at Microsoft Research Cambridge and interned at Disney Research. He received his PhD in engineering from the University of Cambridge, UK.

Research Interests

Experience