Michael Minyi Zhang
Michael Zhang is currently an assistant professor since January 2021 in the School of Computing and Data Science at the University of Hong Kong. His research interests include statistical machine learning, scalable inference and Bayesian non-parametrics. Michael Zhang was a post-doctoral researcher at Princeton University under the supervision of Profs. Barbara Engelhardt and Brandon Stewart and earned a Ph.D. in statistics at the University of Texas at Austin where he was advised by Prof. Sinead Williamson.
News
- Multi-View Oriented GPLVM: Expressiveness and Efficiency has been accepted to NeurIPS 2025.
- I will serve as area chair at AISTATS 2026.
- Scalable Random Feature Latent Variable Models has been published in IEEE TPAMI.
- I will be visiting University College London during summer 2025 thanks to support from the Sino-British Fellowship Trust.
- Online Student-t Processes with an Overall-local Scale Structure for Modelling Non-stationary Data has been published in AISTATS 2025.
- A Deep Bayesian Nonparametric Framework for Robust Mutual Information Estimation is now available on arxiv.
- Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds has been published in Machine Learning.
- I will serve as an area chair at AISTATS 2025 and ICML 2025.
- A Semi-Bayesian Nonparametric Hypothesis Test Using Maximum Mean Discrepancy with Applications in Generative Adversarial Networks has been published in Transactions on Machine Learning Research.
- I am now an Associate Editor at Statistics and Computing.