Michael Minyi Zhang
Michael Zhang is currently a Ph.D. student at the University of Texas at Austin in the Department of Statistics and Data Science since August 2014 under the supervision of Prof. Sinead Williamson. His research interests include statistical machine learning, scalable inference and Bayesian non-parametrics. During summer 2016, Michael was an intern at Bell Labs in the Wireless Research for the Internet of Things laboratory. Michael Zhang earned a B.S. with Honors in Statistics at the University of California, Santa Barbara.
- I am currently looking for a post-doc position. If you are interested, you may read my research statement.
- I have uploaded a new version of Robust and Parallel Bayesian Model Selection on arxiv.
- I have uploaded a new version of Accelerated Inference for Latent Variable Models on arxiv.
- I will be giving a presentation our embarassingly parallel inference in Gaussian Processes paper at Aalto University at the end of November.
- I have uploaded a new revision of our paper, Embarassingly parallel inference for Gaussian Processes, on arxiv.