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 revision of our paper, Embarassingly parallel inference for Gaussian Processes, on arxiv.
- Our new paper, Accelerated Inference for Latent Variable Models, is available on arxiv.
- I will be giving a contributed talk on our embarassingly parallel inference in Gaussian Processes paper at ISBA BNP 11. The slides of my presentation are available here