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 and works closely with Profs. Lizhen Lin and Fernando Perez-Cruz. 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 have uploaded a new revision of Embarassingly Parallel Inference for Gaussian Processes on arxiv, with code available on Github.
- Robust and Parallel Bayesian Model Selection has been published in Computational Statistics & Data Analysis.
- I successfully defended my dissertation! Thank you to all those who made it possible.
- I have uploaded a new version of Accelerated Inference for Latent Variable Models on arxiv.