After graduation, I plan to join the Data Science Institute at Columbia University as a Postdoc Fellow. I will study the casual inference from observational data and use it to help cancer research.
Mingzhang Yin
Department of Statistics & Data Sciences
Ph.D. in Statistics, Spring 2020
Mingzhang Yin
Ph.D. in Statistics, The University of Texas at Austin (Spring 2020)
B.S. in Mathematics and Applied Mathematics, Fudan University
Dissertation: "Variational Methods with Dependence Structure"
Dissertation Advisor: Mingyuan Zhou
Research Interests: Bayesian methods, Causal inference and Deep Learning
Website: https://mingzhang-yin.github.io
What does your research focus on? How is it applied?
My research areas are Bayesian statistics and machine learning. During Ph.D. study, I focused on understanding the statistical dependence structures at different levels of data.
My research helps understand the unobserved quantities from observed data, in their point estimations, uncertainties and association relationships.
What research-related accomplishment are you most proud of and why? (paper, award, presentation, etc.)
I am proud that my work “Semi-Implicit Variational Inference” was accepted in the International Conference on Machine Learning (ICML 2018) as a Long Talk and “Meta-Learning without Memorization” was accepted in the International Conference on Learning Representations (ICLR 2020) as a Spotlight Paper.
The two works were presented as invited talks at NeurIPS workshop on Bayesian Deep Learning in 2018 and 2019 respectively.
What were you up to before you decided to enter a Ph.D. program? What brought you to SDS at UT Austin?
Before coming to UT, I studied math at Fudan University in Shanghai as an undergraduate.
The strong faculty members, the innovative environment in SDS, and of course the weird Austin city – among other things!
What have you liked the most about your time with the Ph.D. program? What are your post-graduation plans? Congratulations, by the way!
My favorite thing is that the research in SDS and UT-Austin are really novel. The researchers adapt to the field progress fast and take the lead in new discoveries.
After graduation, I plan to join the Data Science Institute at Columbia University as a Postdoc Fellow. I will study the causal inference from observational data and use it to help with cancer research.
