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SDS Student Spotlight - Mingzhang Yin

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9 February 2018—Mingzhang (Michael) Yin is a student in the PhD in Statistics program in the Department of Statistics and Data Sciences

Tell us a little bit about yourself - educational background, working experience, etc.

I am from Kunming, a city in Southwest China. I graduated from Fudan University in Shanghai with a bachelor degree in mathematics. Just after graduation, I came to join UT's Ph.D. program in Statistics.

What attracted you to the Ph.D. in Statistics program at UT?

I was attracted by the strong faculty team and active research environment.

Tell us about a project or piece of research you have worked on while attending UT.

I worked on a project to bridge the gap in uncertainty estimation between variational inference and MCMC. Variational inference is a fast Bayesian method to learn from intractable posterior and fits big data well. But it always underestimates the uncertainty. 

How would you describe your area of study/specific research to someone outside your field?

Imagine you are going to give a treatment, drive a car or make an investment based on machine learning algorithm. You will not only want a decision from the machine but also want the machine to honestly tell you how reliable the decision is. This is about uncertainty estimation. 

Tell us a few fun facts about yourself.

  • A talent you have always wanted: Playing piano
  • Favorite book: Among books in English, my favorite is Siddhartha by Herman Hesse
  • Role model: Roger Federer
  • Favorite vacation destination: Phuket Island
  • Favorite food: Mango
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