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PhD student in Econometrics and Statistics

University of Chicago Booth School of Business

Bio

I am a fifth-year Ph.D. student in the Econometrics and Statistics group at the University of Chicago Booth School of Business. My primary research interests are deep learning, approximate Bayesian inference, Bayesian nonparametrics and high-dimensional statistics. I am currently working with Prof. Veronika Rockova and Prof. Nick Polson.

I am on the 2022-2023 job market.

Interests

  • Deep Learning
  • Approximate Bayesian Inference
  • Bayesian Nonparametrics
  • High-dimensional Statistics
  • Quantitative Marketing

Education

  • PhD student in Econometrics and Statistics, 2018-now

    University of Chicago Booth School of Business

  • MSc in Statistics, 2016-2018

    University of Chicago

  • BSc in Mathematics and Applied Mathematics, 2012-2016

    Zhejiang University

Publications

(2022). Approximate Bayesian Computation via Classification. Journal of Machine Learning Research.

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(2022). Data Augmentation for Bayesian Deep Learning. Bayesian Analysis.

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(2021). Variable Selection with ABC Bayesian Forests. Journal of the Royal Statistical Society, Series B.

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(2020). Uncertainty Quantification for Sparse Deep Learning. 23rd Conference on Artificial Intelligence and Statistics.

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Experience

 
 
 
 
 

Data Scientist Intern

Google Research

Jun 2021 – Aug 2021 New York City, NY
 
 
 
 
 

Data Science Intern

Conversant Media

Jun 2020 – Sep 2020 Chicago, IL

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