I am a second-year Ph.D. student in Econometrics and Statistics group at University of Chicago Booth School of Business. I hold a MSc in Statistics from U of C and a BSc in Mathematics and Applied Mathematics fron Zhejiang University(China).
My primary research interests are bayesian statistics, machine learning and network science. I am currenly working with Prof. Nick Polson and Prof. Veronika Rockova.
Papers:
- Wang, Y. & Ročková, V. (2020). Uncertainty Quantification for Sparse Deep Learning. Artificial Intelligence and Statistics (2020)
- Wang, Y., Polson, N. G., & Sokolov, V. O. (2019). Scalable Data Augmentation for Deep Learning.
- Liu, Y., Ročková, V., & Wang, Y. (2018). Variable Selection with ABC Bayesian Forests. Journal of the Royal Statistical Society, Series B (in revision)
- Feng, G., Polson, N., Wang, Y., & Xu, J. (2018). Sparse Regularization in Marketing and Economics.
Work in progress:
- Deep Learning Paticle Filtering, with Jingyu He and Nicholas Polson.
Teaching:
- Big Data (2019 Spring)
- Business Statistics (2019 Fall)