Shumao Zhang 张书茂

Ph.D. Student in Applied & Comput. Math.

Dept. of Computing + Mathematical Sciences

California Institute of Technology, Pasadena, CA

Bio Sketch

I am very glad to be a Ph.D. student in Applied & Comput. Math. at Caltech since 2017, and work with Prof. Thomas Yizhao Hou. Prior to this, I obtained my B.S. in Pure and Applied Math. at Tsinghua University, from 2013 to 2017. Over my years at Tsinghua, Prof. Hao Wu guided me into the frontier of research in applied & comput. math. I was fortunate to visit Prof. Qiang Du at Columbia University for research training, and to work with Dr. Jifeng Dai at Microsoft Research Asia to catch up with the latest progress in machine learning and computer vision, during my undergrad. I am also proud of being a 7-er as I graduated from Chengdu No.7 Middle School, Sichuan, China.

I interned at ExxonMobil Upstream Research Company as a research eningeer in the summer of 2020.

Contact Info

Email: zhangsm1995@gmail.com
Github: https://github.com/ShumaoZ
Office: Annenberg 327, Caltech

Research Interest

I am interested in data-driven problems in the interdisciplinary area of applied math and machine learning.

Publications

Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference, ICML, 2021

Shumao Zhang, Thomas Y. Hou, Pengchuan Zhang
Solving Bayesian Inverse Problems from the Perspective of Deep Generative Networks, Computational Mechanics, 2019

Thomas Y. Hou, Ka Chun Lam, Pengchuan Zhang, Shumao Zhang (alphabetical order)

Awards

Excellent Graduate of Tsinghua University, 2017
Scholarship in memory of the December 9th Movement, 2015

Teaching Experiences

I served as instructor and teaching assistant at Caltech for some undergraduate and graduate applied math courses.

As Instructor:

ACM 11: Introduction to Matlab & Mathematica. 2019 Spring

As Teaching Assistant:

ACM 105: Applied Real & Functional Analysis. 2017 Winter, 2018 Winter, 2019 Winter
CMS 117: Introduction to Probability & Random Processes. 2018 Fall
ACM 11: Introduction to Matlab & Mathematica. 2018 Spring, 2020 Spring
ACM 154: Inverse Problems & Data Assimilation. 2019 Fall
ACM 106: Introductory Methods of Computational Mathematics. 2020 Fall & Winter