Shumao Zhang 张书茂
Ph.D. Student in Applied & Comput. Math.
Advisor: Prof. Thomas Yizhao Hou
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 worked at ExxonMobil Upstream Research Company as a research eningeer intern 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
-
Solving Bayesian Inverse Problems from the Perspective of Deep Generative Networks, Computational Mechanics, 2019
Thomas Y. Hou, Ka Chun Lam, Pengchuan Zhang, Shumao Zhang
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
- ACM 154: Inverse Problems & Data Assimilation. 2019 Fall
- ACM 106: Introductory Methods of Computational Mathematics. 2020 Fall