UMKC
Spring 2023
Washington University in St. Louis
Fall 2021
Math 415: Partial Differential Equations
Spring 2021
Math 450: Optimization Methods in Machine Learning.
GitHub repo: https://github.com/scaomath/wustl-math450
Fall 2020
Math 449: Numerical Applied Mathematics.
GitHub repo: https://github.com/scaomath/wustl-math449
University of California Irvine
Spring 2020
Math 130C: Stochastic Processes
Winter 2020
Math 10: Introduction to Programming in Data Science.
GitHub repo: https://github.com/scaomath/UCI-Math10
Python starter: getting ready for Math 10
Math 130B: Multivariate Probability
Fall 2019
Math 112A: Partial Differential Equations
Math 290C: Calculus of Variation
Mentoring Kaggle machine learning competition
During summers and winter break, Shuhao will be dedicated to mentor (a few) students in the Kaggle machine learning competition: general cross-validation and data analysis, Python workflow, advanced tricks in Pandas, how to write quality code and debug complex Python scientific computing codes, etc. If anyone is interested, please contact Shuhao near the end of a semester (even if not taking Shuhao’s class).
Kaggle in-class competitions
To get started with competing with data scientists from all over the world, taking a class and then participating an in-class Kaggle competition is a great way to learn and practice. Here is a list of in-class competitions I have hosted in the past.
Some project guideline:
Jane Street Market Prediction Competition Dec 2020
Place: Bronze medal, 241 out of 4245 teams; GitHub repo: https://github.com/scaomath/kaggle-jane-street; Student mentored: Ethan Zheng, currently a software engineer at Amazon.
Los Alamos National Lab Earthquake Prediction Competition June 2019
Place: Bronze medal, 381 out of 4516 teams; Student mentored: Ziteng Pang, currently a grad student at UMich.