Courses I have TAed in the past:

  • Operation Management (MBA core)
  • Managerial Statistics (MBA core)
  • High Frequency Trading and Limit Order Book
  • Big Data in Finance (Phd)
  • Introduction to Statistical Inference and Econometrics (Phd)
  • Quantitative Finance: Models and Computation
  • Introduction to R programming
  • Columbia IEOR's MOOC on Financial Enginering at Coursera

Courses I have taken in the recent past:

    Statistics, Econometrics, Machine Learning and Data Science
  • Introduction to Statistical Inference and Econometrics By Fanyin Zheng
  • Applied Statistics II: Statistical Learning By Feng Yang
  • Applied Statistics I By Feng Yang
  • Theoretical Statistics II By Arian Maleki
  • Panel Data Econometrics By Wei Jiang
  • Statistical Learning and Operation By Assaf Zeevi
  • Machine Learning for Operations By Gah-Yi Ban
  • Machine Learning (PhD Workshop) By Martin Haugh, Laurent Charlin, Shlomo Hershkop
  • Natural Language Processing (PhD Workshop)
  • Information Theory By Xiaochuan Wang
  • Mathematics of Deep Learning By Predrag Jelenkovic
  • Stochastic Models
  • Probability Theory I By Ioanis Karazas
  • Probability Theory II By Ioanis Karazas
  • Foundation of Stochastic Process By John Yao
  • Stochastic Models I By Ward Whitt
  • Stochastic Models II By David Yao
  • Optimization
  • Foundation of Optimization By Jacob Leshno
  • Optimization I By Danold Goldfarb
  • Convex Optimization By Frank E. Curtis
  • Economics
  • Economic Theory I & II: Microeconomics By Geoffrey Heal
  • Economic Theory III & IV: Game Theory and Contract Theory By Paolo Siconolfi
  • Economic Networks By Alireza Tahbaz-Salehi
  • Industrial Organizations By Kate Ho
  • Finance and Financial Engineering
  • Continuous Time Models By Neng Wang
  • Stochastic Calculus By Rama Cont
  • Fixed Income Models By Martin Haugh
  • Financial Data Analysis By Steven Kou
  • Finance Theory I By Larry Glosten
  • Asset Pricing By Tano Santos
  • Computer Skills
  • R, Python, Matlab, VBA
  • Java, C++, C, Scala
  • Deep Learning Framework: Tensorflow, Keras, Pytorch
  • Presto, Hive, SQL
  • Linux Bash, Spark