Minyong Lee

Experience

• Banksalad
  • Data Foundation, Head of Data Science, 2020.04. ~ 2022.06.
• Airbnb
  • Experimentation Platform, Senior Data Scientist, 2019.05. ~ 2020.03.
  • Pricing, Senior Data Scientist, 2017.08. ~ 2019.05.
  • Pricing, Data Science Intern, Summer 2016.
• Fitbit, Research and Development, Research Intern, Summer 2014.

Education

• Ph.D. Statistics, Stanford University, 2012-2017.
• B.S. Mathematics & Economics, Seoul National University, 2012.

Publication

1. Top Challenges from the first Practical Online Controlled Experiments Summit, Somit Gupta, et al., SIGKDD Explorations, 2019.
2. Modified Active Subspace Using the Average of Gradients, Minyong R. Lee, SIAM/ASA Journal on Uncertainty Quantification, 2019.
3. Lurking Variable Detection via Dimensional Analysis, Zachary del Rosario, Minyong R. Lee, Gianluca Iaccarino, SIAM/ASA Journal on Uncertainty Quantification, 2019.
4. Winner’s Curse: Bias Estimation for Total Effects of Features in Online Controlled Experiments, Minyong R. Lee and Milan Shen, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018.
5. Single Nugget Kriging, Minyong R. Lee and Art B. Owen, Statistica Sinica, 2018.
6. Prediction and Dimension Reduction Methods in Computer Experiments (Ph.D. dissertation), Minyong R. Lee, Stanford University, 2017.

Teaching Assistant at Stanford

• STATS 363: Experimental Design (Winter 2016, Winter 2017)
• STATS 315B: Modern Applied Statistics: Data Mining (Spring 2016)
• STATS 206: Applied Multivariate Statistical Analysis (Autumn 2016)
• STATS 306B: Unsupervised learning (Spring 2015)
• STATS 200: Introduction to Statistical Inference (Winter 2013, Summer 2015)
• STATS 202: Data Mining (Summer 2013, Autumn 2013, Autumn 2015)
• STATS 191: Introduction to Applied Statistics (Winter 2014)
• STATS 305: Linear Models (Autumn 2014)
• STATS 218: Introduction to Stochastic Processes (Spring 2013)