About Me
I am a Ph.D. candidate in Statistics at Harvard University, where I am advised by Kosuke Imai. My research centers on Causal Inference in the context of policy evaluation and learning, with emphasis on statistical and algorithmic decision-making. My goal is to extract statistically reliable information from data to help decision makers make better choices.
In the summer of 2025, I was a research intern in the Experimentation & Causal Inference group at Netflix.
Before joining Harvard, I earned degrees from the University of Oxford (MSc in Statistical Science), ETH Zurich (MSc in Applied Mathematics), and the University of Vienna (BSc in Mathematics). I also worked full-time as a Data Scientist at QuantCo, a consulting firm specializing in Statistical Machine Learning. Prior to my academic journey, I served in the Austrian Armed Forces, where I underwent training to become an army officer.
Research
For an always up-to-date list of publications, see my Google Scholar page.
Publications
-
Ergodic robust maximization of asymptotic growth under stochastic volatility
(2022). Finance and Stochastics, forthcoming.
Working Papers
News
- September 04, 2025. Talk: Harvard Statistics Department, “Statistical Decision Theory with Counterfactual Loss”
- June 02, 2025. Career: Netflix internship start
- May 15, 2025. Talk: ACIC, Detroit, Session Talk, “Statistical Decision Theory with Counterfactual Loss”
- May 13, 2025. Paper: Statistical Decision Theory with Counterfactual Loss is now available on arXiv
Teaching
Harvard University
- STAT 210: Probability I (Fall 2024)
- STAT 234: Sequential Decision Making (Spring 2025)
- STAT 286: Causal Inference with Applications (Fall 2025)
ETH Zurich
- Probability Theory and Statistics (Spring 2021)
Contact
Email: benedikt_koch@g.harvard.edu