Regression Adjustment with Synthetic Controls in Online Experiments
Congshan Zhang, Dominic Coey, Matt Goldman, Brian Karrer
I’m a research scientist on the Data Science team at Facebook. I received a PhD in physics from University of Michigan and a BA in mathematics and physics from Kenyon College. My current research involves building causal models of user behavior, applying distributed optimization to improve infrastructure systems, and developing experimentation methods for networked environments.
Interests
Statistical physics, complex networks, mathematical epidemiology, causal inference, and experimental design
Areas
Latest Publications
CODE
Network Experimentation at Scale
Brian Karrer, Liang Shi, Monica Bhole, Matt Goldman, Tyrone Palmer, Charlie Gelman, Mikael Konutgan, Feng Sun
The Decoupled Extended Kalman Filter for Dynamic Exponential-Family Factorization Models
Carlos A. Gómez-Uribe, Brian Karrer
BOTORCH: A Framework for Efficient Monte-Carlo Bayesian Optimization
Max Balandat, Brian Karrer, Daniel Jiang, Sam Daulton, Ben Letham, Andrew Gordon Wilson, Eytan Bakshy
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees
Shali Jiang, Daniel Jiang, Max Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett
Constrained Bayesian Optimization with Noisy Experiments
Ben Letham, Brian Karrer, Guilherme Ottoni, Eytan Bakshy
