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
Related Links
Latest Publications
NeurIPS - December 7, 2020
BOTORCH: A Framework for Efficient Monte-Carlo Bayesian Optimization
Max Balandat, Brian Karrer, Daniel Jiang, Sam Daulton, Ben Letham, Andrew Gordon Wilson, Eytan Bakshy
NeurIPS - December 7, 2020
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees
Shali Jiang, Daniel Jiang, Max Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett
Bayesian Analysis 2018 - August 16, 2018
Constrained Bayesian Optimization with Noisy Experiments
Ben Letham, Brian Karrer, Guilherme Ottoni, Eytan Bakshy
VLDB 2017 - August 28, 2017
Social Hash Partitioner: A Scalable Distributed Hypergraph Partitioner
Igor Kabiljo, Brian Karrer, Mayank Pundir, Sergey Pupyrev, Alon Shalita
KDD - August 13, 2016
Compressing Graphs and Indexes with Recursive Graph Bisection
Laxman Dhulipala, Igor Kabiljo, Brian Karrer, Giuseppe Ottaviano, Sergey Pupyrev, Alon Shalita
NSDI - March 15, 2016
Social Hash: an Assignment Framework for Optimizing Distributed Systems Operations on Social Networks
Alon Shalita, Brian Karrer, Igor Kabiljo, Arun Sharma, Alessandro Presta, Aaron Adcock, Herald Kllapi, Michael Stumm
KDD - August 11, 2013
Graph Cluster Randomization: Network Exposure to Multiple Universes
Johan Ugander, Brian Karrer, Lars Backstrom, Jon Kleinberg
ACM (CHI) - April 27, 2013
Quantifying the Invisible Audience in Social Networks
Michael Bernstein, Eytan Bakshy, Moira Burke, Brian Karrer
