Headshot of Max Balandat
Headshot of Max Balandat


Max Balandat

Research Scientist - Core Data Science

I lead the Modeling & Optimization team within the Adaptive Experimentation group on Meta’s Core Data Science team. We focus on developing methods and tools for probabilistic modeling and sample-efficient optimization, and apply them to a broad range of applications across the company, including infrastructure optimization, AutoML, online A/B tests, ranking systems, and AR/VR. I also lead the development of BoTorch, an open-source library for Bayesian Optimization in PyTorch.

In the past, I have also worked on the intersection of Machine Learning and Econometrics, in particular on how to utilize Machine Learning algorithms to perform causal inference in experimental and non-experimental settings.

I hold an MA in Mathematics and a PhD in Electrical Engineering and Computer Sciences from UC Berkeley.


Bayesian Optimization, Gaussian processes, probabilistic modeling, causal inference and machine Learning

Latest Publications

Sustainable AI: Environmental Implications, Challenges and Opportunities

Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, James Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Max Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim Hazelwood

MLSys - 2022