Request for proposals on sample-efficient sequential Bayesian decision making

Funding Agency:

Bayesian optimization is a methodology for sample-efficient learning and optimization. By leveraging a probabilistic model, it allows practitioners and researchers to explore large design spaces using only a small number of experimental trials. At Facebook, we utilize Bayesian optimization to improve product experiences, infrastructure, and aid in cutting edge research. For example, Bayesian optimization may be used to learn personalized video playback algorithms that work well across a diverse set of devices and levels of connectivity. Machine learning teams like Instagram Feed & Stories Relevance use Bayesian optimization to refine their latest machine learning models through the use of online A/B tests. And teams at Facebook Reality Lab use Bayesian optimization to efficiently conduct research in the area of perception in only a fraction of the time that conventional experiments would require.

To enable and support this work, we developed and open-sourced BoTorch, a modular framework for Bayesian optimization research, and Ax, a turn-key framework for those who want to apply Bayesian optimization to their own problems. Our goal with BoTorch is to accelerate the pace of research in the area of Bayesian optimization and unlock new potential applications. With this RFP, we hope to deepen our ties to the academic research community by seeking out innovative ideas and applications of Bayesian optimization that further advance the field. We are committed to open source and will help awardees make the products of this RFP available to the public as part of BoTorch.

Facebook is pleased to invite faculty to respond to this call for research proposals. In order to support academic work that addresses our challenges and opportunities while producing generalizable knowledge, Facebook is pleased to offer two research awards of $50,000 and $25,000, respectively. Awards will be made as unrestricted gifts to the principal investigator’s host university. Awardees will be invited to present and engage in discussion with researchers at Facebook.

Deadline: April 21, 2021

Agency Website

Eligibility Requirements

  • Proposal must comply with applicable U.S. and international laws, regulations, and policies.
  • Applicants must be current full-time faculty at an accredited academic institution that awards research degrees to PhD students.
  • Applicants must be the Principal Investigator on any resulting award.
  • Facebook cannot consider proposals submitted, prepared, or to be carried out by individuals residing in or affiliated with an academic institution located in a country or territory subject to comprehensive U.S. trade sanctions.
  • Government officials (excluding faculty and staff of public universities, to the extent they may be considered government officials), political figures, and politically affiliated businesses (all as determined by Facebook in its sole discretion) are not eligible.



Funding Type





Engineering and Physical Sciences

External Deadline

April 21, 2021