Applications closed

Probability and Programming request for proposals


In the past few years, we have seen an explosion of interest in topics at the intersection of programming languages and machine learning. This is not a coincidence: there has been a growth in real-world applications that need probabilistic thinking. Additionally, the community has realized that probabilistic methods play a genuinely useful role in program analysis – for example, in ranking of deduced facts in static analyses, in type reconstruction, and in general to build explainable generative models. Machine learning techniques such as efficient automatic differentiation are no longer esoteric, and form the basis for popular deep learning frameworks such as Tensorflow and PyTorch and differentiable programming languages like Swift For Tensorflow and others. Deep learning also relies on compiler and code generation techniques to target GPUs and special-purpose accelerator hardware.

At Facebook, we are doing forward-looking research, as well as putting into production concrete results from several of these threads. We introduced HackPPL, which extends our internal PHP dialect into a full-fledged probabilistic programming language, and are creating extensions to Python to eliminate string-based API patterns. We have started various language-centric projects around acceleration and differentiable programming. We also have a portfolio of projects in the “big code” space, exploring several topics such as code search and recommendation, automatic bug fixing, and program synthesis using machine learning. Together, this work hopes to have impact across all of Facebook’s infrastructure.

To foster further innovation in these topics, and to deepen our collaboration with academia, Facebook is pleased to invite faculty and graduate students to respond to this call for research proposals pertaining to the aforementioned topics. We anticipate awarding a total of ten awards, each in the $50,000 range. Payment will be made to the proposer’s host university as an unrestricted gift.

Award Recipients

University of Wisconsin-Madison

Aws Albarghouthi

Massachusetts Institute of Technology

Vikash Mansinghka


Todd Millstein

University of Pennsylvania

Mayur Naik

University of Wisconsin-Madison

Thomas W. Reps

Purdue University

Tiark Rompf

University of Oxford

Samuel Staton

UC Irvine

Erik B. Sudderth

Purdue University

Lin Tan

UC Davis

Aditya Thakur

Applications Are Currently CLosed

Application Timeline

Notifications will be sent by email to selected applicants by April 30th, 2019.

Launch Date

January 17, 2019


March 1, 2019

Winners Announced

April 30, 2019

Areas of Interest

We are interested in proposals that address fundamental problems at the intersection of machine learning, programming languages and software engineering, including:

  • Differentiable programming
  • Probabilistic programming
  • Languages and tools for data science
  • Programming tools built using “big code”
  • Applications of machine learning to optimize systems and human workflows


Proposals should include

  • Names of the researcher(s) involved in the proposed work with links to their DBLP and/or Google Scholar™ pages
  • Host academic research institution with administrative and financial information
  • Clear and concise statement of the scientific contribution and routes to eventual deployment (2 pages) and a proposed budget description (1 page) uploaded in a single PDF file
  • Indication of any previous or current connections/collaborations with Facebook (in which case, please name any Facebook contacts)

Additional Information

Winners will be invited to a Facebook event at PLDI 2019 and to the annual Programming Language Enthusiast Mind Melt (PLEMM) held in Seattle, WA in Fall 2019. Facebook will pay for the winners’ travel and accommodations to attend PLEMM (one representative per winning proposal).

We encourage the winners to openly publish any findings/insights from their work. Successful awardees will be listed on the Facebook Research website.

Terms & Conditions

  • By submitting a proposal, you are authorizing Facebook to evaluate the proposal for a potential award, and you agree to the terms herein.
  • You agree that Facebook will not be required to treat any part of the proposal as confidential or protected by copyright.
  • You agree and acknowledge that personal data submitted with the proposal, including name, mailing address, phone number, and email address of you and other named researchers in the proposal may be collected, processed, stored and otherwise used by Facebook for the purposes of administering the website and evaluating the contents of the proposal.
  • You acknowledge that neither party is obligated to enter into any business transaction as a result of the proposal submission, Facebook is under no obligation to review or consider the proposal, and neither party acquires any intellectual property rights as a result of submitting the proposal.
  • Any feedback you provide to Facebook in the proposal regarding its products or services will not be treated as confidential or protected by copyright, and Facebook is free to use such feedback on an unrestricted basis with no compensation to you.