At POPL 2019, we launched the Probability and Programming research awards with the goal of receiving proposals from academia that addressed fundamental problems at the intersection of machine learning, programming languages, and software engineering.
For 2020, we are continuing this momentum and broadening our slate of topics of interest.
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, as 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 the ranking of deduced facts in static analyses, in type reconstruction, and, in general, in building 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, such as Swift For Tensorflow, Julia, Jax, and others. Deep learning also relies on compiler and code generation techniques to target GPUs and special-purpose accelerator hardware.
At Facebook, we do forward-looking research and put concrete results from several of these threads into production. Building on our work on HackPPL, we are developing a probabilistic programming language that exploits model structure in order to achieve faster and more interpretable inference. We also have various ongoing language-centric projects around acceleration and differentiable programming. More recently, we have started studying neural networks and other probabilistic models with the goal of better understanding their generalization and robustness characteristics.
Last but not least, we 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. Our work goes beyond just the code artifacts—to bring data-driven solutions to all aspects of the software development lifecycle including issue reporting and resolution. Together, this work is already having impact across all of Facebook’s infrastructure.
Call for proposals
To foster further innovation in these topics at the intersection of machine learning, programming languages, statistics, and software engineering, 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 $50K range. Payment will be made to the proposer’s host university as an unrestricted gift.
We are inviting proposals that advance foundations or practice of any of the topics mentioned above. The list includes, but is not limited to:
- Differentiable programming
- Probabilistic programming
- Programming tools built using “big code”
- Applications of machine learning to troubleshoot and optimize systems
- Robustness and uncertainty management for ML models
Proposals must include
- A summary of the project (1-2 pages) explaining the area of focus, a description of techniques, any relevant prior work, and a timeline with milestones and expected outcomes.
- A draft budget description (1 page) including an approximate cost of the award and explanation of how funds would be spent
- Curriculum vitae for all project participants.
- Organization details, including tax information and administrative contact details
- Awards must comply with applicable U.S. and international laws, regulations, and policies.
- Applicants must be a 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.
- Applicants and all individuals involved in the preparation of the proposal or use of any resulting award must reside in the Territory.
“Territory” is defined as any area, country, state, territory, or province where applicable laws do not prohibit applying for or receiving a grant in this RFP and excludes China, Cuba, Crimea, Iran, North Korea, Sudan, Myanmar/Burma, Syria, Zimbabwe, Iraq, Lebanon, Liberia, Libya, Somalia, Zimbabwe, Belarus and any other area or country designated by the applicable agency that designates trade sanctions. Government officials, political figures, and businesses politically affiliated (all as determined by Facebook in its sole discretion) are not eligible to apply for the grant.
Timing and dates
- Applications are now open. Deadline to apply is Wednesday, March 4, 2020 at 5:00 p.m. AOE.
- Notifications will be sent by email to selected applicants by April 30, 2020.
Winners will be invited to the annual Programming Language Enthusiast Mind Melt (PLEMM) held in Fall 2020 (location TBD). Facebook will pay for the winners’ travel and accommodations (one representative per winning proposal) to attend PLEMM and present during a workshop on probability and programming.
We encourage the winners to openly publish any findings/insights from their work. Successful awardees will be listed on the Facebook Research website.
Frequently Asked Questions
Do you typically limit the salary of the PI in the gift?+
Should the proposal be double- or single-spaced? Is there any required/expected font?+
What is the award cycle or when does the funding year begin and end?+
Can award funds be used to cover a researcher's summer salary while conducting research?+
Can you please explain the budget breakdown in more detail?+
We are working as co-PIs and are at the same institution. Is it possible to list both of our names as PI for an RFP proposal?+