[TYPES/announce] CFP: MAPS 21: 5th Annual Symposium on Machine Programming

[Aws Albarghouthi]

The 5th Annual Symposium on Machine Programming
(previously Machine Learning and Programming Languages)

# Call for Papers

Due to recent algorithmic and computational advances, machine learning
has seen a surge of interest in both research and practice. From
natural language processing to self-driving cars, machine learning is
creating new possibilities that are changing the way we live and
interact with computers. However, the impact of these advances on
programming languages remains mostly untapped. Yet, incredible
research opportunities exist when combining machine learning and
programming languages in novel ways.

This symposium seeks to bring together programming language and
machine learning communities to encourage collaboration and
exploration in the areas of mutual benefit. The symposium will include
a combination of rigorous peer-reviewed papers and invited events. The
symposium will seek papers on a diverse range of topics related to
programming languages and machine learning including (and not limited
to):

Application of machine learning to compilation and run-time scheduling
Collaborative human / computer programming (i.e., conversational programming)
Deterministic and stochastic program synthesis
Infrastructure and techniques for mining and analyzing large code bases
Interoperability between machine learning frameworks and existing code bases
Probabilistic and differentiable programming
Programming language and compiler support for machine learning applications
Programming language support and implementation of machine learning frameworks
Neurosymbolic and intentional programming

# Website

https://pldi21.sigplan.org/home/maps-2021#the-5th-annual-symposium-on-machine-programming

# Evaluation Criteria

As in previous years, reviewers will evaluate each contribution for
its significance, originality, and clarity to the topics listed above.
Submissions should clearly state how their novelty and how they
improve upon existing work.

Evaluation will be double-blind and papers must be properly
anonymized. This means that author names and affiliations must be
omitted from the submission. Additionally, if the submission refers to
prior work done by the authors, that reference should be made in third
person. These are firm submission requirements. If you have questions
about making your paper double blind, please contact the Program
Chair.

Broader Impact. Due to the growing concerns regarding potential
positive and negative impacts of any research work, this year, the
authors of MAPS submissions are asked to include a section on the
potential broader impact of their work. This section should highlight
an evaluation of potential misuses and negative impacts of the
presented technology on its users and those indirectly affected, such
as their friends and families, communities, society, and the planet.
Authors should ponder and discuss the negative outcomes of their
research 1) using its current form, 2) if enhanced in the future with
new capabilities. They should also discuss potential ways to mitigate
those harms (policy, law, alternative design choice, etc.).

The broader impact section will be outside the page limit of the
original paper. This section should be at least one paragraph but
should not exceed 1 page. Although this section is a must-have, this
year, the decision to accept the paper will not be influenced by the
discussed negative impacts. However, it might influence the acceptance
decision in future MAPS.

# Paper Submissions

Submissions must be in English. Papers should be in PDF and format and
no more than 8 pages in standard two-column SIGPLAN conference format
including figures and tables but excluding references and appendices.
Submissions must be made through the online submission site (TBD).

All accepted papers will appear in the published proceedings and
available on the ACM Digital Library. Authors will have the option of
having their final paper accessible from the workshop website as well.

Authors must be familiar with and abide by SIGPLAN’s republication
policy, which forbids simultaneous submission to multiple venues and
requires disclosing prior publication of closely related work.



General Chair: Roopsha Samanta (Purdue University)
Program Chair: Isil Dillig (University of Texas at Austin)
Publicity Chair: Aws Albarghouthi (University of Wisconsin Madison)
Ethics Chair: Jesmin Jahan Tithi (Intel Labs, ACM-FCA, ACM COPE)


# Program Committee:
Farhana Aleen (Nvidia)
Dana Drachsler Cohen (Technion)
Niranjan Hasabnis (Intel Labs)
Rania Khalaf (IBM TJ Watson)
Vinod Grover (Nvidia)
Kuldeep Meel (National University of Singapore)
Erik Meijer (Facebook)
Sasa Misailovic (University of Illinois at Urbana–Champaign)
Augustus Odena (Google)
Alex Polozov (Microsoft Research)
Alex Ratner (University of Washington)
Calvin Smith (UT Austin)


# Steering Committee:
Raj Barik (Uber)
Alvin Cheung (UC Berkeley)
Stefano Ermon (Stanford University)
Justin Gottschlich (Chair, Intel Labs and UPenn)
Costin Iancu (Lawrence Berkeley National Lab)
Kunle Olukotun (Stanford University)
Tatiana Shpeisman (Google Brain)
Armando Solar-Lezama (MIT)
Mayur Naik (University of Pennsylvania)

-- 
Aws