Eric Atkinson
eatkinson2@binghamton.edu | @eric93 | DBLP |
I'm Eric, a computer science academic who works primarily on programming languages for uncertainty. My research interests include programming languages, program runtimes, program analysis, formal methods, and language design for unusual domains. I am also interested in the intersection of programming languages and AI. I completed my Ph.D. at MIT in Fall 2023, and am currently a visiting reseracher at INSAIT in Sofia, Bulgaria. Starting in Spring 2024, I will be joining the faculty of Binghamton University as an Assistant Professor. I am currently recruiting Ph.D. students for my group in all areas encompassed by my research interests; please email me if you are interested in joining!
Professional History
Assistant Professor (Starting Spring 2024) | Binghamton University |
Visiting Researcher (Fall 2024) | INSAIT |
Research Intern (Summer 2018) | |
Research Intern (Summer 2013) | Mozilla Research |
Education
Doctor of Philosophy (February 2024) | Massachusetts Institute of Technology |
Dissertation: A Languauge and Logic for Programming and Reasoning with Partial Observability | |
Advisor: Michael Carbin | |
Master of Science (February 2018) | Massachusetts Institute of Technology |
Thesis: Typesafety for Explicitly-Coded Probabilistic Inference Procedures | |
Advisor: Michael Carbin | |
Bachelor of Science (May 2015) | University of California, Berkeley |
Publications
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Eric Atkinson, Charles Yuan, Guillaume Baudart, Louis Mandel, and Michael Carbin. Semi-Symbolic Inference for Efficient Streaming Probabilistic Programming. OOPSLA 2022. Extended arXiv Version
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Eric Atkinson, Guillaume Baudart, Louis Mandel, Charles Yuan, and Michael Carbin. Statically Bounded-Memory Delayed Sampling for Probabilistic Streams. OOPSLA 2021. Extended arXiv Version
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Cambridge Yang, Eric Atkinson, and Michael Carbin. Simplifying Dependent Reductions in the Polyhedral Model. POPL, 2021. Link
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Guillaume Baudart, Louis Mandel, Eric Atkinson, Benjamin Sherman, Marc Pouzet, and Michael Carbin. Reactive Probabilistic Programming. PLDI 2020. Extended arXiv Version
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Eric Atkinson and Michael Carbin. Programming and Reasoning with Partial Observability. OOPSLA 2020. Extended arXiv Version
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Yishen Chen, Ajay Brahmakshatriya, Charith Mendis, Alex Renda, Eric Atkinson, Ondrej Sykora, Saman Amarasinghe, and Michael Carbin. Bhive: A Benchmark Suite and Measurement Framework for Validating x86-64 Basic Block Performance Models. IISWC, 2019.
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Eric Atkinson, Cambridge Yang, and Michael Carbin. Verifying Handcoded Probabilistic Inference Procedures. arXiv 2018
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Eric Atkinson and Michael Carbin. Towards Correct-by-Construction Probabilistic Inference. NeurIPS ML Sys Workshop, 2016
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Leo A. Meyerovich, Matthew E. Torok, Eric Atkinson, and Rastislav Bodik. Parallel Schedule Synthesis for Attribute Grammars. PPoPP, 2013
Teaching
- Teaching Assistant. 6.UAR. Spring 2021
- Lab Assistant. CS 61A. Spring 2012
Service
Committees
Date | Committee |
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LAFI 2023 | Program Committee, Member |
2022 | MIT EECS Faculty Search Committee, Student Member |
2021 | MIT EECS Faculty Search Committee, Student Member |
OOPSLA 2022 | Aritifact Evaluation Committee, Member |
OOPSLA 2022 | Aritifact Evaluation Committee, Member |
POPL 2020 | External Reviewer |
Mentoring
- 2021 MIT EECS GAAP program (mentoring program for graduate school applicants from underrepresented groups).
- SIGPLAN-M mentor (2023-present).