Eric Atkinson
eatkinson2@binghamton.edu | @eric93 | DBLP |
I'm Eric, an assistant professor of computer science 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 was previously a visiting reseracher at INSAIT in Sofia, Bulgaria. Starting in Spring 2024, I have joined 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 (Spring 2024 - present) | 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
- Instructor. CS 571 - Programming Languages. Spring 2024.
- Teaching Assistant. 6.UAR. Spring 2021
- Lab Assistant. CS 61A. Spring 2012
Service
Committees
Date | Committee |
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LAFI 2024 | 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 2021 | 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).