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Atharva Sehgal

[email protected]
atharvas.net
linkedin.com/in/atharvas

Research Interests

My research focuses on developing code generation models for automated and collaborative scientific discovery across scientific domains and modalities.

Education

Visiting Student, Caltech
Working with Yisong Yue on building structured machine learning algorithms with a focus on AI4Science.
August 2024 - Present
PhD in Computer Science, University of Texas Austin
Developing machine learning algorithms for visual reasoning (Cosmos, Escher) and scientific discovery (LaSR, neurosym-lib). Advised by Swarat Chaudhuri.
August 2021 - Present
B.S. in Computer Science, University of Illinois Urbana Champaign
Graduated with high honors. Minor in Linguistics. James Scholar.
August 2017 - May 2021

Publications

FormulaCode: Evaluating Agentic Optimization on Large Codebases PRAL @ ICML 2025
Atharva Sehgal*, James Hou*, Swarat Chaudhuri, Jennifer J. Sun, Yisong Yue
Beyond Accuracy: Metrics that Uncover What Makes a 'Good' Visual Descriptor (Best Poster) | VisCon @ CVPR 2025
Ethan Lin, Linxi Zhao, Atharva Sehgal, Jennifer J. Sun
https://arxiv.org/abs/2507.03542
Escher: Self-Evolving Visual Concept Library using Vision-Language Critics CVPR 2025
Atharva Sehgal, Patrick Yuan, Ziniu Hu, Yisong Yue, Jennifer J. Sun, Swarat Chaudhuri
https://arxiv.org/abs/2504.00185
LaSR: Symbolic Regression with a Learned Concept Library NeurIPS 2024
Arya Grayeli*, Atharva Sehgal*, Omar Costilla-Reyes, Miles Cranmer, Swarat Chaudhuri
https://arxiv.org/abs/2409.09359
Neurosymbolic Grounding for Compositional World Models ICLR 2024
Atharva Sehgal, Arya Grayeli, Jennifer J. Sun, Swarat Chaudhuri
https://arxiv.org/abs/2310.12690
Neurosymbolic Programming for Science AI4Science @ NeurIPS 2022
Jennifer J. Sun*, Megan Tjandrasuwita*, Atharva Sehgal*, Armando Solar-Lezama, Swarat Chaudhuri, Yisong Yue, Omar Costilla-Reyes
https://arxiv.org/abs/2210.05050
Composing Neural and Symbolic Reasoning with an Application to Visual Discrimination IJCAI/ECAI 2022
Adithya Murali, Atharva Sehgal, Paul Krogmeier, P. Madhusudan
https://arxiv.org/abs/1907.05878
Statheros: A Compiler for Efficient Low-Precision Probabilistic Programming DAC 2021
Jacob Laurel, Rem Yang, Atharva Sehgal, Shubham Ugare, Sasa Misailovic
https://ieeexplore.ieee.org/document/9586276

Projects

tacc-inference Library August 2024
The tacc-inference library provides a common API to run LLMs on a single node or multiple nodes of TACC's Vista and Frontera supercomputers (the largest academic supercomputer in the US). Used by 50+ labs. (pip install tacc-inf)
neurosym Library August 2023
The neurosym library is a Python package for neuro-symbolic program synthesis. It is the first framework which integrates tools for DSL design, program search, and program abstraction in a self contained package. Used extensively in research, production, and teaching. Joint work with collaborators at MIT. (pip install neurosym)

Technical Strengths

Computer Languages: Python, C, Julia, C++14, Haskell, HTML/CSS/JavaScript, OCaml
Frameworks: PyTorch/TensorFlow/Scipy, Pandas/Dask, NetworkX, Coq/Lean, Z3, Pyro

Outreach, Service, and Talks

Academic Reviewing
ICML (2023-present), NeurIPS (2022-present), ICLR (2023-present) CVPR (2025-present) ICCV (2025)
Talks
Program Synthesis and Scientific Discovery MIT (2025)
Program Synthesis and Scientific Discovery Caltech (2024)
Program Synthesis and Scientific Discovery Cornell (2024)
Neurosymbolic Programming and Scientific Discovery Chalmers University (2024)
Tutorial on Neurosymbolic Programming Caltech (2022)
Tutorial on Neurosymbolic Programming POPL (2023)
Tutorial on Neurosymbolic Programming ICSE (2024)
Tutorial on Neurosymbolic Programming MIT (2024)
Teaching
Math Tutor Caltech Y (FA24, SP25)
College Math Prep (Co-Instructor) Coleman State Prison (FA23)
DiRP: Neurosymbolic Programming (Instructor) UT Austin (SP24, FA23, SP23)
Honors: Embedded Systems (TA) UIUC (SP20)
Honors: Algorithms for String Processing (TA) UIUC (FA20, SP21)
Data Structures and Algorithms (TA) UIUC (FA19, SP20, FA20, SP21)
Discrete Mathematics (TA) UIUC (FA20)

Relevant Coursework

Program Synthesis, Computer Vision, Robot Learning, Data Driven Algorithm Design, Programming Languages, Trustworthy ML