I graduated summa cum laude from the University of Illinois Urbana-Champaign (UIUC) in December 2025, earning a B.S. in Computer Science and Statistics. I have had the privilege of working with Prof. Alex Aiken (Stanford), Prof. Sasa Misailovic (UIUC), and Prof. Gagandeep Singh (UIUC). I am largely interested in the intersection of Machine Learning and Systems. My research has culminated in publications at NeurIPS, ICLR, and ICML, state-of-the-art models downloaded 300k+ times by the open-source community, and oral presentations at venues including POPL and ICLR, as well as at institutions (e.g., Stanford and CMU) and in industry.

Selected Papers

DINGO: Constrained Inference for Diffusion LLMs
Tarun Suresh*, Debangshu Banerjee*, Shubham Ugare, Sasa Misailovic, Gagandeep Singh
Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS), 2025
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CRANE: Reasoning with Constrained LLM Generation
Debangshu Banerjee*, Tarun Suresh*, Shubham Ugare, Sasa Misailovic, Gagandeep Singh
Proceedings of the 42nd International Conference on Machine Learning (ICML), 2025
pdf

BEAVER: An Efficient Deterministic LLM Verifier
Tarun Suresh*, Nalin Wadhwa*, Debangshu Banerjee, Gagandeep Singh
In Submission
pdf

IterGen: Iterative Semantic-aware Structured LLM Generation with Backtracking
Shubham Ugare, Rohan Gumaste, Tarun Suresh, Gagandeep Singh, Sasa Misailovic
Proceedings of the 13th International Conference on Learning Representations (ICLR), 2025
pdf

SynCode: LLM Generation with Grammar Augmentation
Shubham Ugare, Tarun Suresh, Hangoo Kang, Sasa Misailovic, Gagandeep Singh
Transactions on Machine Learning Research (TMLR), 2025
pdf| code

CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking
Tarun Suresh*, Revanth Gangi Reddy*, Yifei Xu, Zach Nussbaum, Andriy Mulyar, Brandon Duderstadt, Heng Ji
Proceedings of the 13th International Conference on Learning Representations (ICLR), 2025
pdf| blog post| code

SweRank: Software Issue Localization with Code Ranking
Revanth Gangi Reddy*, Tarun Suresh*, JaeHyeok Doo*, Ye Liu, Xuan Phi Nguyen, Yingbo Zhou, Semih Yavuz, Caiming Xiong, Heng Ji, Shafiq Joty
Proceedings of the 14th International Conference on Learning Representations (ICLR), 2026
pdf| code

CodeARC: Benchmarking Reasoning Capabilities of LLM Agents for Inductive Program Synthesis
Anjiang Wei, Tarun Suresh, Jiannan Cao, Naveen Kannan, Yuheng Wu, Kai Yan, Thiago S. F. X. Teixeira, Ke Wang, Alex Aiken
Proceedings of the 2nd Conference on Language Modeling (COLM), 2025
pdf| code

SuperCoder: Assembly Program Superoptimization with Large Language Models
Anjiang Wei, Tarun Suresh, Huanmi Tan, Yinglun Xu, Gagandeep Singh, Ke Wang, Alex Aiken
The 4th Deep Learning for Code Workshop (DL4C) at Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS), 2025
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Quokka: Accelerating Program Verification with LLMs via Invariant Synthesis
Anjiang Wei, Tarun Suresh, Tianran Sun, Haoze Wu, Ke Wang, Alex Aiken
In Submission
pdf

Two-Step Offline Preference-Based Reinforcement Learning with Constrained Actions
Yinglun Xu, Tarun Suresh, Rohan Gumaste, David Zhu, Ruirui Li, Zhengyang Wang, Haoming Jiang, Xianfeng Tang, Qingyu Yin, Monica Xiao Cheng, Qi Zheng, Chao Zhang, Gagandeep Singh
Transactions on Machine Learning Research (TMLR), 2025
pdf

Learning a Pessimistic Reward Model in RLHF
Yinglun Xu*, Hangoo Kang*, Tarun Suresh, Yuxuan Wan, Gagandeep Singh
Aligning Reinforcement Learning Experimentalists and Theorists (ARLET) Workshop at Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS), 2025
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Is Watermarking LLM Generated Code Robust?
Tarun Suresh, Shubham Ugare, Gagandeep Singh, Sasa Misailovic
Tiny Papers Track at Proceedings of the 12th International Conference on Learning Representations (ICLR), 2024 (Oral Presentation)
pdf| code