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
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
pdf
CRANE
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
BEAVER: An Efficient Deterministic LLM Verifier
Tarun Suresh*, Nalin Wadhwa*, Debangshu Banerjee, Gagandeep Singh
VerifAI Workshop at Proceedings of the 14th International Conference on Learning Representations (ICLR), 2026 (Oral Presentation)
pdf
CoRNStack
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
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
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
InvBench
Quokka: Accelerating Program Verification with LLMs via Invariant Synthesis
Anjiang Wei, Tarun Suresh, Tianran Sun, Haoze Wu, Ke Wang, Alex Aiken
VerifAI Workshop at Proceedings of the 14th International Conference on Learning Representations (ICLR), 2026 (Oral Presentation)
pdf
Pessimistic Reward Model
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
pdf
LLM Code Watermarking
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