Vikash Singh

PhD Student at Case Western Reserve University | Machine Learning & AI Researcher

Cleveland, OH, 44106

About

Vikash Singh is a researcher in Artificial Intelligence and a PhD student at Case Western Reserve University. His work advances the reliability of Large Language Models (LLMs) by studying their reasoning behavior, uncertainty, and fairness. He develops practical methods that bridge formal verification and data-driven modeling, including recent work on grammars of formal uncertainty and selective verification signals for automated reasoning tasks. Vikash enjoys tackling challenging problems end-to-end—from idea to robust implementation—and frequently explores adjacent topics like pruning, hyperparameter optimization, and explainable AI.

Key Facts

Name

Vikash Singh

Occupation

PhD Student, Machine Learning & AI Researcher

Date of Birth

May 25

Location(s)

Cleveland, OH 44106 • New York, USA (seasonal)

Contact

vikashjohn2505@gmail.com

Website

vikash-singh.me

Latest Publications

VERGE: Formal Refinement and Guidance Engine for Verifiable LLM Reasoning

Vikash Singh, Darion Cassel, Nathaniel Weir, Nick Feng, Sam Bayless

arXiv, Jan 2026.

arXiv BibTeX

@misc{singh2026vergeformalrefinementguidance,
  title={VERGE: Formal Refinement and Guidance Engine for Verifiable LLM Reasoning},
  author={Vikash Singh and Darion Cassel and Nathaniel Weir and Nick Feng and Sam Bayless},
  year={2026},
  eprint={2601.20055},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2601.20055}
}

Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks

Ganguly, D., Singh, V., Sankar, S., Zhang, B., Zhang, X., Iyengar, S., Han, X., Sharma, A., Kalyanaraman, S., Chaudhary, V.

NeurIPS 2025, May 2025.

arXiv BibTeX

@misc{ganguly2025grammarsformaluncertaintytrust,
      title={Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks}, 
      author={Debargha Ganguly and Vikash Singh and Sreehari Sankar and Biyao Zhang and Xuecen Zhang and Srinivasan Iyengar and Xiaotian Han and Amit Sharma and Shivkumar Kalyanaraman and Vipin Chaudhary},
      year={2025},
      eprint={2505.20047},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2505.20047}, 
}

Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers

Yang Wang, Debargha Ganguly, Xinpeng Li, Chaoda Song, Shouren Wang, Vikash Singh, Vipin Chaudhary, Xiaotian Han

arXiv, Jan 2026.

arXiv BibTeX

@misc{wang2026midthink,
  title={Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers},
  author={Yang Wang and Debargha Ganguly and Xinpeng Li and Chaoda Song and Shouren Wang and Vikash Singh and Vipin Chaudhary and Xiaotian Han},
  year={2026},
  eprint={2601.07036},
  archivePrefix={arXiv},
  url={https://arxiv.org/abs/2601.07036}
}

View All Publications

News & Updates

September 2025 Paper accepted to NeurIPS'25 (Grammars of Formal Uncertainty: When to Trust LLMs).
September 2025 Two papers accepted to HiPC'25.
July 2025 Got accepted to Amazon Applied Science Internship at New York.
May 2025 Research Assistant At CWRU CSDS Department
Jan 2025-May 2025 Teaching Assistant for Data Mining Course.
Aug 2024-December 2024 Teaching Assistant for Computer Security Course at CWRU.
Aug 2024-Present Started PhD in Computer Science at Case Western Reserve University.
May 2024 Summer Internship at MGenio Inc.
Jan 2024 - May 2024 Teaching Assistant for Computational Perception and Compiler Design Courses at CWRU.
Aug 2023 - Dec 2023 Started Masters in Computer Science at Case Western Reserve University.
May 2023 Completed B.Tech in Civil Engineering at Indian Institute of Technology, Mandi
Jan 2022-Sep 2022Internship at DRDO
May 2021 - Aug 2021 Internship at Indian Institute of Technology, Mandi
Aug 2019- May 2023 B.Tech in Civil Engineering at Indian Institute of Technology, Mandi

Research Interests

Formal Reasoning and Verification of LLMs
Fine-Tuning LLMs and Vision Models (LoRA)
Redundancy Mitigation in LLMs
Model Optimization (Pruning, Hyperparameter Tuning)
Explainable AI (XAI)