CS Graduate Student

Welcome to Gaurav’s Homepage!


Note: This webpage was last updated on 05/02/2025.

About me

Hi folks, welcome to my personal homepage! I’m a first-year MS (thesis) student in Computer Science at Virginia Tech, and fortunately advised by Dr. Xuan Wang. I am also affiliated with the Sanghani Center for Artificial Intelligence and Data Analytics.

Prior to joining Virginia Tech, I got my Bachelor’s degree in Computer Science from Manipal University Jaipur in July 2023. During my Bachelor’s program, I was fortunate to be supervised by Dr. Nitesh Pradhan and worked with Dr. Vijaypal Singh Dhaka and Dr. Mahesh Jangid. I was also the President’s Gold Medalist for Excellence in Research. After that I worked at Dell Technologies for 1 year as a Machine Learning Engineer. Before that, I spent 6 months at Swiggy’s Applied Research (Computer Vision) team.

Research  Interests

I work on improving small language models in reasoning—pushing lightweight LMs to think deeper, act smarter, and collaborate like expert teams. My research spans natural‑language processing, complex reasoning, and model efficiency, all aimed at creating efficient, low‑cost AI systems. My current focus areas include:

  1. Complex Reasoning in Small Language Models:
    How far can carefully designed prompting, multi-agent debate, and iterative fine‑tuning push models with only a few billion parameters? I study emergent reasoning, chain‑of‑thought, and which facets of reasoning are kept or lost after compression—revealing when  and  why small models succeed or fail.

  2. Multi‑Agent Debate & Self‑Evolution:
    I design systems where multiple LMs critique, refine, and distill each other’s outputs. Iteratively fine‑tuning the resulting “debate traces” lets a single model self‑evolve without human‑labeled data.

  3. Overthinking in Basic Reasoning:
    Do language models waste cognitive cycles on problems that humans solve almost reflexively? I also study when language models overthink problems that humans solve instinctively. I developed LLMThinkBench, a framework that measures when—and why—LLMs overthink straightforward math and logical reasoning tasks.

News

  • [Apr. 22, 2025] Released the SLM Reasoning Leaderboard!
  • [Apr. 5, 2025] Released the LLMThinkBench framework for evaluating basic‑math reasoning and over‑thinking in language models—install it with pip install llmthinkbench!
  • [Feb. 17, 2025] New preprint on the reasoning abilities of small language models.
  • [Oct. 9, 2024] Accepted a Summer 2025 internship offer at Dell Technologies as an AI Research Intern in the Global Office of the CTO (Round Rock, TX)!
  • [Sep. 4, 2024] Joined Wang’s Group to work on reasoning, small language models, and large language models!
  • [Aug. 6, 2024] Began my M.S. in Computer Science at Virginia Tech!

Honors and Awards

  • 🥇 President’s Gold Medal for Excellence in Research, Manipal University Jaipur (2023)
  • 🥈 Runner-up, Dell IT Development Program (ITDP) FY’23 Hackathon, Dell Technologies (2023)
  • 🪙 Ranked 13/473 globally in Bitgrit Generative AI Competition, Bitgrit (2023)
  • 🪙 117/26,008, Amazon ML Challenge 2023, Amazon (2023)
  • 🥇 Three-time recipient of the Student Excellence Award for publishing research, MUJ (2022 - 2023)
  • 🥇 Best Research Project, Computer Science Department, Manipal University Jaipur (2022)
  • 🥉 All India Grand Finalist, Precision Health Challenge 2021-22 Hackathon, Wipro GE Healthcare (2022)
  • 🥉 All India Grand Finalist, India Automobile Hackathon, NEC and Mitsubishi (2022)
  • 🥉 All India Grand Finalist, HACKBATTLE: Impact Through Data Hackathon, T-Systems (2022)
  • 🥉 3rd Position, “Hack2Hire” Hackathon, Dell Technologies (2021)
  • 🥇 Best Senior Hack, NPSiHacks, Devfolio (2021)
  • 🪙 Kaggle 3X Expert (Top 20% in Competitions, Top 1% in Titanic, Digit Recognizer) (2020 - 2023)