About

Arnav is an IIT Delhi Computer Science Dual Degree student with a drive to apply his skills to real-world problems. He’s proficient in machine learning, data analysis, and algorithm design, always seeking ways to use technology to streamline operations and gain insights. Outside of his studies, Arnav fuels his adventurous spirit by embarking on exciting trips and exploring new culinary experiences. He’s an avid learner, always seeking out new challenges and opportunities for collaboration.

Across research internships at Harvard University (Edge Computing Lab) and Georgia Tech (FSI Lab), Arnav has worked on large language model evaluation, retrieval augmented generation, and generative AI for hardware design. He co-authored a submission to NeurIPS 2025 (Datasets & Benchmarks track) on multi-hop knowledge graph question generation, and continues to explore reinforcement learning and systems optimization for scalable ML. Ranked All India 1158 in JEE Advanced (top 0.5%) and a KVPY SX Fellow, Arnav maintains an active Google Scholar profile highlighting emerging work at the intersection of AI systems, information retrieval, and evaluation reliability. His academic path at IIT Delhi integrates computer architecture, operating systems, and NLP—grounding pragmatic ML research in strong systems fundamentals.

If you searched for terms like “Arnav Raj IIT Delhi”, “Arnav Raj Harvard”, “Arnav Raj NeurIPS”, or “Arnav Raj Google Scholar”—this page consolidates those identities: the same person, focused on trustworthy AI evaluation, scalable retrieval pipelines, and measurable reasoning quality.

Education

  • Indian Institute of Technology Delhi

    B.Tech and M.Tech in Computer Science & Engineering, 2022-2027

  • Mess Secretary, BHM

    Leadership & Operations, Jun 2024–2025

  • Senior Editor, TechAmbit (Pan-IIT Magazine)

    Editorial & Tech Strategy, 2023–Present

FAQ

What research areas is Arnav Raj focusing on? LLM evaluation (reasoning reliability, retrieval grounding), retrieval augmented generation, reinforcement learning exploration, and systems for ML (performance & observability).
Has Arnav Raj published or submitted work to NeurIPS? He is a co-author on a NeurIPS 2025 Datasets & Benchmarks track submission (KG-QAGen) focused on structured multi-hop question generation and long-context evaluation.
What is Arnav Raj's academic background at IIT Delhi? Dual Degree (B.Tech + M.Tech) in Computer Science & Engineering with interests spanning computer architecture, operating systems, and ML systems reliability.
How can I find Arnav Raj on Google Scholar? Visit the Google Scholar link in the social icons above or search for "Arnav Raj Google Scholar"—his profile lists ongoing preprints and submissions.
What competitive achievements does he have (JEE Advanced rank, fellowships)? JEE Advanced AIR 1158 (top 0.5%), KVPY SX Fellowship, multiple national olympiad stage performances, and Codeforces Expert rating.