PhantomGrad

Advancing AI through rigorous research, responsible deployment, and real-world impact.

PhantomGrad is an AI research group at BITS Pilani, led by Professor Dhruv Kumar, a leading AI scientist, professor, and consultant in India. We work at the intersection of large language models, intelligent systems, and real-world applications — spanning foundational research on LLM evaluation, interpretability, and training, and applied projects in education, software engineering, environmental science, and beyond. We partner with industry, government agencies, and NGOs to translate research into impact.

Prof. Dhruv Kumar
Prof. Dhruv Kumar
Director, PhantomGrad
Asst. Professor, BITS Pilani
55+
Publications
4
Funded Projects
₹87.5L+
Research Funding
15+
Collaborators
3
Industry Partners

What We Work On

AI Agents & LLMs

Evaluation, benchmarking, and applications of large language models in real-world settings.

AI for Education

Intelligent tutoring, automated assessment, and understanding LLM impact on learning.

AI for Software Engineering

Code generation, test synthesis, type inference, and formal verification with LLMs.

Mechanistic Interpretability

Understanding internal representations and circuits within transformer models.

Multi-Modal Foundation Models

Vision, time series, and tabular foundation models and their adaptation.

RL & LLM Training

Policy optimization, fine-tuning strategies, and hybrid learning frameworks.

View all research →

News

Mar 2026 Roamify accepted at The Web Conference (WWW 2026) — LLM-based personalised itinerary planning extension. Paper ↗
Jan 2026 Sakshm AI accepted at ACM Journal on Computing and Sustainable Societies (JCSS 2026) — Socratic AI tutor for coding education in India. Paper ↗
Nov 2025 Loop Invariant Generation wins Best Paper Award at AIWare 2025. Paper ↗
Oct 2025 Two papers accepted at EMNLP 2025 — Pedagogical LLM Agents (main) and ReviewEval (findings). View →
Nov 2024 ₹20L grant awarded by BITS Pilani for "Revolutionizing Indian HEIs with Generative AI." Details →
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