I am a PhD student at CSE@IIT Bombay, jointly advised by Abir De and Soumen Chakrabarti.
I design machine learning methods for predictive challenges on graphs, with a focus on neural graph retrieval. This currently involves developing deep learning models for solving graph combinatorial problems, scalable retrieval methods with trainable hashing, and ensuring interpretability through explicit alignment-driven justifications. These techniques are applicable to multimodal retrieval involving graphs from diverse domains, such as knowledge graphs, scene graphs, social networks, and molecular graphs.
My doctoral research is supported by the Prime Minister's Research Fellowship (2022-24), the Qualcomm Innovation Fellowship (2022-24), the Google PhD Fellowship (2024-25), and the Microsoft Research India PhD Award (2025).

News
- One paper accepted at NeurIPS 2025
- Co-organizing Workshop on Differentiable Learning of Combinatorial Algorithms (DiffCoALG@NeurIPS 2025)
- Visiting Research Assistant with Vikas Garg at QuML Lab@Aalto University
- Updated Research Statement (Jun 2025); Previous Research Statement (May 2024)
- Serving as a reviewer for NeurIPS 2025, ICLR 2026.
- Awarded the Microsoft Research India PhD Award (2025)
- ICML 2025 position paper on data leakage in graph matching benchmarks (with proposals for mitigation)