I am a third-year PhD student in Computer Science at Stanford University,
co-advised by Prof. Jure Leskovec
and Prof. Carlos Guestrin.
Before this,
I spent a lovely year learning under
Prof. Zachary Lipton
as a visiting researcher at Carnegie Mellon University (CMU).
I did my undergrad in CS at IIT Delhi,
where I was the President's Gold Medalist for the class of 2022.
I am a machine learning (ML) researcher.
My current focus is relational foundation models (RFMs):
large-scale pretrained models that can understand and reason about relational data
— which subsumes tabular, time-series and graph data —
to solve complex decision-making, forecasting and recommendation challenges
(e.g., see this).
In my free time,
I like to swim, watch movies, and
read.
publications
(* denotes equal contribution)
PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models
Vignesh Kothapalli, Rishabh Ranjan, Valter Hudovernik, Vijay Prakash Dwivedi, Johannes Hoffart,
Carlos Guestrin, Jure Leskovec Under review (2026) paper
| code
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RelBench v2: A Large-Scale Benchmark and Repository for Relational Data
Justin Gu, Rishabh Ranjan, Charilaos Kanatsoulis, Haiming Tang, Martin Jurkovic, Valter Hudovernik, Mark Znidar,
Pranshu Chaturvedi, Parth Shroff, Fengyu Li, Jure Leskovec Under review (2026) paper
| code
| website
Relational Transformer: Toward Zero-Shot Foundation Models for Relational Data Rishabh Ranjan, Valter Hudovernik, Mark Znidar, Charilaos Kanatsoulis, Roshan Upendra, Mahmoud Mohammadi, Joe Meyer, Tom Palczewski, Carlos Guestrin, Jure Leskovec ICLR 2026 [Oral]AI for Tabular Data (AI4TD) Workshop, NeurIPS 2025 (early version) paper
| arxiv
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| cite
RelBench: A Benchmark for Deep Learning on Relational Databases Rishabh Ranjan*, Joshua Robinson*, Weihua Hu*, Kexin Huang*, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan E. Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec NeurIPS 2024 paper
| arxiv
| code
| website
| cite
Post-Hoc Reversal: Are We Selecting Models Prematurely? Rishabh Ranjan, Saurabh Garg, Mrigank Raman, Carlos Guestrin, Zachary Lipton NeurIPS 2024 paper
| arxiv
| code
| cite
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
Matthias Fey*, Weihua Hu*, Kexin Huang*, Jan Eric Lenssen*, Rishabh Ranjan*, Joshua Robinson*, Rex Ying, Jiaxuan You, Jure Leskovec ICML 2024 paper
| arxiv
| code
| website
| cite
A Solver-Free Framework for Scalable Learning in Neural ILP Architectures
Yatin Nandwani*, Rishabh Ranjan*, Mausam, Parag Singla NeurIPS 2022 paper
| arxiv
| reviews
| poster
| slides
| code
| cite
