rishabh ranjan

resume | scholar | github | email

I am a first-year PhD student in Computer Science at Stanford University, where I have worked with Profs. Jure Leskovec and Carlos Guestrin so far. Before this, I spent a lovely year learning under Prof. Zachary Lipton as a visiting researcher at Carnegie Mellon University. I did my undergrad in CS at IIT Delhi, where I was the President's Gold Medalist for the class of 2022.

I am interested in deep learning research, with a recent focus on foundation models. In my past work, I have enjoyed forays into noisy data learning, graph ML, neuro-symbolic AI, and program analysis.

news

pre-prints

1. 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
   paper | arxiv | code | website | cite

publications

1. A Solver-Free Framework for Scalable Learning in Neural ILP Architectures
   Yatin Nandwani*, Rishabh Ranjan*, Mausam, Parag Singla
   Advances in Neural Information Processing Systems (NeurIPS), 2022
   paper | arxiv | reviews | poster | slides | code | cite
2. GREED: A Neural Framework for Learning Graph Distance Functions
   Rishabh Ranjan, Siddharth Grover, Sourav Medya, Venkatesan Chakaravarthy, Yogish Sabharwal, Sayan Ranu
   Advances in Neural Information Processing Systems (NeurIPS), 2022
   paper | arxiv | reviews | poster | slides | code | cite
3. Exploiting Epochs and Symmetries in Analysing MPI Programs
   Rishabh Ranjan, Ishita Agrawal, Subodh Sharma
   IEEE/ACM International Conference on Automated Software Engineering (ASE), 2022
   paper | code | talk | cite