I am an incoming PhD student in Computer Science at Stanford University. I spent a lovely last year learning from Prof. Zachary Lipton as a visiting researcher at Carnegie Mellon University. Before that, I was an undergrad at IIT Delhi where I was fortunate to work with Profs. Mausam, Parag Singla, Sayan Ranu, and Subodh Sharma. I research deep learning, seeking to help it develop into a mature science and engineering discipline. In my past work, I have enjoyed forays into learning from noisy data, neuro-symbolic AI, graph ML and program analysis.
started my PhD at Stanford
this webpage is live
(* denotes equal contribution)
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
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
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