Pulkit Agrawal
Associate Professor, Department of Electrical Engineering and Computer Science

Who they work with
Pulkit Agrawal is an associate professor in MIT’s Department of Electrical Engineering and Computer Science (EECS), the Computer Science and Artificial Intelligence Laboratory (CSAIL) and an affiliate member of the Laboratory for Information and Decision Systems (LIDS). His research interests span robotics, deep learning, computer vision and reinforcement learning. Agrawal’s overarching goal is to build machines that can automatically and continuously learn about their environment to reach what humans consider common sense. Agrawal earned his BS from IIT Kanpur and was awarded the Director’s Gold Medal. He earned his PhD from UC Berkeley and co-founded SafelyYou Inc. His work has appeared in MIT Technology Review, Quanta, and New Scientist. He is a recipient of Sony Faculty Research Award, Signatures Fellow Award, Fulbright Science and Technology Award, Goldman Sachs Global Leadership Award, OPJEMS and Sridhar Memorial Prize, among others. Agrawal holds the equivalent of a BA in Indian classical music and occasionally performs.
Selected Publications
- Torne, M., Balsells, M., Wang, Z., Desai, S., Chen, T., Agrawal, P. & Gupta, A. (2023). Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback. Proceedings of the Conference on Neural Information Processing Systems (NeurIPS).
- Agrawal, P., Srivastava, A., Hong, Z., Kumar, A., Karnik, S., Bhandwaldar, A., Pajarinen, J., Laroche, R. & Gupta, A. (2023). Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets. Proceedings of the Conference on Neural Information Processing Systems (NeurIPS).
- Ajay, A., Han, S., Du, Y., Li, S., Gupta, A., Jaakkola, T., Tenenbaum, J., Kaelbling, L., Srivastava, A. & Agrawal, P. (2023). Compositional Foundation Models for Hierarchical Planning. Proceedings of the Conference on Neural Information Processing Systems (NeurIPS).
Media
- January 9, 2019: MIT News, School of Engineering welcomes new faculty.
- September 19, 2017: Quanta magazine, Clever machines learn how to be curious.
- May 23, 2017: MIT Technology Review, Curiosity may be vital for truly smart AI.