Assistant Professor, Department of Electrical Engineering and Computer Science
Pulkit Agrawal is an assistant professor in MIT’s Department of Electrical Engineering and Computer Science. 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 Tech 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.
- Li, R., Jabri, A., Darrell, T., Agrawal, P. (2020). Towards Practical Multi-object Manipulation using Relational Reinforcement Learning. (ICRA)
- Cheung, B., Terekhov, A., Chen, Y., Agrawal, P., Olshausen, B. (2019). Superposition of Many Models into One. Thirty-third Conference on Neural Information Processing Systems (NeurIPS).
- Xiong, G. L., Bayen, E., Nickels, S., Subramaniam, R., Agrawal, P., Jacquemot, J., Bayen, A. M., Miller, B., Netscher, G. (2019). Real-time Video Detection of Falls in Dementia Care Facility and Reduced Emergency Care. American Journal of Managed Care.
- Pathak, D., Mahmoudieh, P., Luo, M., Agrawal, P., Shelhamer, E., Efros, A. A., Darrell, T. (2018). Zero Shot Visual Imitation. Sixth International Conference on Learning Representations (ICLR).
- Dubey, R., Agrawal, P., Pathak, D., Efros, A. A., Griffiths, T. (2018). Investigating Human Priors for Playing Video Games. Thirty-fifth International Conference on Machine Learning (ICML).
- 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.