Gregory Wornell

Gregory Wornell is the Sumitomo Electric Industries Professor in Engineering in MIT’s Department of Electrical Engineering and Computer Science. He is also affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Institute for Data, Systems, and Society (IDSS). Wornell heads the Signals, Information, and Algorithms Laboratory within the Research Laboratory of Electronics. His research interests span signal processing, information theory, statistical inference, and information security, and include architectures for sensing, learning, computing, communication, and storage; systems for computational imaging, vision, and perception; and aspects of neuroscience. Wornell earned a BASc from the University of British Columbia, and an SM and PhD from MIT.

Selected Publications

• Shen, M., Sattigeri, P., Ghosh, S., Das, S., Bu, Y., Wornell, G. (2023). Post-hoc Uncertainty Learning using a Dirichlet Meta-Model. Association for the Advancement of Artificial Intelligence (AAAI).
• Wornell, G., Sattigeri, P., Panda, R., Das, S., Bu, Y., Lee, J. K. W., Shah, A. (2022). Selective Regression under Fairness Criteria. International Conference on Machine Learning (ICML).
• Aminian, G., Bu, Y., Toni, L., Rodrigues, M. R. D., Wornell, G. (2021). An Exact Characterization of the Generalization Error for the Gibbs Algorithm. Conference on Neural Information Processing Systems (NeurIPS).
• Lee, J. K. W., Sattigeri, P., Wornell, G. W. (2019). Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks. Conference on Neural Information Processing Systems (NeurIPS).

Media

• Dec. 6, 2019: MIT News, Using computers to view the unseen.
• Oct. 19, 2018: MIT News, School of Engineering third quarter 2018 awards.
• Oct. 9, 2017: MIT News, An algorithm for your blind spot.
• May 5, 2014: MIT News, Terahertz imaging on the cheap.