About

Kimia Hassibi is a second-year Ph.D. student in Electrical Engineering and Computer Science at MIT, where she is advised by Professors Asuman Ozdaglar and Pablo Parrilo. Her research focuses on using machine learning for optimization. She is particularly interested in how a diffusion model that is pre-trained on a data distribution can be used to optimize functions over that distribution, and in understanding what algorithms emerge when graph neural networks are trained to solve specific classes of linear programs. Before coming to MIT, Kimia earned a B.S. in Computer Science from Caltech, where she conducted research in machine learning, game theory, and network science.

Education

MIT

Ph.D. , Computer Science

Class of 2026

Awards & Publications