Marzyeh Ghassemi
The Germeshausen Career Development Professor and Associate Professor, Department of Electrical Engineering and Computer Science, and Institute for Medical Engineering & Science
Who they work with
Categories
Marzyeh Ghassemi is the Germeshausen Career Development Professor and an associate professor, with appointments in the Department of Electrical Engineering and Computer Science and the Institute for Medical Engineering & Science at MIT. Ghassemi’s research interests span representation learning, behavioral ML, healthcare ML, and healthy ML. One of her focuses is on real-world applications of machine learning, such as turning diverse clinical data into cohesive information with the ability to predict patient needs. Ghassemi has received BS degrees in computer science and electrical engineering from New Mexico State University, an MSc degree in biomedical engineering from Oxford University, and PhD in computer science from MIT.
Publications
- Zhu, J., Greenewald, K., Nadjahi, K., Saez de Ocariz Borde, H., Gabrielsson, R. B., Choshen, L., Ghassemi, M., Yurochkin, M., & Solomon, J. (2024). Asymmetry in low-rank adapters of foundation models. In Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria. PMLR 235.
- Yang, Y., Zhang, H., Katabi, D., & Ghassemi, M. (2023). Change is hard: A closer look at subpopulation shift. In Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202.
- Adam, H., Yang, M. Y., Cato, K., Baldini, I., Senteio, C., Celi, L. A., Zeng, J., Singh, M., & Ghassemi, M. (2022). Write it like you see it: Detectable differences in clinical notes by race lead to differential model recommendations. In AIES ’22: Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (pp. 7-21).
Media
- August 17, 2023: MIT News, How machine-learning models can amplify inequities in medical diagnosis and treatment
- June 1, 2021: MIT News, The potential of artificial intelligence to bring equity in health care.
- October 2, 2020: MIT Technology Review, How an AI tool for fighting hospital deaths actually worked in the real world