Associate Professor, Electrical Engineering and Computer Science (EECS)
Tamara Broderick is an associate professor in MIT’s Department of Electrical Engineering and Computer Science. She is also an investigator at the Institute for Data, Systems, and Society and the Computer Science and Artificial Intelligence Laboratory. She works in machine learning and statistics, and is focused on understanding how we can reliably quantify uncertainty and robustness in modern, complex data analysis procedures. She is particularly interested in Bayesian statistics and graphical models — with an emphasis on scalable, nonparametric, and unsupervised learning.
- Stephenson, W and Broderick, T. (2020) Approximate Cross-Validation in High Dimensions with Guarantees. International Conference on Artificial Intelligence and Statistics (AISTATS).
- Agrawal, R, Huggins, JH, Trippe, B, and Broderick, T. (2019).
The Kernel interaction trick: Fast Bayesian discovery of pairwise interactions in high dimensions. International Conference on Machine Learning (ICML).
- Trippe, B, Huggins, JH, Agrawal, R, and Broderick, T. (2019). LR-GLM: High-dimensional Bayesian inference using low-rank data approximations. International Conference on Machine Learning (ICML).
- Campbell, T and Broderick, T. (2019) Automated scalable Bayesian inference via Hilbert coresets. Journal of Machine Learning Research.
- Jan. 29, 2020: MIT News, At halfway point, SuperUROP scholars share their research results.
- March 21, 2018: IDSS News, Tamara Broderick receives 2018 NSF CAREER Award.
- Jan. 23, 2018: EECS News, Tamara Broderick receives prestigious Army Research Office award.
- June 23, 2016: IDSS News, Tamara Broderick doubly awarded at ISBA 2016 World Meeting.