About me

I am an Associate Professor with tenure at MIT. I work in the areas of machine learning and statistics. Before coming to MIT, I completed my PhD at UC Berkeley. You can learn more about my background in the following (plaintext) short bio.

In my research, I am interested in understanding how we can quickly, easily, and reliably quantify uncertainty and robustness in modern data analysis procedures.

Current PhD Students and Postdocs

• Madelyn Andersen
• Renato Berlinghieri
• David Burt
• Jenny Y. Huang
• Yunyi Shen
• Eric Weine

Past PhD Students and Postdocs

• Raj Agrawal, Research Scientist, Basis Research Institute
• Trevor Campbell, Associate Professor, University of British Columbia
• Sameer Deshpande, Assistant Professor, University of Wisconsin–Madison
• Sam Elder, Machine Learning Scientist, Kebotix
• Ryan Giordano, Assistant Professor, UC Berkeley
• Jonathan Huggins, Assistant Professor, Boston University
• Mikołaj Kasprzak, Marie Skłodowska-Curie (Global) Fellow (starting as Assistant Professor at ESSEC Business School in fall 2024)
• Lorenzo Masoero, Applied Research Scientist, Amazon
• Yaroslav Mukhin, Postdoctoral Researcher, IDSS
• Tin Danh Nguyen, Quantitative Researcher, Quantbot Technologies LP
• Miriam Shiffman, Senior Scientist in Data & Machine Learning, biotech startup
• William Stephenson, Member of Technical Staff, MIT Lincoln Labs
• Brian Trippe, Postdoctoral Fellow, Columbia University (starting as Assistant Professor at Stanford in fall 2024)

Interested in working with me?

• To apply to work with me as a PhD student, submit your application to MIT EECS; more info at this link. I can also advise PhD students accepted to other appropriate programs at MIT; e.g., I have advised PhDs in Math and CSB.
• To apply to work with me as a postdoc, email me your CV (pdf), a statement of research interests, a pdf of 1 (or 2) of your most significant publications, and the contact details (including email addresses) of two references.

Affiliations

• Electrical Engineering and Computer Science (EECS) Department
• Laboratory for Information and Decision Systems (LIDS)
• Statistics and Data Science Center
• Institute for Data, Systems, and Society (IDSS)
• MachineLearning@MIT
• MIT Institute for Foundations of Data Science (MIFODS)

Accessibility
Plain Academic