
About Me
My research centers on the foundations of privacy for machine learning and statistics, in particular differential privacy and its surprising interplay with other topics such as statistical validity, robustness, cryptography, and fairness. My background is in theoretical computer science, but increasingly my work spans machine learning, statistics, cryptography, and cybersecurity. My research and teaching have been recognized with an NSF CAREER award and the Ruth and Joel Spira Outstanding Teaching Award.
I am a member of the Boston-Area Data Privacy Group and I also co-organize the Workshop on Theory and Practice of Differential Privacy, and differentialprivacy.org.
At Northeastern, I am a member of the Theory Group, the Cryptography and Privacy Group and the Cybersecurity & Privacy Institute. I am also an affiliate member of the Institute for Experiential AI.
Current Events
- 02-06-2023 New paper on the connection between differential privacy and robust statistics.
- 02-01-2023 New paper on bias and variance in statistical estimation.
- 10-31-2022 New paper on instance-optimal private estimation.
- 08-24-2022 New website design courtesy of my bio/academic niece Kira Goldner!
- 08-03-2022 Excited to be back at Northeastern after my sabbatical!
- 06-19-2022 Welcome to the family, Ezra Rainer Ullman! Ezra and Miriam are already conspiring against me.
Students
I'm fortunate to work with an amazing group of students and postdocs. Currently I work with:
- Maryam Aliakbarpour (Postdoc)
- Lydia Zakynthinou (PhD Student)
- Konstantina Bairaktari (PhD Student)
- John Abascal (PhD Student)
- Rose Silver (PhD Student)
- Sushant Agarwal (PhD Student)
- Stanley Wu (Undergraduate)