Jonathan Ullman
Research Interests
- Privacy
- Machine learning and statistics
- Cryptography
- Algorithms
Education
- PhD in Computer Science, Harvard University
- BSE in Computer Science, Princeton University
Biography
Jonathan Ullman is an associate professor at the Khoury College of Computer Sciences at Northeastern University. Ullman received his doctorate in computer science from Harvard University and his bachelor’s in computer science from Princeton University. His area of teaching includes algorithms and privacy for machine learning, and he is a member of the Theory Group, the Cybersecurity and Privacy Institute, and the Institute for Experiential AI.
Ullman’s research centers on the foundations of privacy for machine learning and statistics, in particular differential privacy and its surprising interplay with other topics in such as statistical validity, robustness, cryptography, and fairness. His background is in theoretical computer science, but increasingly his work spans algorithms, cryptography, machine learning, statistics, and security. Ullman has been recognized with an NSF CAREER award and the Ruth and Joel Spira Outstanding Teacher Award.
Research Interests
- Privacy
- Machine learning and statistics
- Cryptography
- Algorithms
Education
- PhD in Computer Science, Harvard University
- BSE in Computer Science, Princeton University
Biography
Jonathan Ullman is an associate professor at the Khoury College of Computer Sciences at Northeastern University. Ullman received his doctorate in computer science from Harvard University and his bachelor’s in computer science from Princeton University. His area of teaching includes algorithms and privacy for machine learning, and he is a member of the Theory Group, the Cybersecurity and Privacy Institute, and the Institute for Experiential AI.
Ullman’s research centers on the foundations of privacy for machine learning and statistics, in particular differential privacy and its surprising interplay with other topics in such as statistical validity, robustness, cryptography, and fairness. His background is in theoretical computer science, but increasingly his work spans algorithms, cryptography, machine learning, statistics, and security. Ullman has been recognized with an NSF CAREER award and the Ruth and Joel Spira Outstanding Teacher Award.