Jonathan Ullman is broadly interested in theoretical computer science. Much of his work addresses questions regarding when and how to analyze a dataset while ensuring privacy for individuals in the dataset, and how to prevent false discovery in the empirical sciences. Jonathan studies these questions and others using tools from cryptography, computational learning theory, algorithms, and game theory.
Since Fall 2015, Jonathan has been an assistant professor in the College of Computer and Information Sciences at Northeastern University, where he is affiliated with Northeastern's Theory Group and the Cybersecurity and Privacy Institute. Jonathan is also a senior researcher on the Harvard University Privacy Tools Project. Jonathan's work has been recognized with a NSF CAREER Award and a Google Faculty Research Award.
- Data Privacy: Foundations and Applications, Spring 2019. Visiting Scientist and Workshop Organizer.