Jonathan Ullman is a theoretical computer scientist. The focus of his research is how to make data analysis more reliable and better aligned with societal values. A particular focus is statistical data privacy, which studies how and when we can analyze a dataset without revealing information about the individuals in that dataset. He is also interested in how to prevent false discovery in the empirical sciences. He studies these and other questions using tools from cryptography, algorithms, machine learning, and statistics.

His research has been recognized with an NSF CAREER Award and a Google Faculty Research Award.