Jordan Awan

I am an Assistant Professor of Statistics at University of Pittsburgh. Before joining Pitt, I was an Assistant Professor at Purdue University for 5 years. I completed his PhD in Statistics from Penn State in 2020 under the advisement of Aleksandra Slavkovic and Matthew Reimherr. My primary research interest is in data privacy, where the goal is to publish meaningful statistical results on sensitive datasets, without compromising the privacy of the participants in the dataset. In particular, I mostly work in the framework of differential privacy, which has been adopted by a number of tech companies as well as the US Census. Some data privacy problems that I am particularly interested in are 1) performing valid statistical inference subject to privacy constraints (e.g., confidence intervals, hypothesis tests, posterior inference), 2) designing privacy-aware algorithms for a variety of tasks (e.g., functional data analysis, topological data analysis), and 3) foundations of data privacy (e.g., definitions of privacy, optimizing basic privacy mechanisms). I also work with a variety of scientists as an applied Statistician on problems related to diagnosing and treating voice disorders, and developing novel methods of low-cost spirometry. Before transitioning to Statistics, I worked on discrete mathematics problems in graph theory, matroid theory, and discrete geometries.

Courses

• Pitt: Special Topics in Differential Privacy (Fall 2025)
• Purdue: Undergraduate Statistical Theory, Undergraduate Introduction to Data Science, Graduate Probability, Special Topics in Differential Privacy, Graduate Research Seminar
• Penn State: Introduction to Probability and Statistics for Engineers
• Brandeis University: Integral Calculus