I received my Ph.D in Statistics and Operations Research under the advisement of Professors Shankar Bhamidi and Andrew Nobel at the University of North Carolina at Chapel Hill in 2015. I am now an Assistant Professor of Statistics at the University of San Francisco (USF), where I am part of the Department of Mathematics and Statistics, the Master of Data Science program, Co-Director of the Data Science Program and Associate Director of Research at the Data Institute.
My research focuses on the development, analysis and application of computational methods for complex network data. My work relies on applying statistical principles from random graph theory to enable inference on various families of networks, including multilayer, dynamic and weighted networks. I work on network problems in a variety of application areas, including functional brain imaging, political voting trends, and labor market competition. I also work closely with companies in the Bay Area to solve exciting data science and network analysis problems. This year I am excited to be working with analytics members at the Houston Astros, Xoom, Zipcar, and Bracket Voodoo.
- Network Inference via the Generalized Exponential Random Graph Model. ISBIS 2018, University of Piraeus, Greece. July 4th - 6th, 2018.
- The Power of A/B Testing under Social Interference. Indeed, Inc. July 12th, 2018.
Videos of Past Presentations
- <Community Detection in Multilayer Networks with Heterogeneous Community Structure>, Network Science Institute at Northeastern University. February, 2018