Large crowds, especially at sporting events and mega-concerts, pose huge risks to event organizers and safety personnel. My research focuses on detection of dangerous and abnormal crowd behavior using computer vision techniques. I also have conducted research in the area of face recognition, including the study of identical twins and hierarchical structure of facial features (gender, ethnicity, and race).

Previously to joining Middlebury, I conducted my graduate work in the Computer Vision Research Lab at the University of Notre Dame and earned my Bachelor's degree from the University of Maryland, Baltimore County (UMBC). Outside of work, I enjoy both indoor and outdoor recreation, such as running, biking, playing basketball, and weightlifting. I like to cook some, but I enjoy eating more! When I am not doing any of the other aforementioned things, I am likely at the piano, working on something gospel, classical, jazz, or pop.

I study quantum computers, which take advantage of the laws governing small physical systems in order to solve computational problems. I design algorithms for quantum computers and try to prove that their performance is better than comparable algorithms on standard computers. I also create efficient and accurate ways of characterizing errors in experimental quantum computers.

I did my thesis work at MIT, postdoctoral research at the University of Maryland, and my undergrad studies at Williams College. I also like to cook (especially Korean food - I make a mean kimchi), play the accordion, and do things outdoors, like hiking, biking, and x-country skiing.