Ph.D., Physics, University of Maryland, College Park
B.S., Physics (Magna Cum Laude with High Honors), University of Maryland, College Park
Burghardt is a Computer Scientist at the USC Information Sciences Institute who specializes in understanding biases in human behavior with physics-inspired models, and correcting these biases for fairer automated decisions. His recent research also spans network science, including how cascades spread on networks as well as how road networks and collaborations grow. Burghardt was PI for several accepted grants, including a USC + Amazon Center on Secure and Trusted Machine Learning grant and ISI Research grant in 2021, and co-PI for an accepted $1.0M DARPA grant in 2019. In addition, he received a 2016 ISI Director’s Intern Award and a 2015 Conference on Complex Systems Starred Paper Award. He co-organizes USC GRIDS Datafest in Fall 2021, and has led the USC ISI AI Seminar Series 2020-21, the Summer School on Sensor-Based Behavioral Machine Learning in 2020. Burghardt is a co-lecturer for DSCI 550 “Data Science at Scale” (Spring 2022), and was a co-lecturer for DSCI 552 “Machine Learning for Data Science” (Spring 2021) and INF 553 “Foundations and Applications of Data Mining” (Fall 2019). He received a Ph.D. and a B.S. (Magna Cum Laude with High Honors in Physics) in Physics at the University of Maryland, College Park (2016 and 2012, respectively).