Andrea Bajcsy is an Assistant Professor in the Robotics Institute at Carnegie Mellon University where she leads the Interactive and Trustworthy Robotics Lab (Intent Lab).
Her research develops theoretical frameworks and practical algorithms for safe human-robot interaction, and draws upon methods from optimal control, dynamic game theory, Bayesian inference, and deep learning.
She grounds her work through a variety of applications, such as assistive robotic arms, quadrotors, quadrupedal robots, and autonomous cars, and in experiments with real human participants.
Andrea received her Ph.D. in Electrical Engineering & Computer Science from UC Berkeley and B.S. in Computer Science at the University of Maryland, College Park.
Her research has been featured in NBC news, WIRED magazine, and the Robohub podcast.
She is the recipient of an Honorable Mention for the T-RO Best Paper Award, the NSF Graduate Research Fellowship, UC Berkeley Chancellor’s Fellowship, and has worked at NVIDIA Research and Max Planck Institute for Intelligent Systems.