I’m Shuangge Wang, a Ph.D. candidate in Computer Science at Yale University, advised by Tesca Fitzgerald and Brian Scassellati. My research sits at the intersection of robotics, artificial intelligence, and human-robot interaction. I study how people teach robots through feedback and how robots can adapt their learning to become more interpretable, efficient, and pereceptive. My recent work focuses on learning from physical corrections and shared-control for precise manipulation tasks. Before Yale, I earned bachelor’s degrees in Electrical and Computer Engineering and Applied and Computational Mathematics from the University of Southern California. I also spent a summer conducting research at the Robotics Institute at Carnegie Mellon University.
Search for Shuangge Wang's papers on the Research page