Class-wise rationalization: teaching AI to weigh pros and cons
Shiyu Chang
Research Staff Member

Who they work with
Shiyu Chang is a research scientist at the MIT-IBM Watson AI Lab and an associate professor of computer science at UC Santa Barbara. His research focuses on machine learning and its applications in natural language processing and computer vision. Most recently, he has been investigating how machine predictions can be made more interpretable to humans, and how human intuition and rationalization can improve AI transferability, data efficiency, and adversarial robustness. Prior to his current position, Chang was a research scientist at the IBM T.J. Watson Research Center. He got his BS and PhD from the University of Illinois at Urbana-Champaign; his PhD advisor was Thomas S. Huang.
Publications with the MIT-IBM Watson AI Lab