Robotics Colloquium: Attention in Vision-based AI Systems

This week's speaker, Catherine Zhao, will be giving a talk titled "Attention in Vision-based AI Systems."

Abstract

Imagine that you are at a bus stop in a new city. You take a few glimpses around, parse and summarize the information you gather, and decide the next steps. Although intuitive, it implies a highly sophisticated and superior ability to select and parse information. Our research is along this line to develop and utilize machine attention for AI systems. In this talk, Professor Catherine Zhao will discuss the challenges and share the recent innovations in data, models, and applications from our research.

Zhao will first talk about attention prediction - the ability of machines to find the most relevant information. She will elaborate on our computational models and experimental methods for attention prediction and explain how they have advanced the state-of-the-art. She will then discuss new approaches that leverage attention in computer vision and language tasks, leading to better interpretability and task performance. She will also present preliminary data suggesting that this approach can help reveal and improve the black-box decision-making process of learning-based AI systems. Finally, Zhao will discuss the applications of our models and data in healthcare and will give two examples where our work leads to the discovery of neurobehavioral signature in autism patients, as well as cutting-edge brain-machine interface technology that restores the lost motor function in upper-limb amputee patients.

Biography

Catherine Qi Zhao is an associate professor in the Department of Computer Science & Engineering at the University of Minnesota. Dr. Zhao’s research interests are in computer vision and machine learning, and their applications in healthcare. Her current research on machine attention is supported by NSF and NIH. Dr. Zhao has published more than 100 papers in peer reviewed conferences and journals. She is an associate editor at the IEEE Transactions on Neural Networks and Learning Systems and the IEEE Transactions on Multimedia, a program chair at WACV '2022, and an area chair at CVPR and other computer vision and AI venues.