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Computer Vision Seminar - Neuro-Symbolic AI for Visual Intelligence

22 Feb
Tuesday, 02/22/2022 4:00pm to 5:00pm
Zoom
Seminar
Speaker: Chuang Gan

Abstract: Visual intelligence is characterized by the ability to understand and reason about the world around us. While deep learning has excelled at pattern recognition tasks such as image classification and object recognition, it falls short of deriving the true understanding necessary for complex reasoning and physical interaction. In this talk, I will introduce a framework, neuro-symbolic AI, to reduce the gap between machine and human intelligence in terms of data efficiency, flexibility, and generalization. Our approach combines the ability of neural networks to extract patterns from data, symbolic programs to represent and reason from prior knowledge, and physics engines for inference and planning. Together, they form the basis of enabling machines to effectively reason about underlying objects and their associated dynamics as well as master new skills efficiently and flexibly.

Bio: Chuang Gan is a principal research staff member at MIT-IBM Watson AI Lab. He is also a visiting research scientist at MIT, working closely with Prof. Antonio Torralba and Prof. Josh Tenenbaum. Before that, he completed his Ph.D. with the highest honor at Tsinghua University, supervised by Prof. Andrew Chi-Chih Yao. His research interests sit at the intersection of computer vision, machine learning, and cognitive science. His research works have been recognized by Microsoft Fellowship, Baidu Fellowship, and media coverage from BBC, WIRED, Forbes, and MIT Tech Review. He has served as an area chair of CVPR, ICCV, ICML, ICLR, NeurIPS, ACL, and an associate editor of IEEE Transactions on Image Processing.

Join the Seminar

This seminar will be streaming via Zoom at the link above but requires a passcode. To obtain the passcode for this event, please see the announcements on the college email lists or contact us.