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COLLOQUIUM: Lynna Gui, "Predictive Learning in the Dynamic World"

Event Type
Seminar/Symposium
Sponsor
Illinois Computer Science
Location
https://mediaspace.illinois.edu/media/t/1_ebq5gck7
Date
Sep 27, 2021   3:30 pm  
Views
212
Originating Calendar
Computer Science Colloquium Series

Link to Talk Video: https://mediaspace.illinois.edu/media/t/1_ebq5gck7

Abstract:
In real-world scenarios, such as AR/VR, autonomous driving, and robots, being able to predict the environment’s dynamics is important. Humans are living in a dynamic world. By nature, we are continuously predicting how the surrounding environment changes and how other people act over time. These predictions are critical for shaping our daily interactions with the world. However, such ability has been substantially missing in modern artificial intelligent systems.

 

In this talk, I will present our efforts towards endowing machine learning systems with predictive learning ability, on the illustrative task of 3D human motion prediction. The core idea is to leverage the rich yet implicit structural dependencies and regularities inherent in motion sequences without any additional supervision, including geometric, temporal, contextual, attentional, and model parameter structures. By incorporating the desired structural knowledge into a deep learning based framework, I will show that we forecast realistic, human-like, and diverse future motion in both short-term and long-term scenarios with significantly less annotated motion capture data. I will also demonstrate the application of our prediction model for human-robot interaction, and further discuss some ongoing work on in-the-wild prediction, with the ultimate goal of building autonomous agents that perceive, interpret, and interact with the dynamic world.

Bio:
Liangyan Gui is a research assistant professor in the Department of Computer Science at UIUC. Her research interests lie in computer vision, machine learning, and robotics, with a particular focus on predictive learning and efficient learning. Before joining UIUC, she was a computer vision researcher at Argo AI, LLC and a postdoctoral fellow at Carnegie Mellon University. She received her Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University under the supervision of José M. F. Moura. Previously, she got her M.S. and B.E. in Electronic Engineering from Tsinghua University. She has spent time at Google and Facebook Reality Labs.

 

Password: csillinois 

 

Part of the Illinois Computer Science Speakers Series. Faculty Host: Lana Lazebnik

link for robots only