Distinguished Lectures in Humanities: Language Learning in Humans and Machines: Two Sides of the Same Coin

Abstract

Psychology, Computer Science and Neuroscience have a history of shared questions and inter-related advances. Recently, new technology has enabled those fields to move from “toy” small-scale approaches to the study of language learning from raw sensory input and to do so at a large scale that constitutes daily life. The three primary goals of my research are 1) to quantify the statistical regularities in the real world, 2) to examine the underlying computational mechanisms operated on the statistical data, and 3) to apply the findings from basic science to real-world applications. In this talk, I will present several projects in my research lab to show that the advances in human learning and machine learning fields place us at the tipping point for powerful and consequential new insights into mechanisms of (and algorithms for) learning.

About the speaker

Chen Yu is the Charles and Sarah Seay Regents Professor of the Department of Psychology, Central of Perceptual Systems, and Institute of Neural Science at the University of Texas at Austin. He is a fellow of the Cognitive Science Society and the Association of Psychological Science. He received the Robert L. Fantz Memorial Award from American Psychological Foundation, the David Marr Prize from the Cognitive Science Society, and the ICIS Early Distinguished Contribution Award. He has published over 200 articles with several best paper awards from IEEE ICDL, Cognitive Science, and CVPR. His research has been funded by NICHD, NSF, NIDCD, NEI, NIJ, and AFOSR.