CS Seminar: Tianmin Shu

Description

Tianmin Shu, a postdoctoral associate in the Department of Brain and Cognitive Sciences and the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology, will give a talk titled "Cognitively Inspired Machine Social Intelligence" for the Department of Computer Science.

Abstract:

Despite our tremendous progress in artificial intelligence (AI), current AI systems still cannot adequately understand humans and flexibly interact with humans in real-world settings. The goal of my research is to build AI systems that can understand and cooperatively interact with humans in the real world. My hypothesis is that to achieve this goal, we need human-level machine social intelligence and that we can take inspiration from the studies of social cognition to engineer such social intelligence. To transfer insights from social cognition to real-world systems, I develop a research program for cognitively inspired machine social intelligence, in which I first i) build computational models to formalize the ideas and theories from social cognition, ii) develop new computational tools and AI methods to implement those models, and finally iii) apply those models to real-world systems such as assistive robots.

In this talk, I will discuss the progress I have made in my research program toward transforming those insights into real systems. I will first introduce the cognitively inspired approaches for the two key building blocks of machine social intelligence: social scene understanding and multi-agent cooperation. I will then demonstrate how these cognitively inspired approaches can enable the engineering of socially intelligent embodied AI assistants that can help people in their homes. Finally, I will also discuss future directions I plan to explore in order to reach the ultimate goal of engineering human-level machine social intelligence for real-world AI applications, such as smart cities, healthcare, and social VR.