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Events for March 11, 2020
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CS Colloquium: Jesse Thomason (University of Washington) - Language Grounding with Robots
Wed, Mar 11, 2020 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Jesse Thomason, University of Washington
Talk Title: Language Grounding with Robots
Series: CS Colloquium
Abstract: We use language to refer to objects like "toast", "plate", and "table" and to communicate requests such as "Could you make breakfast?" In this talk, I will present work on computational methods to tie language to physical, grounded meaning. Robots are an ideal platform for such work because they can perceive and interact with the world. I will discuss dialog and learning strategies I have developed to enable robots to learn from their human partners, similar to how people learn from one another through interaction. I will present methods enabling robots to understand language referring expressions like "the heavy, metallic mug", the first work showing that it is possible to learn to connect words to their perceptual properties in the visual, tactile, and auditory senses of a physical robot. I will also present benchmarks and models for translating high-level human language like "put the toast on the table" that imply latent, intermediate goals into executable sequences of agent actions with the help of low-level, step-by-step language instructions. Finally, I will discuss how my work in grounded language contributes to NLP, robotics, and the broader goals of the AI community.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Jesse Thomason is a postdoctoral researcher at the University of Washington working with Luke Zettlemoyer. He received his PhD from the University of Texas at Austin with Raymond Mooney. His research focuses on language grounding and natural language processing applications for robotics (RoboNLP). Key to this work is using dialog with humans to facilitate both robot task execution and learning to enable lifelong improvement of robots' language understanding capabilities. He has worked to encourage and promote work in RoboNLP through workshop organization at both NLP and robotics conference venues.
Host: Stefanos Nikolaidis
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Computer Science General Faculty Meeting
Wed, Mar 11, 2020 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Invited Faculty Only
Contact: Assistant to CS chair
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*CANCELLED* CAIS Seminar: Rediet Abebe (Harvard University) - Mechanism Design for Social Good
Wed, Mar 11, 2020 @ 04:15 PM - 05:15 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Rediet Abebe, Harvard University
Talk Title: Mechanism Design for Social Good
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: Algorithmic and artificial intelligence techniques show immense potential to deepen our understanding of socioeconomic inequality and inform interventions designed to improve access to opportunity. Interventions aimed at historically under-served communities are made particularly challenging by the fact that disadvantage and inequality are multifaceted, notoriously difficult to measure, and reinforced by feedback loops in underlying structures.
In this talk, we develop algorithmic and computational techniques to address these issues through two types of interventions: one in the form of allocating scarce societal resources and another in the form of improving access to information. We examine the ways in which techniques from algorithms, discrete optimization, and network and computational science can combat different forms of disadvantage, including susceptibility to income shocks, social segregation, and disparities in access to health information. We discuss current practice and policy informed by this work and close with a discussion of an emerging research area -- Mechanism Design for Social Good (MD4SG) -- around the use of algorithms, optimization, and mechanism design to address this category of problems.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Rediet Abebe is a Junior Fellow at the Harvard Society of Fellows and will be receiving her Ph.D. in computer science from Cornell University in 2019. Her research is broadly in the fields of algorithms and AI, with a focus on equity and social good concerns. As part of this research agenda, she co-founded Mechanism Design for Social Good (MD4SG), a multi-institutional, interdisciplinary research initiative working to improve access to opportunity for historically disadvantaged communities. This initiative has active participants from over 100 institutions in 20 countries and has been supported by Schmidt Futures, the MacArthur Foundation, and the Institute for New Economic Thinking.
Abebe currently serves on the NIH Advisory Committee to the Director Working Group on AI, tasked with developing a comprehensive report to the NIH leadership. She was recently named one of 35 Innovators Under 35 by the MIT Technology Review and honored in the 2019 Bloomberg 50 list as a "one to watch." Her work has been covered by outlets including Forbes, the Boston Globe, and the Washington Post. In addition to her research, she also co-founded Black in AI, a non-profit organization tackling diversity and inclusion issues in AI. Her research is deeply influenced by her upbringing in her hometown of Addis Ababa, Ethiopia.
Host: USC Center for Artificial Intelligence in Society (CAIS)
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
