Abstract: In this talk I will present the seeing-eye robot grand challenge and discuss the components required to design and build a service robot that can replace or surpass the functionalities of a seeing-eye dog. This challenge encompasses a variety of research problems that can benefit from human-inspired AI: reasoning about other agents, human-robot interactions, explainability, teaching teammates, and more. For each of these problems, I will present an example novel contribution that leverages the bilateral investigation of human and artificial intelligence. Finally, I will discuss the many remaining challenges towards achieving a seeing-eye robot and how I plan to tackle these challenges.

Short Bio: Reuth Mirsky is a Postdoctoral Fellow at the Computer Science Department in the University of Texas at Austin and an incoming Assistant Professor at the Department of Computer Science in Bar Ilan University. In her research, she is interested in the similarities and the differences between AI and natural intelligence, and how these can be used to extend AI. Reuth is an active member in the AI research community and is the general chair of this year's AI-HRI fall symposium. Reuth was selected as one of the 2020 Electrical Engineering and Computer Science (EECS) Rising Stars.
https://sites.google.com/site/dekelreuth/