(CSE Distinguished Lecture Series)
Speaker: Yolanda Gil, University of Southern California
Date: Wednesday, November 8, 2017
Location: Room 1242, CSE Building (Multipurpose Room)
Abstract: We face increasingly complex integrative problems of societal importance that are orders of magnitude more challenging every decade. Computing has had a prime role in handling that complexity by scaling up calculations over data, more recently through powerful artificial intelligence techniques such as deep learning. I foresee qualitatively different advances stemming from new artificial intelligence approaches for scaling up reasoning over knowledge to systematically search through complex information spaces. In this talk, I will describe recent research to develop intelligent systems capable of automating hypothesis-driven discovery by capturing knowledge about experiment design strategies that determine what data and analysis methods can be used to test and revise a given hypothesis. I will propose seven principles and a research agenda for developing “thoughtful artificial intelligence” with capabilities that would significantly augment our ability to tackle fundamental problems in data science and scientific discovery that have been a barrier for progress in many areas.
Bio: Dr. Yolanda Gil is Director of Knowledge Technologies and Associate Division Director at the Information Sciences Institute of the University of Southern California, and Research Professor in the Computer Science Department. She received her M.S. and Ph. D. degrees in Computer Science from Carnegie Mellon University, with a focus on artificial intelligence. Her research is on intelligent interfaces for knowledge capture, knowledge-based planning and problem solving, information analysis and assessment of trust, and social knowledge collection. In recent years, Dr. Gil has collaborated with scientists in different domains on semantic workflows, metadata capture, reproducibility, and computer-mediated collaboration. She is a Fellow of the Association for Computing Machinery (ACM), and Past Chair of its Special Interest Group in Artificial Intelligence (SIGAI). She is also Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), and was elected its 24th President in 2016.