“Artificial Intelligence for Environmental Sciences: An Essential Research Agenda”

Yolanda Gil Information Sciences Institute and Department of Computer Science University of Southern California

ABSTRACT

Artificial Intelligence (AI) has enormous potential to provide fundamental new capabilities for environmental sciences. Since its early days, AI has made strong contributions to diverse areas in science through machine learning, robotics, planning, knowledge representation and reasoning. In order to meet the challenges presented by complex phenomena with uncertain, intermittent, sparse, multi-resolution, and multi-scale data, new AI approaches must be developed to incorporate existing scientific knowledge and the user’s context into intelligent systems. This requires strong joint collaborations between AI researchers and environmental scientists. In this talk, I will present our ongoing work in developing new AI approaches for interdisciplinary model integration spanning climate, hydrology, agriculture, and socioeconomic modeling. I will also summarize potential joint areas of research in knowledge representation, machine learning, sensing and data collection, data integration, and intelligent user interfaces. The new USC Center for Knowledge- Powered Interdisciplinary Data Science will foster these novel areas of collaborative work between AI researchers and environmental scientists.

SPEAKER 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 Computer Science and Spatial Sciences. 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, which she investigates in a variety of projects concerning scientific discovery, knowledge-based planning and problem solving, information analysis and assessment of trust, semantic annotation and metadata, agent and software choreography, and community-wide development of knowledge bases. Dr. Gil collaborates with scientists in different domains on semantic workflows and metadata capture, social knowledge collection, 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. She is also Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), and was elected as its 24th President in 2016.