Talk Abstract
We will start with a 4-year collaboration with a crowdsourcing food rescue platform, where we combined offline ML model with online optimization to improve volunteer engagement. We will discuss our randomized controlled trial, and our experience rolling it out to over 25 cities across North America. Lifting ourselves beyond this particular application domain, we propose bandit data-driven optimization, a theoretical paradigm for principled iterative prediction-prescription to address the unique challenges that arise in low-resource sustainability settings. We will also discuss our work on large language model-based media monitoring for environmental conservation, which as been adopted by the World Wildlife Fund in multiple countries. We will conclude the talk with the ample future directions on AI and LLM research for social good.
Biography
Dr. Ryan Shi is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh. He works with public sector organizations to address societal challenges in food security, environmental conservation, and poverty alleviation using AI. Some of his research has been deployed at these organizations worldwide. Dr. Shi was the recipient of a 2023 IAAI Deployed Application Award, a 2022 Siebel Scholar Award, a 2021 Carnegie Mellon Presidential Fellowship, and was selected as a 2022 Rising Star in Data Science and ML & AI by UChicago and USC. Previously, he consulted for DataKind and interned at Microsoft and Facebook. Dr. Shi got his Ph.D. in Societal Computing from Carnegie Mellon University advised by Fei Fang and a B.A. in Mathematics and Computer Science from Swarthmore College.
Location
Sennott Square Building, Room 5317
Date
Friday, February 2 at 2:00 p.m. to 3:15 p.m.