april, 2021

fri02apr11:00 amfri12:00 pmOM PhD SeminarsPhebe Vayanos, University of Southern California11:00 am - 12:00 pm CST OnlineRegister

Event Details

Phebe Vayanos of The University of Southern California will be speaking on designing robust, interpretable, and fair social and public health interventions.

Designing Robust, Interpretable, and Fair Social and Public Health Interventions

In the last decades, significant advances have been made in AI, ML, and optimization. Recently, systems relying on these technologies are being transitioned to the field with the potential of having tremendous influences on people and society. With an increase in the scale and diversity of deployment of algorithm-driven decisions in the open world come several challenges including the need for robustness, interpretability, and fairness which are confounded by issues of data scarcity and bias, tractability, ethical considerations, and problems of shared responsibility between humans and algorithms.

In this talk, we focus on the problems of homelessness and public health in low resource and vulnerable communities and present research advances in AI, ML, and optimization to address one key cross-cutting question: how to allocate scarce intervention resources in these domains while accounting for the challenges of open-world deployment? We will show concrete improvements over the state of the art in these domains based on real-world data. We are convinced that, by pushing this line of research, AI, ML, and optimization can play a crucial role to help fight injustice and solve complex problems facing our society.

About Phebe Vayanos

Phebe Vayanos is an Assistant Professor of Industrial & Systems Engineering and Computer Science at the University of Southern California. She is also an Associate Director of CAIS, the Center for Artificial Intelligence in Society, an interdisciplinary research initiative between the schools of Engineering and Social Work at USC. Her research is focused on Operations Research and Artificial Intelligence and in particular on optimization and machine learning. Her work is motivated by problems that are important for social good, such as those arising in public housing allocation, public health, and biodiversity conservation.

Prior to joining USC, she was a lecturer in the Operations Research and Statistics Group at the MIT Sloan School of Management and a postdoctoral research associate in the Operations Research Center at MIT. She holds a Ph.D. degree in Operations Research and an MEng degree in Electrical & Electronic Engineering, both from Imperial College London. She served as a member of the ad hoc INFORMS AI Strategy Advisory Committee and is an elected member of the Committee on Stochastic Programming (COSP). She is a recipient of the INFORMS Diversity, Equity, and Inclusion Ambassador Program Award.


(Friday) 11:00 am - 12:00 pm CST




Iman Dayarianidayarian@culverhouse.ua.edu