Young Achievers Symposium

The CSRAI Young Achievers Symposium series highlights early career researchers in diverse fields of AI for social impact. The symposium series seeks to focus on emerging research, stimulate discussions, and initiate collaborations that can advance research in artificial intelligence for societal benefit.

All events in the series are free and open to the public unless otherwise noted. Penn State students, postdoctoral scholars, and faculty with an interest in socially responsible AI applications are encouraged to attend.

Note: When watching recordings of past talks, closed captions can be enabled by selecting the [CC] button in the YouTube video player.

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Past Events

"Bridging Gaps Between Metrics and Goals to Improve Societal Impacts of Machine Learning"- Serena Wang, University of California, Berkeley
"Incorporating Prosocial Constraints and Exploiting Problem Structure in Sequential Decision-Making" - Christine Herlihy, University of Maryland, College Park
"Learning and Planning Under Uncertainty for Wildlife Conservation" - Lily Xu, Harvard University
"Navigating the Limits of AI Explainability: Designing for Novice Technology Users in Low-Resource Settings" - Chinasa T. Okolo, Cornell University
"Towards Scalable Game Theoretic Approaches for Addressing Societal Challenges" - Chun Kai Ling, Carnegie Mellon University
"Challenges and Frontiers in Deploying Transparent Machine Learning" - Umang Bhatt, University of Cambridge
“Towards Equitable Language Technologies” - Su Lin Blodgett, Microsoft Research Montreal
“From a Bag of Bagels to Bandit Data-Driven Optimization” - Ryan Shi, Carnegie Mellon University
"Differential Privacy for Measuring Nonlinear Correlations between Sensitive Data at Multiple Parties” - Praneeth Vepakomma, MIT
“Decision-focused Learning: Integrating Optimization Problems into Training Pipeline to Resolve Social Challenges” - Kai Wang, Harvard University
“Diversity and Inequality in Social Networks” - Ana-Andreea Stoica, Columbia University
“Interactive AI Model Debugging and Correction” - Sherry Tongshuang Wu, University of Washington