AI for Social Impact Seminar Series

The AI for Social Impact Seminar Series brings together researchers and thought leaders from a variety of fields to explore the diverse applications of artificial intelligence for a societal benefit. Through the series, the Center for Socially Responsible Artificial Intelligence aims to inspire new ideas and collaborations and to identify novel approaches that can advance discovery in the field at Penn State and beyond.

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

Past Events

"How AI is Reshaping Your Paycheck: Personalized Wages in the Inference Economy" - Dana Calacci, Penn State
"Weather and Climate Emulation with State-of-the-Art Physics-Informed AI Algorithms" - Romit Maulik, Penn State
"AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation" - Qingyun Wu, Penn State
“Algorithmic Rural Road Planning in India: Constrained Capacities and Choices in Public Sector” - Harsh Nisar, Government of India
"Mind the Gap: From Predictions to ML-Informed Decisions” - Maria De-Arteaga, University of Texas at Austin
“Advances in AI for Cyber-Safety” - Srijan Kumar, Georgia Institute of Technology
"Initial Progress on the Science of Science" - Dashun Wang, Northwestern University
"Mobility Networks for Modeling the Spread of COVID-19" - Jure Leskovec, Stanford University
"Measuring Economic Development from Space with Machine Learning" - Stefano Ermon, Stanford University
"Physics-Guided AI for Learning Spatiotemporal Dynamics " - Rose Yu, University of California San Diego
"Data Science for Social Equality" - Emma Pierson, Cornell Tech
"Steps Toward Trustworthy Machine Learning" - Tom Dietterich, Oregon State University
"Political Polarization and International Conflicts through the Lens of NLP" - Ashique KhudaBukhsh, Carnegie Mellon University
"Behavior Change for Social Good Using AI" - Kobi Gal, Ben-Gurion University of the Negev and University of Edinburgh
"COPs, Bandits, and AI for Good" - Long Tran-Thanh, University of Warwick
"Responsible AI: Thinking Beyond Data and Models" - Vinodkumar Prabhakaran, Google
"Just, Equitable, and Efficient Algorithmic Allocation of Scarce Societal Resources" - Sanmay Das, George Mason University
"AI for Population Health" - Bryan Wilder, Harvard University
"Doing Good with Data: Fairly and Equitably" - Rayid Ghani, Carnegie Mellon University
"AI for Public Health and Conservation" - Milind Tambe, Harvard University