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.

Upcoming Events

3:00 pm - 4:00 pm
E202 Westgate and Virtual via Zoom

Join Romit Maulik, assistant professor at the Penn State College of Information Sciences and Technology, for an upcoming talk as part of CSRAI's AI for Social Impact Seminar Series. This lecture is free and open to the Penn State community.

Join This Talk

About the Talk

Recently, advances in machine learning, hardware (e.g. GPUs/TPUs), and availability of high-quality data have set the stage for machine learning (ML) to tackle problems for weather and climate. This has led to a paradigm shift in operational weather forecasting, most evidently seen by the vast amount of resources being invested into AI models at the leading operational centers including NOAA, ECMWF, and others. This has been motivated by the influx of deep learning-based models in the last three years for weather forecasting which have been demonstrated to have forecasting skill approaching or even exceeding the best available numerical weather prediction (NWP) models. In this seminar, we explore the rise of ML-based modeling for weather and climate prediction, specifically, by looking at (1) a vision transformer-based model for medium-range weather forecasting called Stormer and, (2) one of the first systematic evaluations of machine learning-based emulators for climate research. We conclude by discussing some exciting new directions that are a consequence of our developed models.

About the Speaker

Romit Maulik is an Assistant Professor in the College of Information Sciences and Technology at Penn State. He is also a co-hire in the Institute for Computational and Data Sciences at Penn State and a Joint Appointment Faculty at Argonne National Laboratory. He obtained his Ph.D. in Mechanical and Aerospace Engineering at Oklahoma State University in 2019 and was the Margaret Butler Postdoctoral Fellow from 2019-2021 before becoming an Assistant Computational Scientist at Argonne National Laboratory from 2021-2023. His group studies high-performance multifidelity scientific machine learning algorithm development with applications to various multiphysical nonlinear dynamical systems such as those that arise in fluid dynamics, weather and climate modeling, nuclear fusion, and beyond. He is an Early Career Awardee from the Army Research Office.

About the 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.

Past Events

"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