Recent developments of artificial intelligence and advanced machine learning tools introduce new insights and approaches of advancing the study in a wide variety of frontiers. New mathematical theories and practically applicable strategies are strongly needed requiring deeper understandings of the machine learning methods to model crucial poorly represented processes and to facilitate the understanding and prediction of nature. These issues have been significantly advanced from several outlooks in rigorous mathematical theory, quantitative and qualitative modeling, and novel multiscale asymptotic and computational strategies. This workshop brings together researchers and practitioners from different backgrounds to explore ideas and communicate recent advancements in theoretical, computational and application aspects on scientific machine learning.

Organizers: Guang Lin and Di Qi, Purdue University

This workshop is supported by Office of Naval Research and Center for Computational and Applied Mathematics at Purdue University.

• Please register before September 22, 2025 if you will be attending. There is no charge for registration, but registration is required for an accurate lunch count.

• We will also have a poster session and lightning talks for students or junior researchers who are interested in sharing their work. Please submit your title, abstract and the presentation format HERE before September 1, 2025. 

The Venue: All the presentations will be in LWSN 1142,  305 N University St, West Lafayette, IN