Soledad Villar
Johns Hopkins University
"Exact and Approximate Symmetries in Machine Learning Models"

Philip Morrison
The University of Texas at Austin
"The Metriplectic 4-bracket: A Curvature-like Framework for Describing Dissipation in Joined Hamiltonian and Dissipative Fluid and Plasma"

Daniel Tartakovsky
Stanford University
"Role of Physics in Physics-Informed Machine Learning"

Houman Owhadi
CalTech
"Computational Hypergraph Discovery"

Noseong Park
Yonsei University
"GREAD: Graph Neural Reaction-Diffusion Networks"

Reese Jones
Sandia National Laboratories
"Machine Learning Constitutive Models of Inelastic Materials with Microstructure"

Prasanna Sattigeri
IBM
"Uncertainty Quantification and Trustworthy AI-assisted Decision Making"

Mengjia Xu
Brown University
"Stochastic Graph Embeddings on Transformers in Dynamic Graphs"

Panos Stinis
Pacific Northwest National Laboratory
"Multifidelity Scientific Machine Learning"

Prasanna Balaprakash
Oak Ridge National Laboratory
"Scalable Automated Design and Development of Deep Neural Networks for Scientific and Engineering Applications"

Priya Panda
Yale University
"Bio-Plausible Algorithm-Hardware Co-Design for Efficient & Robust AI"

Yu (Kevin) Cao
Arizona State University
"Scale up Your In-Memory Computing: A Heterogenous Paradigm"

Eric Hall
Dundee University
"Uncertainty Quantification for Deep Learning of Complex Systems"

Ani Hsieh
University of Pennsylvania
"Building a Smart Ocean Observational Framework: Challenges and Opportunities for Robotics and Autonomous Systems"

Alex Hernandez-Garcia
Mila-Quebec Artificial Intelligence Institute
“GFlowNet: Introduction and Applications to AI-Driven Scientific Discovery”