Upcoming Events

Viva la Revolución of Open Source Large Language Models: Unleashing the Dark Horse in AI Innovation

Industrial Problems Seminar

Patrick Delaney (BloomBoard)

Advancing Machine-Learned Interatomic Potentials: Enhancing Accuracy and Robustness in Materials Science Applications

Data Science Seminar

Yangshuai Wang (University of British Columbia)

Academia, to Industry, to the NBA – Navigating a Non-Academic Career with a PhD

Industrial Problems Seminar 

Daniel Martens (Minnesota Timberwolves)

Conditional coalescent and its applications in population genomics

Data Science Seminar

Wai-Tong (Louis) Fan (Indiana University)

Graph AI: Science and Industrial Applications

Industrial Problems Seminar 

Jie Chen (IBM Research)

Abstract

Graphs serve as both a mathematical abstraction and a structured framework for organizing data, finding widespread applications across scientific and technological domains. The ascent of graph neural networks underscores their exceptional efficacy in capturing intricate data interactions, leading to a resurgence of traditional applications with elevated solution quality and the emergence of novel uses. This talk delves into several graph-related challenges encountered in industrial contexts and the consequent evolution of graph-based deep learning methodologies. Topics include the learning of graph grammar for advancing material discovery and circuit design, the scaling of graph neural network training for financial forensics, and the unveiling of latent graph structures in power grid analytics. The talk concludes with a discussion on graph-based learning in the era of foundation models and research opportunities.

Are the measurement data enough: an instability study for an inverse problem for the stationary radiative transport near the diffusion limit

Data Science Seminar

Hongkai Zhao (Duke University)

Numerical Methods of Neural Network Discretization for Solving Nonlinear Differential Equations

Data Science Seminar

Wenrui Hao (The Pennsylvania State University)

Lecture: Greg Lyng

Industrial Problems Seminar

Greg Lyng (UnitedHealth Group - Optum Labs)

Lecture: Guannan Zhang

Data Science Seminar

Guannan Zhang (Oak Ridge National Laboratory (ORNL))

Math-to-Industry Boot Camp IX

The Math-to-Industry Boot Camp is an intense six-week session designed to provide graduate students with training and experience that is valuable for employment outside of academia. The program is targeted at Ph.D. students in pure and applied mathematics. The boot camp consists of courses in the basics of programming, data analysis, and mathematical modeling. Students work in teams on projects and are provided with training in resume and interview preparation as well as teamwork.

Applications are due Friday, March 15th, 2024.