Upcoming Events
Viva la Revolución of Open Source Large Language Models: Unleashing the Dark Horse in AI Innovation
Friday, March 29, 2024, 1:25 p.m. through Friday, March 29, 2024, 2:25 p.m.
Lind Hall 325 or Zoom
Industrial Problems Seminar
Patrick Delaney (BloomBoard)
Advancing Machine-Learned Interatomic Potentials: Enhancing Accuracy and Robustness in Materials Science Applications
Tuesday, April 2, 2024, 1:25 p.m. through Tuesday, April 2, 2024, 2:25 p.m.
Lind Hall 325 and Zoom
Data Science Seminar
Yangshuai Wang (University of British Columbia)
Academia, to Industry, to the NBA – Navigating a Non-Academic Career with a PhD
Friday, April 5, 2024, 1:25 p.m. through Friday, April 5, 2024, 2:25 p.m.
Lind Hall 325 and Zoom
Industrial Problems Seminar
Daniel Martens (Minnesota Timberwolves)
Conditional coalescent and its applications in population genomics
Tuesday, April 9, 2024, 1:25 p.m. through Tuesday, April 9, 2024, 2:25 p.m.
Lind Hall 325 and Zoom
Data Science Seminar
Wai-Tong (Louis) Fan (Indiana University)
Graph AI: Science and Industrial Applications
Friday, April 12, 2024, 1:25 p.m. through Friday, April 12, 2024, 2:25 p.m.
3-180 Keller Hall or Zoom
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
Tuesday, April 16, 2024, 1:25 p.m. through Tuesday, April 16, 2024, 2:25 p.m.
Lind Hall 325 or via Zoom
Data Science Seminar
Hongkai Zhao (Duke University)
Numerical Methods of Neural Network Discretization for Solving Nonlinear Differential Equations
Tuesday, April 23, 2024, 1:25 p.m. through Tuesday, April 23, 2024, 2:25 p.m.
Lind Hall 325 or via Zoom
Data Science Seminar
Wenrui Hao (The Pennsylvania State University)
Lecture: Greg Lyng
Friday, April 26, 2024, 1:25 p.m. through Friday, April 26, 2024, 2:25 p.m.
Lind Hall 325 or Zoom
Industrial Problems Seminar
Greg Lyng (UnitedHealth Group - Optum Labs)
Lecture: Guannan Zhang
Tuesday, April 30, 2024, 1:25 p.m. through Tuesday, April 30, 2024, 2:25 p.m.
Lind Hall 325 or via Zoom
Data Science Seminar
Guannan Zhang (Oak Ridge National Laboratory (ORNL))
Math-to-Industry Boot Camp IX
Monday, June 17, 2024, 8 a.m. through Friday, July 26, 2024, 5 p.m.
Online
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.