Past Events

The Impact of High-Performance Computing on Linear Solver Algorithms and Mathematical Software

Industrial Problems Seminar

Ulrike Meier Yang (LLNL)

On efficient, approximate sampling for high dimensional scientific computing

Data Science Seminar

Yifan Chen (New York University)

From academia to Industry. Old and new challenges and strategies.

Industrial Problems Seminar

Luis Duque Alvarez (Meta)

In-context learning of solution operators to linear elliptic PDEs

Data Science Seminar

Frank Cole (University of Minnesota)

Applied Machine Learning and Computer Vision: Solving Industry Challenges in Consumer Products

Industrial Problems Seminar

Sajad Vahedizade (3M)

Quantitative Finance - The Confluence of Statistics, Mathematics, and Guessing

Industrial Problems Seminar

Chris Jones (US Bank)

Flag manifolds for robust averaging, principal directions, and hierarchical data representation

Data Science Seminar

Nathan Mankovich (University of Valencia)

From Graduate Research to Industry Impact: Navigating Your Early in Career Path

Industrial Problems Seminar

Brooke Logan Ogrodnik (Metron)

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.

Generative Machine Learning Models for Uncertainty Quantification

Data Science Seminar

Guannan Zhang (Oak Ridge National Laboratory (ORNL))