Past Events

Math-to-Industry Boot Camp X

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.

Mathematical Biology in the Pharmaceutical Industry: A Quantitative Systems Pharmacology Model of Rheumatoid Arthritis

Industrial Problems Seminar

Maria Munoz Lopez (Simulations Plus, Inc.)

Low Distortion Embedding with Bottom-up Manifold Learning

Data Science Seminar

Gal Mishne (UCSD)

Machine learning and its application in industry: science, e-commerce and more

Industrial Problems Seminar

Yiran Li (Microsoft)

The Wasserstein barycenter problem with signed weights

Data Science Seminar

Matt Jacobs (UC Santa Barbara)

From The Three-Body Problem to Quantitative Finance

Industrial Problems Seminar

Chen Shi (Morgan Stanley)

Federated Reinforcement Learning: Statistical, Communication and Computation Trade-offs

Data Science Seminar

Yuejie Chi (Carnegie Mellon)

Nonlinear inverse problems in semiconductor manufacturing

Industrial Problems Seminar

Christopher A. Wong

On Provable Posterior Sampling with Denoising Oracles

Data Science Seminar

Joan Bruna (NYU Courant Institute)

Lie-Poisson Neural Networks (LPNets): Data-Based Computing of Hamiltonian Systems

Data Science Seminar

Vakhtang Poutkaradze (University of Alberta)