Past Events

Math-to-Industry Boot Camp XI

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.

Hamilton-Jacobi-Bellman equations on graphs— the integro-differential viewpoint

Data Science Seminar

Russell Schwab (Michigan State University)

Operator learning meets inverse problems

Data Science Seminar

Nicholas Nelsen (Cornell University)

Time Scaling via Stochastic Simulation: Guidance, Correction and Sequential Monte Carlo

Data Science Seminar

Yiping Lu (Northwestern University)

Mathematicians in the age of industrial intelligence

Industrial Problems Seminar

Keith Rush (Google Deepmind)

Mean-Field Dynamics of Transformers: From Modeling to Clustering and Critical Scaling

Data Science Seminar

Shi Chen (MIT)

Scalable Normalizing Flows for Visual Generation

Industrial Problems Seminar

Jiatao Gu (Apple)

Surprises and Adventures in PCA under Heterogeneous Noise

Data Science Seminar

David Hong (University of Delaware)

From Mathematics to Risk Management: A Quantitative Perspective

Industrial Problems Seminar

Xu Li (Citi)

From Academic Rigor to Industrial Impact: Leveraging Applied Mathematics and Communication Skills in Software Engineering

Industrial Problems Seminar

Kelsey DiPietro (NextSilicon)