News

 Undergraduate Andy Wang develops a statistical method to better measure uncertainty in motion tracking .

For her Design Day project, a Johns Hopkins student examines how conflict, deforestation, and governance intersect to shape human trafficking networks. 

The prestigious award honors exceptional STEM students nationwide, including a Johns Hopkins Applied Mathematics and Statistics undergraduate among this year’s honorees.

Applied mathematics and statistics faculty and students help lead conversations on advancing women in artificial intelligence.

A machine learning approach mimics real-world, act-at-the-moment choices to improve timing, reduce costs, and adapt to changing demand.

Johns Hopkins undergraduate Talia Hovsepian is taking a gap year in England to work as a data scientist for Racing Bulls.

Applied Mathematics and Statistics student Adam Tobin-Williams ’26 bridges engineering and mathematics to solve real-world problems. 

Johns Hopkins researchers unlock hidden patterns to help AI recognize images with far less training data.

Johns Hopkins team uses computer simulations to find the optimal level of disorder for light-manipulating devices.

In this Q&A, a new assistant professor discusses the mathematical foundations of AI and his plans for collaboration at Johns Hopkins.

In this Q&A, incoming assistant professor shares how she became interested in PDEs and what excites her about joining Johns Hopkins.

New research ditches trial-and-error for faster, sharper, more trustworthy models.