Organizers: Tom Haines
When: 5:00pm - 5:50pm Mondays
Where: In-person MTH 3206, Online Zoom meeting ID number 990 3116 1357
Description: This RIT is designed to useful for all graduate students, regardless of research specialty. The lectures will be a mixture of surveys on current interesting developments in mathematics and applications and talks about "mathematical culture", such as how to publish your research.

Canvas page: https://umd.instructure.com/courses/1302777

Organizer: Maria Cameron
When: Friday, 12PM
Where: Kirwan Hall MTH 1313
Web Page: https://www.math.umd.edu/~mariakc/rit.html
Description: In recent years, machine learning techniques penetrated a tremendous variety of scientific fields. In particular, they gave rise to data-driven methods for the study of rare event in complex physical systems such as conformational changes in biomolecules, rearrangements of clusters of interacting particles, etc. These methods truly opened new horizons by enabling us to address problems that used to be intractable due to the curse of dimensionality. They are divided into two families: diffusion map-based and neural network-based. In this RIT we will explore methods for the study of rare events based on machine learning.

Organizers: Patrick Brosnan
When: Friday at 2pm
Where: Kirwan Hall MTH 3206

Organizers: Ricardo Nochetto and Maziar Raissi
When: Fridays, 4:30 - 5:30 PM
Where: MATH 1308
Description: In this RIT we will discuss the fundamentals of sparse grids (hyperbolic cross approximations) and their applications to numerical solution of partial differential equations in high dimensions. The main focus will be on dealing with the "curse of dimensionality". We will drive best possible rates of approximation that can be achieved by sparse grids in Sobolev spaces of interest.

Organizers: Dmitry Dolgopyat, Giovanni Forni, Michael Jakobson, and Vadim Kaloshin
When: Mondays @ 3pm - 4:30pm
Where: Math 1308
Description: The goal of the RIT is to introduce the participants to basic techniques and open problems in the field of Dynamics.

Organizers: Vince Lyzinski and Eric Slud
When: TBA
Where: TBA

The topic for fall 2024 is "High-Dimensional Statistics", following Wainwright's book High-Dimensional Statistics.  For more details, go to this web page.