### HELLO!

I am an associate professor at
__Mathematics and Statistics
department at
McGill University__.

EMAIL: elliot.paquette@mcgill.ca

OFFICE: Burnside Hall 925

I
received my Ph.D. from the
Mathematics department at the University
of Washington (2013) from Ioana Dumitriu
__
Prof. Ioana Dumitriu__.
After that I held an NSF
postdoctoral
fellowship
at the Weizmann Institute of Science, in Rehovot, Israel
with
__Prof. Ofer Zeitouni__.
From 2016-2020, I was an assistant professor, tenure track, at Ohio State University.
I joined McGill University in 2020.

My research is in probability. Most of my research is in random matrix theory. My first focus is on $\beta$--ensembles, connections to branching processes. My second focus is on high-dimensional optimization, especially in its connections to random matrix theory. I also have work on probability with geometric and topological inspirations.

If you'd like to know more about probability in Montreal. See some of the links below:

I am currently supervisor for the postdoctoral fellows:

- (2022-)
__Elizabeth Collins-Woodfin (McGill)__ - (2024-)
__Inbar Seroussi (McGill)__

I have the pleasure of being the supervisor to the following PhD students:

- (2021-)
__Vincent Painchaud (McGill)__

- (2023-)
__Kevin Xiao (McGill)__

- (2023-)
__Noah Marshall (McGill)__(joint with Adam Oberman)

And MSc students:

- (2023-)
__Sam Kirkiles (McGill)__

- (2023-)
__Yixi Wang (McGill)__(joint with Courtney P.)

In the past, I supervised the following trainees:

- (2020-2023) PhD
__Kiwon Lee (McGill)__(joint with Courtney P.)

- (2019-2023) PhD
__Andrew Vander Werf (Ohio State)__(joint with Matt Kahle) Postdoc Brown

- (2022-2024)
__Hugo Latourelle-Vigeant (McGill)__(joint with Courtney P.) PhD Yale.

- (2022-2023) MSc
__Andrew Cheng (McGill)__(joint with Courtney P.) PhD Harvard.

- (2019-2020) Postdoc
__Érika Roldán (Ohio State)__(joint with Matt Kahle) Postdoc TU München and EPFL.

### RESEARCH

On the publications page below, I have put my preprints and publications.
This includes the *abstract* and for some, a pretty picture. You can also
find most of this information through these other means:

__CV__ *
__Google Scholar__ *
__arXiv__

### Papers

### Notes and Resources

### Math 598/784 (Fall 2023): High-dimensional probability

Course at a glance: Syllabus.

### Math 598/784 (Winter 2022): Random matrix theory

Course at a glance: Syllabus.

### Course materials

Random matrix theory of high-dimensional optimization. This is a set of notes for the July 2024 random matrix theory and probability summer schools: Random matrix theory and optimization theory.

Stochastic processes notes. This is a set of notes for Math547, stochastic processes, covering Markov chains and martingales (all in discrete time). Math 547 notes.

High dimensional limits of SGD. This is a set of notes for the July 2023 summer school in probability at Lehigh university, organized by Si Tang: High-dimensional limits of SGD.