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'''Friday, January 26. Jacob Bedrossian'''
'''Friday, January 26. Jacob Bedrossian'''
'''Theoretical methods for data-driven complex systems: from mathematical machine learning to simplicial complexes'''


== Past Colloquia ==
== Past Colloquia ==

Revision as of 03:09, 22 January 2024


UW Madison mathematics Colloquium is on Fridays at 4:00 pm in Van Vleck B239 unless otherwise noted.

Contacts for the colloquium are Simon Marshall and Dallas Albritton.


Spring 2024

date speaker title host(s)
Monday Jan 22 at 4pm (Room TBD) Yingkun Li (Darmstadt Tech U, Germany) Arithmetic of real-analytic modular forms Yang
Thursday Jan 25 at 4pm in VV911 Sanjukta Krishnagopal (UCLA/UC Berkeley) Smith
Jan 26 Jacob Bedrossian (UCLA) Tran
Feb 2
Feb 9 (held for town hall)
Feb 16 Jack Lutz (Iowa State) Guo
Feb 23
Mar 1 Per-Gunnar Martinsson (UT-Austin) TBA Li
Mar 8 Anton Izosimov (U of Arizona) Gloria Mari-Beffa
Mar 15 Peter Humphries (Virginia) Marshall
Mar 20 Wanlin Li (Washington U St Louis) Dymarz, GmMaW
Mar 29 Spring break
Apr 5 Ovidiu Savin (Columbia) Tran
Apr 12 Mikayla Kelley (U Chicago Philosophy) Math And... seminar, title TBA Ellenberg, Marshall
Apr 19 Yanyan Li (Rutgers) Tran
Apr 26 Chris Leininger (Rice) TBA Uyanik

Abstracts

Monday, January 22. Yingkun Li

Arithmetic of real-analytic modular forms

Modular form is a classical mathematical object dating back to the 19th century. Because of its connections to and appearances in many different areas of math and physics, it remains a popular subject today. Since the work of Hans Maass in 1949, real-analytic modular form has found important applications in arithmetic geometry and number theory. In this talk, I will discuss the amazing works in this area over the past 20 years, and give a glimpse of its fascinating future directions.

Thursday, January 25. Sanjukta Krinshagopal

Theoretical methods for data-driven complex systems: from mathematical machine learning to simplicial complexes

In this talk I will discuss some aspects at the intersection of mathematics, machine learning, and networks to introduce interdisciplinary methods with wide application.

First, I will discuss some recent advances in mathematical machine learning for prediction on graphs. Machine learning is often a black box. Here I will present some exact theoretical results on the dynamics of weights while training graph neural networks using graphons - a graph limit or a graph with infinitely many nodes. I will use these ideas to present a new method for predictive and personalized medicine applications with remarkable success in prediction of Parkinson's subtype five years in advance.

Then, I will discuss some work on higher-order models of graphs: simplicial complexes - that can capture simultaneous many-body interactions. I will present some recent results on spectral theory of simplicial complexes, as well as introduce a mathematical framework for studying the topology and dynamics of multilayer simplicial complexes using Hodge theory, and discuss applications of such interdisciplinary methods to studying bias in society, opinion dynamics, and hate speech in social media.


Friday, January 26. Jacob Bedrossian

Past Colloquia

Spring 2024

Fall 2023

Spring 2023

Fall 2022

Spring 2022

Fall 2021

Spring 2021

Fall 2020

Spring 2020

Fall 2019

Spring 2019

Fall 2018

Spring 2018

Fall 2017

Spring 2017

Fall 2016

Spring 2016

Fall 2015

Spring 2015

Fall 2014

Spring 2014

Fall 2013

Spring 2013

Fall 2012

WIMAW