Upcoming Events

Events coming soon:

PDEs of incompressible fluid flows, computer assisted proofs and neural networks

Event Overview

The aim of the conference is to bring together both experts and young scholars in three areas undergoing rapid progress: PDEs of fluid dynamics, computer assisted proofs and machine learning, to discuss the latest developments and facilitate discussion and collaboration.

Schedule Abstracts


  • Javi Serrano Gomez  – Brown University                    
  • Ching-Yao Lai – Stanford University  
  • Yongji Wang – Princeton University
  • Jiajie Chen – New York University
  • In-jee Jeong – Seoul National University
  • Sanchit Chaturvedi – New York University
  • Jia Shi – Massachusetts Institute of Technology
  • Joonhyun La – Korea Institute for Advanced Study
  • Tristan Leger – New York University
  • Raj Beekie – Duke University
  • Xinyu Zhao – McMaster University
  • Sifan Wang – University of Pennsylvania
  • Susanna Haziot – Brown University


  • Tristan Buckmaster
  • Javier Serrano Gomez
  • Alexandru Ionescu
  • Hao Jia
  • Ching-Yao Lai


Supported by NSF DMS-2245228 "FRG: Collaborative Research: Singularities in incompressible flows: computer assisted proofs and physics-informed neural networks”

Recent Advances in Nonlinear Partial Differential Equations

Event Overview

Recent Advances in Nonlinear Partial Differential Equations will be held from May 13 through May 17, 2024, at the University of Minnesota–Twin Cities. The conference provides much needed opportunities for participants to keep track of the significant developments in some of the most active research areas in PDEs. The talks are arranged at a leisurely pace over one week, to allow participants ample time to interact with experts in their area of interest. There will be a poster session where junior participants are encouraged to present their own research. Panel discussions on career developments and experts-led sessions on open problems will further enhance the involvement of participants in the conference. Speakers will be asked for permission to record their talks that will be made publicly available for a wider accessibility. Special attention will be paid to advertise and recruit participants from underrepresented groups.

The analysis of fluid equations and Calculus of Variations (CVs) is undergoing very rapid and significant progress in recent years. The conference features a wide scope of active topics in both fluid equations and calculus of variations. Specifically, the scientific themes of the conference include (i) Computation and Computer Assisted Proofs in PDEs, (ii) Convex Integration Techniques and its Applications, (iii) Regularity theory of the Euler and Navier Stokes equations, (iv) Hydrodynamic stability in high Reynolds number regime, (v) Calculus of Variations from material sciences. Important breakthroughs have been achieved in recent years in all these closely related areas. CVs is a fertile source of ideas for many branches of PDEs including fluid equations. It is hoped that by bringing together experts from both areas a cross-fertilization is more likely to occur. 


Apply Here

Preliminary List of Speakers

  • Kyungkeun Kang – Yonsei University
  • Gregory Seregin – University of Oxford
  • Alexander Kiselev – Duke University
  • John Ball – Heriot-Watt University
  • Thierry Gallay – Université Grenoble Alpes Institut Fourier
  • Laszlo Szekelyhidi – Max Planck Institute for Mathematics in the Sciences
  • Camillo De Lellis – Institute for Advanced Study
  • Richard James – University of Minnesota
  • Javi Gomez-Serrano – Brown University
  • Connor Mooney – University of California, Irvine
  • Jacob Bedrossian – University of California, Los Angeles
  • Anna Mazzucato – Pennsylvania State University
  • Peter Constantin – Princeton University
  • Peter Polacik –  University of Minnesota
  • Julien Guillod – Laboratoire Jacques-Louis Lions, Sorbonne Université
  • Hyunju Kwon – ETH Zürich
  • Irene Fonseca – Carnegie Mellon University
  • Robert Kohn – New York University
  • Svitlana Mayboroda – University of Minnesota
  • Blair Davey – Montana State University


  • Dallas Albritton – University of Wisconsin, Madison
  • Tarek Elgindi – Duke University
  • Hao Jia – University of Minnesota
  • Tai-Peng Tsai – University of British Columbia, Vancouver
  • Vlad Vicol – New York University
  • Xiaodong Yan – University of Connecticut

The conference is supported by NSF DMS-2346780: "Conference: Recent advances in nonlinear Partial Differential Equations." The event is also sponsored in part by the Institute for Mathematics and its Applications.

Developing Online Learning Experiments Using Doenet (2024)

Apply to attend


  • Kris Hollingsworth - Minnesota State University, Mankato
  • Anurag Katyal - Palm Beach State College
  • Melissa Lynn - St Olaf College
  • Duane Nykamp - University of Minnesota, Twin Cities

In this five-day workshop, participants will learn how to create and implement online learning experiments using the Distributed Open Education Network (Doenet, doenet.org). Doenet is designed to help faculty critically evaluate how different content choices influence student learning in their classrooms. Doenet enables instructors to quickly test hypotheses regarding the relative effectiveness of alternative approaches by providing tools to assign different variations of an activity and analyze the resulting data.

Following brief introductions and demos of features of the Doenet platform, participants will work in small groups to develop learning experiments that can be used in the college classroom, assisted by the developers of Doenet. The expectation is that participants will leave the workshop with a learning experiment that they can use in their classroom the following year.

The workshop will run from 9 AM on Monday, May 20 through Noon on Friday, May 24. All organized activities will occur between 9 AM and 4 PM each day.

The workshop is open to faculty at all levels teaching STEM courses.

To apply, please submit the following documents through the Program Application link at the top of the page:

  1. A personal statement briefly (200 words or less) stating what you hope to contribute to the discussion on learning experiments and what you hope to gain from this workshop. Include courses you teach for which you'd like to develop learning experiments. Priority will be given to those able to run learning experiments in their courses in the following year.
  2. A brief CV or resume. (A list of publications is not necessary.)
This workshop is funded by the National Science Foundation. Limited funding is available to support travel and/or local expenses. The application includes a section to request this funding. There is no registration fee.

Deadline for full consideration: April 17, 2024.

Summer School and Workshop on Relative Langlands Duality


The relative Langlands program is a generalization of the classical Langlands program from reductive groups to certain homogeneous spaces. The recent work of Ben-Zvi, Sakellaridis, and Venkatesh on relative Langlands duality reveals new connections of the program to algebraic geometry and physics. The summer school and workshop will cover several aspects of the relative Langlands program and explore those new connections.


The priority deadline for applications is Friday, January 26th. We will begin reviewing submissions at that time.

Apply Here

Summer school on Relative Langlands Duality, June 3-5, 2024

Invited Speakers

  • David Ben-Zvi (Austin)
  • Yiannis Sakellaridis (JHU)
  • Lei Zhang (NUS)
  • Chen Wan (Rutgers)
  • Hiraku Nakajima (IPMU)

Workshop on classical, geometric and physics aspects of the Relative Langlands program, June 6-8, 2024

Invited Speakers

  • Gurbir Dhillon (Yale)
  • Ruotao Yang (skoltech)
  • Wang Xiao (Chicago)
  • David Nadler (Berkeley)
  • Hiraku Nakajima (IPMU)
  • Zhilin Luo (Chicago)
  • Spencer Leslie (Boston College)
  • Hiraku Nakajima (IPMU)
  • Charlotte Chan (Michigan)
  • Yiannis Sakellaridis (JHU)
  • Tony Feng (Berkeley)
  • Zhiwei Yun (MIT)
  • Xinwen Zhu (Stanford)


  • Tsao-Hsien Chen (UMN)
  • Dihua Jiang (UMN)
  • Kai-Wen Lan (UMN)
  • David Nadler (Berkeley)


We expect some funding will be available for graduate students and post-docs. More information will be posted in January 2024.

School of Mathematics Event Calendar

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