Data Meets Dynamics: Workshop on Data Assimilation for Complex Systems and Applications

August 21–22, 2025 (Thursday–Friday), Discovery Building (330 N. Orchard Street, Madison)

This event is a collaboration with the Data Science Center at Brigham Young University (BYU), a partner of UW IFDS. We sincerely appreciate the generous support of NSF and the Institute for Foundation of Data Science at the University of Wisconsin-Madison.

This workshop brings together researchers and practitioners to explore the broad landscape of data assimilation, emphasizing both theoretical foundations and practical applications. On the theoretical front, the workshop will delve into topics such as nudging data assimilation and its connections to partial differential equations (PDEs), control theory, and error analysis. For practical methods, we will highlight a range of Bayesian data assimilation techniques, including the ensemble Kalman filter and the particle filter, which represent discrete-in-time approaches. Continuous-intime frameworks, such as nudging methods, conditional Gaussian nonlinear data assimilation, and the ensemble Kalman-Bucy filter, will also be discussed, with real-world applications in climate science, atmospheric and ocean modeling, and engineering systems. A key focus of the workshop is to strengthen interdisciplinary connections between data assimilation and tools such as machine learning, stochastic models, parameter estimation, optimal control, and model identification. By fostering discussions among different communities, the event aims to bridge gaps between theory and practice, encourage collaboration, and inspire new research directions. Additionally, the workshop will provide an excellent opportunity for young researchers to gain exposure to various methods, equipping them with tools to address challenges in complex dynamical systems.

The workshop will feature posters and lightning-talk sessions to provide students and junior researchers an opportunity to showcase their work. There will also be a limited amount of financial support for students and junior researchers. For those who want to attend this workshop and give a poster (together with a lightning) presentation, please fill out this form.
If you have any questions, please feel free to contact Dr. Nan Chen (chennan at math.wisc.edu).

Confirmed speakers:

Erik Bollt (Clarkson Univeristy)
Inverse Problems for processing satellite images – remote sensing of ocean.  Smart filters for anisotropic noise characteristic of satellite imagry and specialized for data driven learning of ocean flows.
Elizabeth Carlson (Caltech)
Understanding Large-Time Behavior of Fluid Systems Using Data Assimilation & Optimization
Steven J. Fletcher (Colorado State University)
Non-Gaussian-based variational, Kalman Filters, and Ensemble-based Data Assimilation methods
Pedram Hassanzadeh (University of Chicago)
Learning extreme, rare dynamics from data in high-dimensional multi-scale systems such as weather
Chris Jones (University of North Carolina, Chapel Hill)
Adapting the data assimilation scheme to the computational model
Adam Larios (University of Nebraska–Lincoln)
Data Underground: Assimilation methods for water flow in the soil
Evelyn Lunasin (United States Naval Academy)
Data-Driven Model Identification Using Time Delayed Nonlinear Maps for Systems with Multiple Attractors
Vincent R. Martinez (The City University of New York Hunter College)
Some principles for state and parameter reconstruction in a class of nonlinear dissipative systems
Romit Maulik (Penn State University)
Divide and conquer: Learning chaotic dynamical systems with multistep penalty optimization
Jonathan Poterjoy (University of Maryland, College Park)
TBD
Daniel Sanz-Alonso (University of Chicago)
Long-time accuracy of ensemble Kalman filters for chaotic and machine-learned dynamical systems
Peter Jan Van Leeuwen (Colorado State University)
Nonlinear data assimilation, physical nudging, and machine learning
Jinlong Wu (University of Wisconsin Madison)
Conditional Gaussian Koopman Network for Modeling Complex Systems and Data Assimilation

Confirmed participants:

• Erik Bollt (Clarkson University)
• Elizabeth Carlson (Caltech)
• Steven J. Fletcher (Colorado State University)
• Pedram Hassanzadeh (University of Chicago)
• Chris Jones (University of North Carolina, Chapel Hill)
• Adam Larios (University of Nebraska–Lincoln)
• Evelyn Lunasin (United States Naval Academy)
• Vincent R. Martinez (The City University of New York Hunter College)
• Romit Maulik (Penn State University)
• Jonathan Poterjoy (University of Maryland, College Park)
• Sebastien Roch (University of Wisconsin Madison)
• Daniel Sanz-Alonso (University of Chicago)
• Peter Jan Van Leeuwen (Colorado State University)
• Jinlong Wu (University of Wisconsin Madison)

• Marios Andreou (University of Wisconsin Madison)
• Chuanqi Chen (University of Wisconsin Madison)
• Catherine Ding (Northwestern University)
• Mrigank Dhingra (University of Tennessee at Knoxville)
• Louisa Ebby (North Carolina State University)
• Emmanuel Fleurantin (George Mason University)
• Naureen Ghani (University College London)
• Toan Huynh (Florida State University)
• Hai Van Le (North Carolina State University)
• Brian Manuel (North Carolina State University)
• Charlotte Moser (University of Wisconsin Madison)
• Kaidi Peng (University of Wisconsin Madison)
• Parvathi Kooloth (Pacific Northwest National Laboratory)
• Thea Spigarelli (Brigham Young University)
• Bipin Tiwari (University of Tennessee at Knoxville)
• Shanyin Tong (Columbia University)
• Jason Louis Torchinsky (Sandia National Laboratories, New Mexico)
• Lydia Tolman (Brigham Young University)
• Nathan Waniorek (University of Chicago)
• Zhongrui Wang (University of Wisconsin Madison)
• Nick Wharff (North Carolina State University)
• Xuping Xie (Old Dominion University)
• Yinling Zhang (University of Wisconsin Madison)

Workshop Schedule

Lightning talks/posters (5 mintues each presentation):

August 21 (Thursday):

August 22 (Friday):

Organizers:
Nan Chen (UW-Madison)
Pouria Behnoudfar (UW-Madison)
Jared Whitehead (BYU)
Blake Barker (BYU)