The past few decades have witnessed rapid advances in the study of dynamics on and of networks, enabling new applications across ecology, epidemiology, neuroscience, infrastructure systems, and beyond. Despite significant progress within individual research communities, a unified mathematical framework for reducing the dimensionality of such systems remains elusive, and connections across communities working on dynamical systems, operator theory, graph limits, scientific computing, and machine learning remain limited. This workshop will bring together researchers around four complementary perspectives on dimension reduction for network dynamics: (i) operator-based methods (Koopman operators, dynamic mode decomposition, Mori-Zwanzig theory); (ii) continuum and density perspectives (graphons, mean-field and kinetic models); (iii) graph-based learning for model reduction (graph neural networks,neural differential equations); and (iv) broader machine learning approaches for nonlinear dynamics (reservoir computing, physics-informed neural networks, deep reinforcement learning). Through a five-day small-workshop format designed for intensive interaction, the workshop aims to identify unified theoretical principles for reduced modeling of large-scale network systems, forge new mathematical connections across currently disparate communities, and catalyze collaborations that bridge rigorous analysis, computation, and data-driven modeling.
In-Person Registration
Seats are limited at the venue, which means that in-person registration may be capped prior to the workshop start date. If capacity is reached, a waitlist will be imposed, which the registration form will reflect. Early registration is strongly encouraged.
All in-person registrants must wait to receive an invitation to attend in-person from IMSI before traveling, which generally begin to be sent out 4-6 weeks in advance.
All registrants (online and in-person) will receive zoom links and are welcome to attend online.
Registration Fee
A non-refundable registration fee will be payable by credit card or debit card for any participants invited to attend this workshop in-person. In-person participants agree to pay the non-refundable fee by the deadline given by IMSI. Failure to pay the fee by the deadline may mean that the invitation to attend in-person is revoked.
IMSI is committed to making all of our programs and events inclusive and accessible.
Contact [email protected] to request
disability-related accommodations.
In order to register for this workshop, you must have an IMSI account and be logged in.