Links :  UCR Interdisciplinary Center for Data-driven Modeling in Biology

     UCR Math Department seminar

               PDE and Applied Math Seminar

The format of the seminar can be either in-person or online. If on zoom, please contact Dr. Mykhailo Potomkin (mykhailp@ucr.edu)  for the zoom link.

Spring 2026 

April 7 - Organizational meeting 

April 14, 2:00 PM, Dr. Alex Safsten, University of Maryland

April 28, 2:00 PM, Dr. Nicholas Battista, The College of New Jersey

May 1, 12:00 PM - Jointly with UCR RAISE Center by Daniele E. Schiavazzi, University of Notre Dame

May 5, 2:00 PM, Dr. Saverio E Spagnolie, University of Wisconsin-Madison

May 13 - Jointly with Departmental Colloquium by Dr. Alex Mogilner, New York University

May 19, 2:00 PM, Dr. Christopher Strickland, University of Tennessee, Knoxville

May 26, 2:00 PM, Dr. Jia Gou, University of California, Riverside

June 2, 2:00 PM, Dr. Bradford E. Peercy, University of Maryland, Baltimore County

Upcoming talks:

Tuesday, May 05, 2026, 02:00 PM - 03:00 PM Pacific Time

Dr. Saverio E Spagnolie, University of Wisconsin-Madison

Title: Unifying Active Matter in Complex Fluids

Abstract: Decades of work have unearthed a dizzying array of emergent phenomena when active particles interact through viscous and complex fluids. In this talk we will seek to unify a broad spectrum of systems, from active suspensions in Newtonian fluids to individual active particles in confined or bulk complex flows, using three key dimensionless parameters. The first is the Deborah number, which compares the timescales of particle activity and environmental relaxation; the second is a similar comparison but of length scales, which we term the Benes number; and the third is the active particle volume fraction. 

Motivated by this map to navigate towards new research areas, we will present a mean-field theory describing the dynamics of active suspensions in bulk viscoelastic and anisotropic environments, which predicts the emergence of arrested, flowing states, traveling waves, breathing modes, and dramatic thrashing modes; and we will identify a key parameter which bridges the gap between active nematics, and active suspensions in Newtonian fluids.

Bio: Dr. Saverio E. Spagnolie is an applied mathematician known for his work on biological and bio-inspired systems, including the motion of microorganisms, active matter, and complex fluids. He is a professor of mathematics at the University of Wisconsin-Madison, where he contributes to both research and graduate training in applied mathematics. Before joining the University of Wisconsin-Madison, Dr. Spagnolie obtained his Ph.D. from the Courant Institute and held postdoctoral positions at the University of California, San Diego, and Brown University. 

Dr. Anton Peshkov, California State University Fullerton

Title: Collective states of the nematode T. aceti (the talk is tentatilvely postponed to Fall)

Abstract: My research group experimentally studies the collective behavior of the nematode T. Aceti, which are able to synchronize their body oscillations across thousands of individuals to produce metachronal waves. In this collective state, they exert a strong pushing force at the front as well as create a fluid flow at the back with their tails.  I will show how my group tries to instrumentalize these forces to produce many novel collective states in different geometries. We use this force to deform a flexible boundary between two fluids, where we discover several novel states. We also study the collective motion of nematodes in oils, where we find that they can form propagating filaments that branch and connect, forming complex networks reminiscent of the ones formed by neurons. We will also discuss the challenges that exist to model these systems.

Previous talks:

 Friday, May 01, 2026, 12:00 PM - 1:00 PM Pacific Time, Location: MRB seminar room, 1st floor

Daniele E. Schiavazzi, University of Notre Dame

Title: Model Synthesis for Scientific Agents

Abstract: Applications of generative modeling and deep learning in physics-based systems have traditionally focused on building emulators - computationally inexpensive approximations of input-to-output maps. However, the remarkable flexibility of data-driven architectures opens opportunities to broaden their scope to include model inversion and identifiability analysis. We present InVAErt networks, a framework for data-driven analysis and synthesis of parametric physical systems. Through numerical experiments, we demonstrate the framework's versatility across a wide range of problems, including linear systems of equations, spatio-temporal PDEs, and lumped-parameter physiological models. We further introduce an extension for systems with observational noise, enabling the separation of structural from practical identifiability in complex ill-posed inverse problems. Finally, we discuss recent efforts to integrate InVAErt networks with large language model agents for applications in cardiovascular health.

Tuesday, April 28, 2026, 02:00 PM - 03:00 PM Pacific Time

Dr. Nicholas Battista, The College of New Jersey

Title: Fishes Go MOO: Pareto analysis across 6-dimensional design space

Abstract: Aquatic organisms display an incredible range of swimming strategies, even within a common mode like body-caudal fin (BCF) propulsion. This raises a fundamental question: what drives that diversity?

In this work, we explore the biomechanics of BCF swimming by mapping performance trade-offs in a six-dimensional design space. To do this, we built a numerical framework that combines computational fluid dynamics, machine learning, multi-objective optimization (MOO), and global sensitivity analysis. We identify Pareto-optimal trade-offs between key performance measures, where clear patterns begin to emerge. We also find that multiple combinations of kinematic parameters can achieve similar performance, revealing both redundancy and sensitivity in the system. Together, these results provide a mechanistic explanation for the diversity of swimming patterns observed in fish, and offer new insight into how physical and evolutionary constraints may shape swimming behavior and design.

Tuesday, April 14, 2026, 02:00 PM - 03:00 PM Pacific Time

Dr. Alex Safsten, University of Maryland

Title: Spatio-Temporal Population Dynamics for Interacting Species: Vector Control & Predator-Prey

Abstract: I will present two PDE models for interacting animal species. My first model is for mosquito population control. Mosquitoes top the list of the deadliest animals in the world due to the diseases they carry and transmit to humans, most importantly, malaria. The sterile insect technique (SIT), which entails the periodic mass release of sterilized male mosquitoes into an environment where adult female mosquitoes are abundant, is one of the main promising approaches being proposed to suppress the populations of malaria-spreading mosquitoes. I will use a two-species model of SIT to see how an SIT program can leverage interspecies competition between mosquito species to replace a species of high vectorial capacity with a species of low vectorial capacity. Using this competition, I will show that SIT can locally eradicate malaria-carrying mosquito species at a much lower cost (in terms of the number of sterile males released) than using SIT alone. Second, I will present a PDE model for predator-prey interactions in which the predators' range is a subset of the prey's range. If the predators' range is too large, they may over-hunt the prey whereas if their range is too small, they will not have enough prey available to be able to support a large population. I will show how the existence of nontrivial equilibrium solutions can be proved despite the challenge of having coupled PDEs in different domains, and numerical results showing a rich family of behaviors from solutions of this model. I will address the question of, given a domain for the prey species, what is the subset of that range for the predator species that maximizes the predator population?

Bio: Dr. Safsten specializes in partial differential equations in mathematical biology, with an emphasis on free-boundary problems. Applications of his work include cell motility, tissue dynamics, and, more recently, animal and human population dynamics. He received his Ph.D. in Mathematics from the Pennsylvania State University and is currently a Novikov Postdoctoral Fellow at the University of Maryland.