Links :  UCR Interdisciplinary Center for Quantitative Modeling in Biology

     UCR Math Department seminar

               PDE and Applied Math Seminar

The format of the seminar is hybrid. One might join the seminars in Skye Hall 284 or through zoom link. Please contact Dr. Qixuan Wang (qixuanw@ucr.edu)  for the zoom link.

Winter 2026 

Jan 13, 2:00 PM (Zoom): Dr. Mary Myerscough (University of Sydney)

Jan 20, 2:00 PM:  no seminar

Jan 27, 2:00 PM (Skye 284): Dr. Pooja Flora (UC Riverside)

Feb 3, 2:00 PM (Skye 284): Dr. Qi Wang (San Diego State University)

Feb 10, 11:00 AM (Zoom): Dr. Albert Goldbeter (Université Libre de Bruxelles)

Feb 17, 2:00 PM: no seminar

Feb 20, Friday, 11:00 AM (Skye 284): Dr. Adam MacLean (USC)

Feb 24, 2:00 PM (Skye 284): Dr. Thomas Bury (UCR)

Mar 3, 2:00 PM: Dr. Ritambhara Singh (Brown U)

Mar 10, 2:00 PM: Dr. James Glazier (Indiana U)

Upcoming talks:

Jan 27, 2026, 02:00 PM - 03:00 PM Pacific Time

Dr. Pooja Flora, UC Riverside

Title: Decoding the epigenetic blueprint of stem cell regulation and longevity

Abstract: In adults, the skin constantly renews itself and the stem cells (SCs) of the basal layer (EpSCs) of the interfollicular epithelium and the hair follicle stem cells (HFSCs) residing in the hair follicle bulge are responsible for maintaining tissue integrity, structure, and reepithelization following an injury. However, over an organism’s lifetime these SC pools of the adult skin either lose their vigor or diminish in numbers which manifests into aging-related phenotypes that include epidermal atrophy, fragility, hair loss disorders and delayed wound healing. The fundamental mechanisms that drive SC aging in the adult skin remain largely unknown. To date research in invertebrate and cellular models of aging have shown that there is a change in global occupancy of many histone methylations, and modulation of methyltransferases and demethylases increase organism longevity. While most of these studies have paved the way for us to understand how epigenetic mechanisms influence the aging process, there is a need for addressing if these mechanisms also contribute towards aging of a mammalian tissue. My preliminary in vivo loss-of-function studies indicate that the conserved epigenetic regulators, Polycomb repressive complexes (PRCs), may be functioning differentially in the HFSCs and EpSCs to maintain their longevity in the adult skin. This is particularly intriguing in light of the fact that genome-wide studies have implicated that the modulation of chromatin accessibility in aged HFSCs establish a transcriptional landscape that promotes aging. The goal of this project is to add to these correlative observations and elucidate if epigenetic regulators and their corresponding histone modifications have a functional role in safeguarding SC longevity in the skin. 

Bio: Pooja Flora is an Assistant Professor in the Department of Molecular, Cell, and Systems Biology at the University of California, Riverside. She received her Ph.D. in Biological Sciences from the University at Albany, SUNY, where her thesis focused on transcriptional and post-transcriptional regulation of Drosophila oogenesis. She then conducted postdoctoral research at the Icahn School of Medicine at Mount Sinai, where her work centered on the epigenetic regulation of skin stem cells. In her own lab, Pooja utilizes comparative approaches that span classical genetics, cellular and molecular biology, and multi-omics analyses across model systems to uncover the functional epigenetic mechanisms that govern epithelial function and tissue longevity.

Feb 3, 2026, 02:00 PM - 03:00 PM Pacific Time

Dr. Qi Wang, San Diego State University

Title: Physics-Constrained Flow Reconstruction and Event Identification via Adjoint-Based Domains of Dependence

Abstract: Turbulence governs fluid motion across a wide range of spatial and temporal scales, posing fundamental challenges for modeling, estimation, and control. Accurate reconstruction of turbulent flow states from limited observations is essential for both scientific understanding and engineering applications. While laboratory experiments and numerical simulations each provide partial insight, their optimal integration remains a central challenge. We present a physics-constrained framework that systematically incorporates experimental measurements into computational flow models through adjoint-based optimization. The resulting inverse problem is formulated as a constrained optimization problem, with gradients obtained from the discrete adjoint of the governing equations. This approach enhances model fidelity, reduces uncertainty, and enables accurate flow state estimation from sparse data. We demonstrate the method in a turbulent channel flow, reconstructing the flow field using limited measurements. 

Beyond state estimation, we show that the adjoint sensitivity and the associated Hessian naturally define the first- and second-order sensitivities of measurements, which together characterize the domain of dependence of a sensor. This perspective provides a powerful interpretation of measurement data and reframes flow-event identification as a geometric search problem in space and time. We apply this formulation to several canonical problems, including localization of a steady scalar source, identification of vortex sources in potential and laminar flow around an airfoil, and detection of heat sources in laminar stratified channel flows. Finally, we examine how adjoint sensitivities in turbulent flows expose fundamental limitations in flow reconstruction from sparse measurements, particularly as the estimation time horizon increases. These results highlight intrinsic challenges in turbulence estimation and provide possible pathways for future data assimilation strategies by stabilizing the adjoint fields.

Bio: Dr. Qi Wang’s research lies at the intersection of turbulence, inverse problems, and physics-informed machine learning. He develops physics-constrained and adjoint-based methods for interpreting sparse measurements and reconstructing complex flow dynamics, with applications ranging from scalar and vortex source localization to turbulent flow reconstruction and hypersonic boundary-layer diagnostics.

Previous talks:

Jan 13, 2026, 02:00 PM - 03:00 PM Pacific Time

Dr. Mary R. Myerscough, School of Mathematics and Statistics, University of Sydney

Title: The Mathematics of Lipids and Cells:

Modelling the Development of Atherosclerotic Plaques

Abstract: Atherosclerotic plaques are fatty accumulations in the inside of the walls of major arteries.  They are the principal cause of ischaemic heart attacks, strokes and peripheral vascular disease.  Their formation is driven by chronic inflammation, which is initiated and fuelled by the presence of cholesterol-bearing modified low density lipoproteins in the vessel wall.

Atherosclerosis, like cancer, is a major cause of death and disease world-wide.  Unlike cancer, it has not, to date, been well-studied by mathematical biologists and other modellers, and in particular the cellular and immune processes, that drive plaque formation, maturation and ultimately plaque fate, have not been widely modelled.

In scientific research, plaques must be grown inside an experimental animal and each plaque can be viewed at just a handful of time points.  In clinical practice, plaques in humans are usually only observed at the late stage when clinical complications occur.  Hence there is a clear role for modelling and simulation in understanding the dynamics of plaques and the factors that influence their growth or regression. 

In this talk, I will present research on ODE and PDE models for immune cell populations and the lipid (cholesterol) that they contain. In particular, I will present work exploring the effect of timing in raising the level of high density lipoprotein (HDL which carries “good cholesterol”); structured population models for macrophages that include lipid trafficking; and a model to explore the outcomes of phenotypic changes in plaque smooth muscle cells.

Bio: Mary completed her undergraduate and masters study at the University of Sydney.  She undertook doctoral studies at the Centre for Mathematical Biology at Oxford where she was supervised by Professor Jim Murray on a project on cell chemotaxis.  She returned to Sydney to a postdoc at Macquarie University in the School of Chemistry.  During this contract, she was introduced to modelling social insects. (Is a hanging stationary bee swarm like a burning lump of coal?  Answer: Yes, sort-of.)  Consequently, she spent the next part of her research career modelling ants, bees and termites until about 2008 when she returned to cell biology and started modelling the growth of atherosclerotic plaques.  Mary is currently Professor of Mathematical Biology in the School of Mathematics and Statistics at the University of Sydney.