Links :  UCR Interdisciplinary Center for Quantitative 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. 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, CANCELLED: 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:

February 24th 2026, 02:00 PM - 03:00 PM Pacific Time

Dr. Thomas Bury, UCR

Title: Combining dynamical systems and deep learning for early warning of critical transitions in cardiac systems

Abstract: The human heart is a complex dynamical system that can undergo critical transitions to abnormal rhythms, known as cardiac arrhythmias. Predicting when such transitions will occur remains a major challenge. In this talk, I will demonstrate how deep learning can be combined with mechanistic mathematical models of cardiac dynamics to (i) improve prediction of an arrhythmia precursor known as alternans (a beat-to-beat oscillation in cardiac activity), and (ii) uncover dynamical mechanisms that can lead to arrhythmia onset. We validate these approaches in vitro using heart cell aggregates and monolayers. I will argue that the rapid development of cardiac monitoring technologies is creating exciting opportunities at the interface of cardiology, dynamical systems, and machine learning.

Bio: - Undergraduate and Masters in Math at Uni of Cambridge

- PhD in Applied math from University of Waterloo

- Postdoc at McGill in Dept. of Physiology where I worked with experimentalists and clinicians to study the nonlinear dynamics of cardiac arrhythmia.

- Joined UCR as an Assistant Prof in the Math dept. at beginning of January

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

Dr. Ritambhara Singh, Brown University

Title: Optimal Transport Methods for Understanding Single-Cell Dynamics and Gene Regulation

Abstract: Understanding cellular development and gene regulation requires analyzing how cells change over time. In this talk, I will present two complementary computational methods that leverage optimal transport and temporal single-cell data to uncover developmental dynamics and regulatory mechanisms. First, I will introduce OTVelo, a method for inferring gene regulatory networks from time-stamped single-cell gene expression data. We estimate gene velocities using optimal transport, then infer regulation through time-lagged correlation and Granger causality via regularized linear regression. Overall, OTVelo reveals how regulatory relationships evolve across time points. Next, I will present scMultiNODE, an unsupervised integration method for combining single-cell gene expression and chromatin accessibility measurements across developmental timepoints. While multi-modal profiling offers comprehensive insights into cell development, obtaining multiple measurements from the same cells is resource-intensive, limiting joint analysis. scMultiNODE integrates these disparate measurements while preserving both cell type identity and developmental dynamics. The method employs scalable Quantized Gromov-Wasserstein optimal transport to align cells across modalities, then uses neural ordinary differential equations to explicitly model continuous developmental trajectories in a shared latent space. Together, these methods demonstrate how optimal transport and dynamical systems modeling can unlock new insights from temporal single-cell data, advancing our understanding of both gene regulation and cellular development.

Bio: Ritambhara Singh is an Associate Professor of Computer Science and Data Science and a member of the Center for Computational Molecular Biology at Brown University.  Her research lab develops machine learning methods with the goals of data integration and model interpretation for biological and biomedical applications. Prior to joining Brown, she was a post-doctoral researcher in the Noble Lab at the University of Washington. She completed her Ph.D. in 2018 from the University of Virginia with Dr. Yanjun Qi as her advisor. Ritambhara has received the NHGRI Genomic Innovator Award and Brown University’s Richard B. Salomon Faculty Research Award for developing deep learning methods to integrate and model genomics datasets. She has also received the Dean’s Award for Excellence in Teaching at Brown. She recently received the NSF CAREER award for developing integrative and explainable machine learning methods for heterogeneous health-related datasets.

Previous talks:

February 20th, 2026, Friday, 11:00 AM - 12:00 PM Pacific Time

Dr. Adam MacLean, University of Southern California

Title: Modeling and inference of gene regulatory network dynamics to reveal the fates of single cells

Abstract: Cells make decisions to enable multicellular life. Cell fate decision-making underlies development and homeostasis, and goes awry as we age. Despite great promise, we have yet to harness the high-resolution information on cell states and fates that single-cell genomics data offer to understand cell fate decisions in development and aging. Nor do we know how these fate decisions are controlled by gene regulatory networks. I will describe our recent work constructing mathematical models of cell fate decisions and how they are controlled by gene regulatory networks, informed by single-cell genomics. In application to the human lifetime, we have discovered how early-life events -- mutational, transcriptional, and epigenetic -- shape and change stem cell function as we age in a manner that could be harnessed to ameliorate cancer and diseases of aging.

Bio: Dr. Adam MacLean develops theory to understand cell fate decision-making in hematopoietic stem cells (HSCs) and cancer. He has developed models of cell-cell communication, and the gene regulatory networks that control cell fate decisions via single-cell multi-omics data analysis and statistical inference. Recent work from the MacLean lab has discovered a gene regulatory circuit controlling HSC quiescence that is disrupted by aging, and has shown how variants arising before birth can explain HSC clonal dynamics late in life.

Adam is an Assistant Professor in the Department of Quantitative and Computational Biology, at the University of Southern California. He studied mathematical physics (BSc) at the University of Edinburgh, and completed a PhD in systems biology from Imperial College London. He worked as a postdoc at the University of Oxford and the University of California Irvine, before joining USC in 2019. Recent grants supporting his work include an NSF CAREER Award and an NIH R35 MIRA award.

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.

Feb 10, 2026, CANCELLED

Dr. Albert Goldbeter, 

Unit of Theoretical Chronobiology, Faculté des Sciences, 

Université Libre de Bruxelles (ULB), Brussels, Belgium

Title: The cell cycle and the circadian clock: Dynamics of two coupled cellular rhythms

Abstract: The cell cycle and the circadian clock are two major cellular networks which appear to be coupled. The circadian regulatory network has been studied first in Drosophila and Neurospora, and then in mammals. Models for the circadian network show that it can produce sustained oscillations in constant conditions, and be entrained by the light-dark cycle. The model for the mammalian circadian clock accounts for the effect of mutations leading to sleep disorders such as the familial advanced sleep phase disorder (FASPS) or the non-24h sleep-wake cycle disorder corresponding to the absence of entrainment. The cell cycle regulatory network has been studied first in amphibian embryos and yeast, and later in mammalian cells. Models for the embryonic and mammalian cell cycles show that they are driven by oscillations in the activity of cyclin-dependent kinases (Cdks). The dynamical consequences of the bidirectional coupling of the two oscillatory networks have been studied by merging models for the mammalian circadian clock and for the network of cyclin-dependent kinases (Cdks) that drives the mammalian cell cycle. Compared to unidirectional coupling, which results in the entrainment of one oscillator by the other, bidirectional coupling of the cell cycle and the circadian clock greatly enhances the robust synchronization of the two cellular rhythms. The model further predicts the possibility of a coexistence between multiple modes of synchronization characterized by different synchronization periods.

Bio: After completing his studies in Chemistry and his PhD at the Université Libre de Bruxelles (ULB, Brussels, Belgium), Albert Goldbeter did postdoctoral work at the Weizmann Institute of Science (Rehovot, Israel) and a research stay at UC Berkeley, before returning to ULB, where he is now honorary Professor. He held visiting professorships at UC Berkeley, at the university of Paris XI-Orsay in France, and in China (Fudan University, in Shanghai, Nanjing Agricultural University, and Soochow University, in Suzhou). His research mainly pertains to modeling the molecular mechanism of cellular rhythms, including circadian clocks in Drosophila and mammals, the cell cycle in amphibian embryos and mammalian cells, and the bidirectional coupling of the cell cycle and the circadian clock. He is the author of several books, including Biochemical Oscillations and Cellular Rhythms. The molecular bases of periodic and chaotic behaviour (Cambridge University Press, UK).

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.

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.