Mathematical Modeling podcasts

Neurobiologist Tom Clandinin joins Nicholas Weiler to explore how interacting genetic, cellular and metabolic systems maintain brain health over a lifetime, and how their breakdown contributes to neurodegeneration. The discussion moves beyond single explanations such as inflammation or waste clearance to a systems-level study of brain resilience. Clandinin describes a collaborative programme combining large-scale genetic perturbations in flies and mice with molecular, circuit and behavioural measurements. Computational models will connect these observations across cell types, predict interactions and guide experiments toward potential ways to strengthen the aging brain’s maintenance systems.

Hosted by Nicholas Weiler

Chris Smith presents a research-news episode covering a treatment for prematurely fused infant skull bones, discussion of advanced AI risks, animal-assisted observations in Greenland’s fjords, and a European commercial rocket launch. The surgery segment explains how biomedical modelling and engineered springs supported treatment planning.

Hosted by Chris Smith

Ellen Zapata-Webborn discusses how mathematical research can help predict household energy use. The episode connects patterns in smart-meter data, human behaviour and the demands of electricity systems, illustrating how quantitative models can inform practical energy questions.

Gaute Einevoll talks with Tatjana Tchumatchenko about a mechanistic mathematical model of how neurons minimize energy use by deciding whether ion-channel proteins are produced locally in dendrites or in the soma. The model’s predictions agree with experimental findings.

Joe Hilton explains how health economics and mathematical modelling inform difficult decisions about healthcare resources. The conversation contrasts costly treatments benefiting small groups with interventions serving larger populations, and examines how such trade-offs are assessed. Hilton also discusses his route into research and the experience of beginning work on health policy during the COVID-19 pandemic.

Hosted by Rachel Thomas, Marianne Freiberger

Ulrich Sperhake and Seppe Staelens explain hypothetical boson stars and how researchers use mathematical modelling to investigate them. The discussion connects these unusual compact objects to black holes, gravity and gravitational-wave observations.

Laura Leay interviews MIT’s Carlos Portela about a computational design framework for deformable woven metamaterials. Graphs describe the periodic architecture and how struts interweave at nodes; user-defined helix geometry controls the woven beams. The framework produces files for finite-element analysis and 3D printing, enabling predictions of large-deformation behavior and fabrication of previously inaccessible architectures. The freely available approach connects textile-inspired design with tunable elastic response.

Hosted by Laura Leay

David Dahmen examines how differences between individual neurons affect network function and when homogeneous models miss important behaviour.

Katherine Nagel discusses how fruit flies navigate using odour and how ring models can explain the short-term memory involved.

Tilo Schwalger discusses population-level descriptions of neural dynamics and how mean-field models can be derived from underlying network mechanisms.

Tom Griffiths discusses mathematical accounts of cognition through logic, neural networks and probability. The conversation draws on his book The Laws of Thought to examine how these approaches complement one another, the ideas and people behind them, and prospects for a unified theory of mind.

Taylor Sparks and Oklahoma State University researcher Jake Bair discuss the history and methods of phase-field modelling. They explain how diffuse interfaces represent material transitions and support simulations of crack growth and dendritic structures. The episode links listeners to NIST’s Phase Field Community Hub for further technical resources.

Hosted by Taylor Sparks

Richard Gao discusses fitting spiking-network models to experimental data and dealing with different parameter combinations that explain similar observations.

Hans Ekkehard Plesser discusses reproducibility in computational research through a decade of work with the Potjans-Diesmann cortical network model.

Michael Shadlen develops an account of how thoughts become conscious, drawing on decision-making research and embodied and ecological perspectives. The conversation connects neural activity and drift-diffusion models with unconscious and conscious thought, aiming to identify tractable directions for experimental consciousness research.

Sara Solla discusses how low-dimensional descriptions can reveal structure in recordings from large populations of motor-cortex neurons.

Polina Shichkova discusses models of brain metabolism, including energy supply and the cellular processes that maintain neuronal function.

Tatiana Engel discusses how high-dimensional neural connectivity generates low-dimensional activity associated with cognition. Topics include latent-circuit models, the relationship between manifolds and anatomical networks, brain-wide neuronal timescales and collaborative work through the International Brain Laboratory.

Steven Niederer and Richard Wilkinson discuss personalised mathematical models of patients’ hearts and their potential use in care. The conversation connects digital twins and the CVDNet project with research on representing, calibrating and using uncertainty in predictions. It also traces how this work develops ideas from the earlier Fickle Heart research programme.

Nicolas Brunel discusses excitation-inhibition balance and mathematical explanations of irregular activity in cortical networks.