Seminars
October 2026
KIPAC Seminar: Large-scale structure between peaks - modeling the intergalactic medium for the next generation of cosmological datasets
Jamie Sullivan· MIT
Mon, Oct 12 · 18:00 UTC · Online
Galaxy images and spectra map large-scale cosmic structure and constrain fundamental physics. While galaxy-clustering bias models are well developed, forthcoming datasets can also trace the intergalactic medium and recover complementary cosmic-web information. Jamie Sullivan discusses models for both neutral and ionized intergalactic material. Neutral-hydrogen work includes the environments of Lyman-alpha emitters at redshifts 2.5–5, relevant to future DESI extensions and Spec-S5, together with the measured Lyman-alpha forest and an observationally practical compression of its bispectrum. Ionized-gas research studies momentum through an effective-field-theory kinetic Sunyaev–Zel’dovich bispectrum, and density through fast-radio-burst clustering and cross-correlations. Together, these approaches aim to map intergalactic modes alongside galaxy tracers and improve precision cosmological constraints.
AstrophysicsCosmologySeries: Kavli Institute for Particle Astrophysics and Cosmology, Stanford University
Anderson Localization in Periodic Elastic Systems with Random Perturbations
Wei Wu· Jilin University, China
Fri, Oct 9 · 03:00 UTC · Online
This seminar investigates Anderson localization in subwavelength elastic periodic systems with random perturbations. For the unperturbed structure, layer-potential methods recast the eigenvalue problem as boundary integral equations, yielding asymptotic expressions for subwavelength eigenvalues and establishing a band gap above the subwavelength band. A Floquet transform then brings the perturbed problem into a periodic formulation and produces equations for resonant frequencies under general perturbations. Numerical experiments on monomer and dimer structures test agreement with the analysis. Increasing the strength and number of random perturbations demonstrates localization, providing a mathematical basis for elastic metamaterial design.
PhysicsSolid MechanicsSeries: Department of Applied Mathematics, The Hong Kong Polytechnic University
Building a Brain, One Cell at a Time: Reading the Developmental Instructions Behind Human Neural Diversity
Tom Nowakowski· UCSF
Wed, Oct 7 · 20:00 UTC · Cambridge, United States
Tom Nowakowski explains lineage barcoding and single-cell sequencing approaches for reconstructing neural stem-cell family trees and early wiring programs in developing mouse and human brains.
TMS in Autism Spectrum Disorder: From Pathophysiology to Development of Novel Therapeutic Protocols
Lindsay N. Oberman· National Institute of Mental Health, Developmental Clinical Neurophysiology and Neurostimulation Research Program
Wed, Oct 7 · 20:00 UTC · Online
Lindsay N. Oberman reviews evidence for transcranial magnetic stimulation protocols in autism spectrum disorder. The seminar first explains how TMS works and how it can probe the brain mechanisms associated with autism. It then presents NIH research using repetitive TMS as an experimental therapeutic tool, examining its effects on both brain function and behaviour to guide the development of potential interventions. Online via Duke Zoom. Wednesday 7 October 2026, 16:00 EDT (America/New_York; UTC−4). Register through the event-specific Register Here link on the Duke Autism Seminar Series page to receive remote access. The presentation will not be recorded. Accommodation requests should reach the organizer at least ten days before the event. The speaker directs NIMH’s Developmental Clinical Neurophysiology and Neurostimulation Research Program.
High tech and no tech: intention and pedagogy in a modeling-based calculus course
Marty Weissman· University of California, Santa Cruz
Tue, Oct 6 · 16:00 UTC · Online
Marty Weissman presents a University of California, Santa Cruz course that develops mathematics for the life sciences through models of biological dynamics. Adapted from UCLA’s LS30 course, it integrates calculus, dynamical systems and linear algebra. The seminar describes the curriculum and its active learning discussion sections, where deliberate choices range from custom dynamical-system simulators to paper exercises and blackboard work. Drawing on two years of teaching, Weissman reflects on which approaches appear to support student learning and the development of the teaching team.
MathematicsMathematics EducationSeries: Online Seminar on Undergraduate Mathematics Education (OLSUME)
Human balance: Delays, sensory dead zones and micro-chaos!
John G. Milton· The University of Texas at Austin
Tue, Oct 6 · 16:00 UTC · Online
How do humans stabilize an inverted pendulum, and why does a balanced pole eventually fall? Drawing on 25 years of fingertip pole-balancing research, this talk examines neural correction delays: longer poles move more slowly relative to the nervous system’s response time. Delay-differential models can stabilize the upright position, yet skilled people still experience falls. The proposed explanation is microchaos arising from interactions among delay, sensory dead zones and frequency-dependent force encoding. A region of transient falling solutions lies next to stable microchaotic dynamics. Such microchaos is absent in virtual frontal-plane balancing tasks, while models of standing postural sway lack the corresponding transient regime. The comparison suggests that human falls, unlike pole falls, are more plausibly associated with medical events or slips and trips.
Deciphering the cortical output code – A multiscale approach to predictive brain modelling
Mon, Oct 5 · 07:30 UTC
To orchestrate complex behaviors in mammals, the cerebral cortex must continuously transmit its processing results to subcortical regions. While internal cortical processing relies on highly selective sparse codes, these descending cortical output streams employ an enigmatic dense code, characterized by high firing rates and low feature selectivity. This dense population code presents a profound paradox: how can downstream regions extract precise, cognitively relevant signals when most cortical output neurons can be active at any moment? We address this paradox by testing the hypothesis that cortex does not lose information when switching to a dense code. Instead, it utilizes a mechanism for sparse-to-dense coding transformations discovered by my laboratory: thalamocortical synapses target specifically the dendritic initiation zone for calcium action potentials (APs), which enables cortical output neurons to transmit multiple information streams simultaneously via a multiplexed 1-2-3 AP syntax. I will provide first evidence that this remarkable synaptic specificity and coding syntax generalize across long-range pathways. Information coupling via an anatomically and biophysically distinct dendritic nexus may hence be a ubiquitous mechanism for sparse-to-dense coding transformations in cortex. Dissecting these mechanistic origins of cortical output streams is only now possible due to a unique in vivo – in silico approach, perfected over two decades, that my laboratory developed for bridging the gaps between dendritic and population-level computations
September 2026
Machine Learning with Hard Constraints
Navid Azizan· Massachusetts Institute of Technology — Mechanical Engineering and Institute for Data, Systems & Society
Wed, Sep 30 · 16:00 UTC · Online
Navid Azizan presents methods that make neural models obey physical, safety and operational constraints at deployment. Hard-constrained neural networks, or HardNets, enforce input-dependent constraints by construction while preserving universal approximation within the feasible function class. Applications include models of chaotic dynamics with bounded trajectories, energy-constrained operator learning, safe reinforcement learning and control with formal guarantees. The talk then turns to enforcing constraints during sampling from pretrained diffusion and flow-matching models. Formulating generation as trajectory optimization allows receding-horizon control to guide outputs toward feasibility without retraining or imposing excessive restrictions on the sampling process. Examples from fluid dynamics, robot planning and control, PDE control and language-guided image editing illustrate how constraints can define admissible behavior while retaining expressive learning and generation.
Machine LearningDeep LearningSeries: Georgia Institute of Technology — Machine Learning Seminar Series
The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks
Lenka Zdeborová· École Polytechnique Fédérale de Lausanne (EPFL)
Wed, Sep 30 · 15:00 UTC · Online
Lenka Zdeborová introduces the Rules-and-Facts model, in which some observations follow a shared rule while others are isolated exceptions requiring memorization. The framework studies when a learner can acquire the rule and retain those exceptions simultaneously. Its results emphasize how capacity is organized and deployed, rather than capacity alone. The talk examines how regularization and the geometry of kernels or learned feature maps can reserve resources for memorization without undermining rule learning. It connects the balance between abstraction and memory to architectural and algorithmic choices, providing a theoretical account of neural networks that both generalize and recall specific facts.
How dark matter halos get their cusps
Uddipan Banik· Perimeter Institute for Theoretical Physics
Recorded
Uddipan Banik derives a dynamical account of dark-matter halo density profiles using the Boltzmann–Poisson equations for an expanding Universe populated by subhalos of many masses. A self-similar solution links density slope to halo mass growth; including gravitational scattering and subhalo capture gives gamma = 6/(s + 2). Initial collapse with s = 2 produces a prompt cusp of slope 3/2. Hierarchical growth connects the slope to the primordial power spectrum and recovers the Syer–White relation during matter domination. Stable clustering selects an inner Navarro–Frenk–White cusp of slope one, while stalled accretion approaches the outer slope of three. The framework connects these profiles to successive stages of halo assembly.
The paradox of the corpus callosum: insights from the developing brain
Vanessa Siffredi· Lausanne University Hospital (CHUV) and University of Lausanne (UNIL)
Tue, Sep 29 · 07:30 UTC · Hôpital des Enfants, Geneva · Hybrid
Vanessa Siffredi explores why the corpus callosum is central to typical brain development, yet some children born without it or with callosal abnormalities develop comparably to their peers. The talk connects callosal structure and communication between hemispheres with cognition, attention, executive function, memory, language and socio-emotional development. Structural and functional neuroimaging studies of typical development and callosal dysgenesis examine how developing brains compensate for alterations in this major white-matter pathway. Siffredi is affiliated with CHUV and UNIL; Carole Guedj chairs the seminar. Hybrid: Auditoire de pédiatrie Fred Bamatter, HUG, Hôpital des Enfants, Geneva; online via Zoom. Tuesday 29 September 2026, 09:30–10:30 CEST (Europe/Zurich; UTC+2), followed by CIBM news and networking until 11:00. Organized by CIBM Center for Biomedical Imaging — Breakfast and Science. In-person attendance is free without registration. Remote attendees must register through the Zoom link on the event page and select the 29 September occurrence.
Stability and Bifurcations in a Free Boundary PDE Models of Cell Motility
Leonid Berlyand· Pennsylvania State University
Thu, Sep 24 · 19:00 UTC · Princeton, United States
Leonid Berlyand discusses mathematical models for the onset of cell motion driven by myosin contraction. A two-dimensional free-boundary PDE model links cell-shape evolution to diffusion and Keller–Segel-type transport. The talk examines linear stability, a stability-determining eigenvalue and the way nonlinear diffusion changes the bifurcation from supercritical to subcritical. It also considers the curvature of the bifurcation curve, connections to bistability, and the role of non-self-adjoint operators. An example illustrates why a spectral gap alone need not guarantee stability. This is an in-person Analysis of Fluids and Related Topics seminar at Princeton.
Taillte May investigates how unstable black-hole quasinormal-mode spectra affect observed gravitational-wave signals. Small changes in a gravitational potential can substantially shift the frequencies normally used to test astrophysical black holes. A simple time-domain model reveals a delay before those shifts appear, tied to the echo travel time between the perturbation and the main potential. In the perturbative regime, the frequency change after one echo agrees with the conventional frequency-domain prediction. Beyond that regime, the intermediate waveform cannot be represented by a single constant frequency shift.
Creating Periodic Orbits of Reeb Vector Fields in Three Dimensions
Michael Hutchings· Institute for Advanced Study
Tue, Sep 22 · 18:00 UTC · Princeton, United States
Michael Hutchings introduces Reeb vector fields and explains why their periodic orbits are substantially better understood in three dimensions through Seiberg-Witten theory. The colloquium develops Irie's closing lemma, which creates a periodic orbit through a selected region after a small perturbation, and discusses a quantitative refinement connecting the perturbation size to an upper bound on the orbit period.
Early Sleep Biomarkers of Alzheimer's Disease Pathophysiology and Memory Impairment
Bryce Mander· UC Irvine School of Medicine
Fri, Sep 18 · 19:00 UTC · Stanford, United States
Bryce Mander presents research on early sleep biomarkers associated with Alzheimer's disease pathophysiology and memory impairment. The William C. Dement Seminar connects sleep and circadian neuroscience with neurodegeneration, cognition and clinically relevant approaches to detecting disease-related change.
Gravitational waveform modeling with physics informed neural networks and surrogates
Nils Deppe· Cornell University
Thu, Sep 17 · 15:00 UTC · Princeton, United States
This seminar discusses a proof-of-concept gravitational-waveform model described in arXiv:2511.10522. It augments post-Newtonian equations using physics-informed neural-network methods and universal differential equations. The talk also covers ongoing development of a precessing surrogate model designed to evaluate in less than one millisecond while covering a broader portion of the LVK frequency band.
Kirk Public Lecture | An operator-algebraic perspective on topological orders
Yoshiko Ogata· Kyoto University
Wed, Sep 16 · 15:00 UTC · Cambridge, Cambridge
Kirk Public Lecture at the Isaac Newton Institute by Yoshiko Ogata (Kyoto University) on how macroscopic properties of matter emerge from quantum particle interactions and the classification of topological order from an operator-algebraic perspective in mathematical physics.
Applied MathematicsMathematical ModelingSeries: Isaac Newton Institute for Mathematical Sciences, University of Cambridge
Canonical Quantization of Singular Configuration Spaces: Symmetry Reduction, Mass Gap Bounds, and Non-smooth Calculus
Luca Mrini· University of Vienna
Thu, Sep 10 · 18:30 UTC · Waterloo, Canada
Luca Mrini presents work in progress on quantising singular configuration spaces using the non-smooth calculus of metric-measure spaces. The framework generalises smooth quantum mechanics through Hilbert spaces, position and momentum operators, Hamiltonians, unitary dynamics, and observable algebras. A method for bounding mass gaps after symplectic reduction uses the curvature of the unreduced configuration space. Examples include the harmonic oscillator constrained to zero angular momentum, lattice Yang–Mills theory, and fractional-dimensional Laakso spaces. The talk closes with prospective applications to the Yang–Mills mass-gap problem and quantum gravity.
Changing Perspectives on Self Control
Yuko Munakata· University of California, Davis
Wed, Sep 9 · 20:00 UTC · Cambridge, United States
Yuko Munakata presents evidence challenging capacity-only accounts of self-control and explains how experience, effort, and expected payoff shape executive-function engagement and later outcomes.
Learning and memory in the infant brain
Nick Turk-Browne· Yale University
Tue, Sep 8 · 14:30 UTC · New York, United States
Nick Turk-Browne presents research using infant functional MRI to investigate how the hippocampus supports learning and memory early in life. The seminar connects neural development, memory formation and infantile amnesia through new methods for studying awake infants.