Seminars

Srinivasan Keshav (University of Cambridge) presents an interface designed to help ecologists use AI for remote sensing despite unfamiliarity with embeddings and algorithms. The Tessera Embeddings Explorer lets practitioners privately explore a region of interest, create habitat maps and perform regressions using their domain expertise and ground-truth knowledge. The talk demonstrates the tool and explains the design principles and the software architecture that follows from them, connecting usable ecological workflows with AI representations. Keshav is the Robert Sansom Professor of Computer Science at Cambridge.

Alok Puranik (Jane Street) examines data mixing for large language models: allocating model capacity and computation among training sources. A small model’s preferred data mix may differ from that of a larger model, yet the cost of large-model training forces many decisions to depend on smaller experiments. Scaling laws can predict performance as size and computation increase only when trends remain stable or change predictably. The talk uses experiments from Puranik’s work and frontier laboratories to examine data-mix questions that violate these assumptions, explain why small-scale results can mislead, and explore better methods for choosing training data. His research at Jane Street concerns scaling laws for sequence models in trading.

Cryopreservation constrains manufacturing and clinical delivery of immune cells such as NK and T cells. DMSO protects against freezing but becomes toxic at physiological temperatures; associated infusion morbidity can require washing or divided dosing that diminishes therapeutic effectiveness. This talk presents an alternative in which reversible, cytocompatible hydrogels encapsulate cells before freezing without DMSO. The speaker examines evidence that encapsulation cushions osmotic stress, suppresses kinetic and phase transitions, and reduces injury caused by extracellular ice growth and fusion. The discussion covers recovery efficiency, function after thawing, control of biological stress responses, and the challenges of extending the approach to clinical-scale cell preservation.

Ivo D. Dinov examines augmented intelligence as a partnership between people and computational systems. The talk traces the technical and philosophical development of neural networks, then introduces complex-time, or kime, representations and the inference methods they support. Applications include medical imaging, healthcare and economic forecasting. It also considers the academic mission, societal consequences of AI and tensions between rapid technical development and human values, framing mathematical AI methods as extensions of human reasoning. Free hybrid seminar hosted by Wayne State University's Institute for AI and Data Science, AIDaS: CAD Seminar Series. Wednesday 30 September 2026, 14:30–15:30 EDT (America/Detroit; UTC−4). Attend in Room 1146, Faculty/Administration Building, 656 W. Kirby, Detroit, MI 48202, USA, or use the Zoom link on the official event page. Researchers, practitioners, students and faculty are welcome; the organizer encourages in-person attendance.

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.

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.

Charlie Wilson examines how artificial intelligence affects energy transitions and carbon emissions, from data centres to the wider economy. The talk evaluates evidence behind competing claims, identifies optimism bias in assessments extending beyond data-centre electricity use, and presents research quantifying AI’s effects on global emissions pathways to 2050. It considers how aligning AI development with climate action changes the feasibility and cost of meeting long-term climate targets. Wilson is Professor at the Environmental Change Institute, University of Oxford. Takeshi Kuramochi provides commentary; Naoko Shimazu moderates. Online via Zoom Webinar. Wednesday 30 September 2026, 14:00–15:00 JST (Asia/Tokyo; UTC+9). Public advance registration is required through the organizer’s event page. The lecture is in English with Japanese interpretation. Organized by Tokyo College, The University of Tokyo Institutes for Advanced Study.

Peter Meikle, Bernie Pope and Tingting Wang present the Australian Cardiovascular disease Data Commons (ACDC). Some heart attacks occur without established risk factors, and repeat events remain common despite optimal treatment. ACDC addresses this gap by securely pooling multi-omics, imaging and longitudinal outcomes from approximately 400,000 people in 18 Australian cohorts. The webinar explains cloud infrastructure, data harmonisation and federated standards based on Gen3; how integrated genomic, multi-omics and imaging cohorts support new risk markers and polygenic risk-score testing; and how the platform can move diagnostic research towards clinical practice. Meikle and Wang are at the Baker Heart and Diabetes Institute; Pope is at Australian BioCommons. Online via Zoom. Wednesday 30 September 2026, 12:00–13:00 AEST (Australia/Melbourne; UTC+10). Free, with advance registration through the official event page. Intended for life scientists, bioinformaticians, cardiovascular clinicians, data custodians and medical data scientists. Parts may be recorded; the Australian BioCommons Code of Conduct applies. Organized by Australian BioCommons.

MIT Biology Colloquium Series talk by Peter Koo (Cold Spring Harbor Laboratory), hosted by Yunha Hwang, on using AI to learn the gene regulatory code.

Mansi Chhajed examines how the move from home sleep patterns to disrupted hospital sleep relates to cognitive outcomes after surgery. The session combines longitudinal sleep measurements with clinical assessments of postoperative delirium to identify baseline markers of vulnerability and consider practical ways to improve recovery. It connects sleep architecture, biological and environmental influences, and preoperative risk with proactive, sleep-informed patient care. Chhajed is a Clinical Research Coordinator at Massachusetts General Hospital. Online via Zoom Webinar. Tuesday 29 September 2026 at 14:00 ET / 13:00 CT (America/New_York; EDT, UTC−4). Organized by the Sleep Research Society — Virtual Seminar Series. Follow Register Today on the organizer's page to the event-specific Zoom form, which requests name and email. The form is publicly accessible; advance registration supplies webinar access.

Irene Rombel discusses how artificial intelligence and machine learning can address bottlenecks, quality issues, and production costs in cell, gene, and RNA therapy manufacturing. The seminar focuses on real-world process-development applications that improve reproducibility, speed, and cost effectiveness.

Paco Villaescusa examines how simulations and artificial intelligence change the extraction of physical knowledge from precision cosmological surveys. The talk asks how much information lies in large-scale structure beyond power spectra, including nonlinear scales and higher-order statistics, and introduces the Quijote and Backlight simulation programmes. It then addresses the uncertain astrophysical processes that complicate small-scale inference through CAMELS, a framework combining cosmology, galaxy formation and machine learning. DREAMS is presented as a route to predicting dark-matter observables while accounting for baryonic uncertainties. The final part considers coupling simulations with increasingly capable AI: Denario is introduced as an agentic research system that generates hypotheses, designs analyses, writes and executes code, interprets results and refines research directions. The discussion considers what coordinated populations of agents and simulations spanning physical scales could make possible.

Merav Ahissar examines how expertise emerges through learning the statistics of task-relevant stimuli. Slow learning builds familiarity with stable regularities, such as syllable patterns in language, while fast adaptation supports flexible responses to changing situations, including surprising social interactions. The talk considers atypical learning dynamics in dyslexia and autism and how these may explain difficulties in linguistic and social skill acquisition, respectively. The discussion draws on Gertsovski and Ahissar, Trends in Cognitive Sciences, 2026. Speaker: Merav Ahissar, Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem. Organized by Cornell Cognitive Science. Friday 25 September 2026, 15:00–16:30 America/New_York (EDT). Attend online through the public Join via Zoom link on the official event page; the link opens Zoom’s app and browser join options. Cornell advertises the source event as hybrid, but this listing covers the verified online attendance route.

Mark Harnett presents work on how synaptic organization, nonlinear dendritic processing, and neuronal activity patterns interact to support computation, flexibility, and learning in the adult mammalian neocortex. The Brain and Cognitive Sciences colloquium is followed by a reception.

Farhad Danesh examines how mitochondrial reactive oxygen species, altered metabolism and structural remodelling convert hyperglycaemia into progressive kidney injury. The seminar connects mitochondrial dynamics with diabetic microvascular damage, non-coding RNA regulation and experimental models that establish causal links to disease progression. Genome-wide CRISPR screens and spatial metabolomics reveal cellular gene-regulatory and metabolic changes. Integrating these approaches with molecular genetics, genomics and epigenomics, the work seeks therapeutic targets to prevent diabetic kidney disease progressing to kidney failure. Hybrid: New Research Building Auditorium, Georgetown University Medical Center, Washington, DC, and Zoom. Thursday 24 September 2026, 16:00–17:00 EDT (America/New_York; UTC−4). Use the public event registration form to arrange attendance, or follow its Zoom link for remote participation. Organized by Georgetown’s Distinguished Scientist Seminar Series. Danesh is Professor of Medicine and Chief of Nephrology at MD Anderson.

Bowen Li explains how ionizable lipids are designed for lipid nanoparticles that deliver messenger RNA. The seminar covers combinatorial and machine-learning-guided design, four-component reactions for rapidly producing lipid libraries, and barcoded screening in living systems to identify formulations targeting organs and cells, including lungs, T cells and tumours. It then examines applications of AI-guided nanoparticle platforms to mRNA therapeutics. Li is an Associate Professor and Canada Research Chair at the University of Toronto's Leslie Dan Faculty of Pharmacy. Online via Zoom. Thursday 24 September 2026, 11:00–12:00 Eastern Daylight Time (America/New_York; UTC−4). Use Join via Zoom on Western University's event page. The stated audience includes researchers, students, alumni and the general public. Organized by Western University's Western Bioinformatics Research Seminar.

Florian Marquardt surveys approaches to reducing the energy and computational cost of neural networks by implementing their functions in physical devices. The central question is how experiments can efficiently determine updates to adjustable parameters, allowing the hardware itself to learn. Examples include learning through time reversal, obtaining nonlinear computation from linear optical scattering, and training analog quantum simulators as neuromorphic systems. The seminar is available in person and through the registration link on the organizer’s event page.

Qihao Ye examines practical, affordable ways for individual mathematicians to use AI in literature searches, proof development and verification. The talk identifies seven recurring failure modes and introduces the open-source QED multi-agent system designed to address them. A case study on constructing Carleman weights for wave equations on the half-line shows how automated search can be combined with a researcher’s mathematical insight and rigorous checking. The organizer links both the implementation and the accompanying research paper. Online via Rutgers DIMACS Zoom. Wednesday 23 September 2026, 10:00–11:00 EDT (America/New_York; UTC−4). Use the Zoom link and passcode on the official event page. Organized by the DIMACS AI and Mathematics Seminar. This listing advertises the verified remote attendance option.

ISTA Lecture by Klaus Robert Müller (TU Berlin & Korea University, Seoul) on how machine learning and AI enable scientific research, particularly in medicine and chemistry, and on explainability techniques for extracting understanding from machine learning models.

Stanford Neurosciences Seminar Series talk by Emery Brown (Massachusetts Institute of Technology, Neuroscience Statistics Research Lab) on deciphering the dynamics of the unconscious brain under general anesthesia, hosted by the Wu Tsai Neurosciences Institute.