What can honeybees teach us about building a healthier planet — and a sustainable business? Dr. Noah Wilson-Rich, CEO of The Biodiversity Lab and founder of Urban Bee Lab and The Best Bees Company, grew a backyard beekeeping project into a nationwide research network powering insights for NASA, MIT, Harvard, and beyond. Today, through The Biodiversity Lab’s strategic consulting and Urban Bee Lab’s nonprofit research, Noah is expanding that mission to help communities and organizations design actionable solutions at the intersection of science, sustainability, and impact. In this talk, he will share how bees serve as living sensors of biodiversity and climate change — and the lessons he’s learned about entrepreneurship at the crossroads of business, sustainability, and science.

Ten minutes for your mind@2:50 every day at 2:50 pm in multiple time zones:Europa@2:50, EET, Athens, Helsinki (UTC+2) (7:50 am EST) https://us02web.zoom.us/j/88298032734Atlantica@2:50, EST, New York, Toronto (UTC-4) https://us02web.zoom.us/j/85349851047Pacifica@2:50, PST, Los Angeles, Vancouver (UTC=7) (5:50 pm EST) https://us02web.zoom.us/j/85743543699Almost everything works better again if you unplug it for a bit, including your mind. Stop by and unplug. Get the benefits of mindfulness without the fuss.@2:50 meets at the same time every single day for ten minutes of quiet together.No pre-requisite, no registration needed.Visit the website to view all @2:50 time zones each day.at250.org or at250.mit.edu

Date: Thursday, November 6, 2025 Time: 4:00 pm – 5:00 pm Location: Singleton Auditorium (Third floor of MIT Building 46)Title: The dynamics of the geometry of abstractionAbstract: Neurons in the mammalian brain often exhibit complex, non-linear responses to multiple task variables (mixed selectivity). Despite the diversity of these responses, which are seemingly disorganized, it is often possible to observe an interesting structure in the representational geometry: task-relevant variables are encoded in approximately orthogonal subspaces in the neural activity space. This encoding is a signature of low-dimensional disentangled representations, it is typically the result of a process of abstraction and allows linear readouts to readily generalize to novel situations. We show that these representations are observed in multiple brain areas in human and non-human primates. We then studied how the geometry changes during the decision-making process in 5 different brain areas (the hippocampus, dorsolateral prefrontal cortex, anterior cingulate cortex, orbitofrontal cortex, and the amygdala) of non-human primates, and how the analysis of the geometry dynamics can be used to understand the underlying neural mechanisms. We finally show how the representational geometry changes with learning in humans. Collaboration with the Salzman and Rutishauser groups.Bio: Stefano Fusi was born in Florence, Italy, and graduated in 1992 from the Sapienza University of Rome with a degree in physics. After his degree, he obtained a researcher position at the Italian National Institute for Nuclear Physics in Rome and started to work in the field of theoretical neuroscience. In 1999, he received a Ph.D. in physics from the Hebrew University of Jerusalem, Israel, and moved to the University of Bern, Switzerland, as a postdoctoral fellow. After visiting Brandeis University as a postdoctoral fellow in 2003, in 2005 he was awarded a professorial fellowship by the Swiss National Science Foundation and became an assistant professor at the Swiss Federal Institute of Technology in Zurich (ETHZ), Switzerland. In 2009, he joined the Department of Neuroscience at Columbia University, where he is now a Professor of Neuroscience.

A series of talks on OR-related topics. For more information see: https://orc.mit.edu/seminars-events/

Speaker: Javier Gomez-Serrano (Brown University)

Speaker: John Pardon (Simons Center for Geometry and Physics)Title: Log derived moduli spaces of pseudo-holomorphic curvesAbstract: I will sketch the construction of a canonical log derived smooth manifold structure on moduli spaces of pseudo-holomorphic curves. This provides a convenient language for the construction and manipulation of enumerative and Floer homotopical invariants. Derived smooth manifolds form an infinity-category, which may be obtained from the (ordinary) category of smooth manifolds by freely adjoining finite infty-limits, modulo transverse limits. The derived smooth structure on moduli spaces of pseudo-holomorphic curves comes from a (quite tautological) moduli functor on derived smooth manifolds (the main result is thus that this functor is representable). Log smooth manifolds (essentially defined by Melrose, and recently developed further by Parker and Joyce) are used to capture in precisely what sense moduli spaces of pseudo-holomorphic curves are "smooth" near maps from nodal domain curves. Combining these notions yields "log derived smooth manifolds".