More from Events Calendar
- Apr 291:30 PMWomen's Health (WHx) Program Seminar Series | Talk 2: Linda GriffithMice, or Microfluidics? Humanizing Biomedical Research, Inspired by Women’s Health ChallengesJoin us for the second seminar series event hosted by the Women's Health Program (WHx) at the MIT Media Lab, featuring Linda Griffith, who is Professor of Teaching Innovation at the MIT School of Engineering and director of the MIT Center for Gynepathology Research.Dr. Canan Dagdeviren, head of the Conformable Decoders research group and WHx Faculty Lead, will moderate the event. The WHx seminar series is supported by the WHx program and the Program in Media Arts and Sciences (MAS).
- Apr 292:00 PMMeditationJoin us for a rejuvenating 30-minute meditation session led by an experienced Buddhist monk.This weekly session is open to the MIT community and offers a peaceful break to manage stress, ease frustration, and enhance focus. By practicing mindfulness meditation, you'll not only boost your compassion, energy, and productivity but also connect with like-minded peers who share a passion for mental wellness. Sessions feature light meditation guidance and time for silent practice.Whether you're new to meditation or an experienced practitioner, this session provides a supportive space to cultivate inner peace and resilience. Don't miss this opportunity to recharge and foster a mindful community.
- Apr 292:30 PMOrganizational Economics SeminarTBA | Anna Sanktjohanser (Toulouse)
- Apr 292:30 PMPhysical Mathematics SeminarSpeaker: Miles Couchman (York University)Title: Turbulent mixing in stratified flowsAbstract:Understanding how turbulence enhances the irreversible mixing of scalars in density-stratified fluids is a central problem in industrial and geophysical fluid dynamics. For instance, accurately parametrizing turbulent heat transport within the ocean is a leading area of uncertainty in climate modelling. We here present a series of data-driven approaches for quantifying the spatiotemporal distribution of mixing hotspots and structures in turbulence datasets.First, we describe an unsupervised clustering technique for analyzing oceanographic data, highlighting that traditional analyses may significantly underestimate mixing generated by rare, extreme events. We then consider mixing in complementary direct numerical simulations, revealing the importance of stable anisotropic density interfaces embedded within the flow. Finally, we introduce a dimensionality-reduction algorithm for classifying experimental videos of stratified flow instabilities, leading to a cluster-based network model quantifying turbulent transition pathways.Collectively, our findings highlight that extreme mixing events have the potential to dominate bulk mixing statistics. Current parametrizations of turbulent heat transport may thus be skewed by undersampled measurements, resulting in a focus on the most common, but not necessarily the most significant, events.
- Apr 292:45 PMMIT@2:50 - Ten Minutes for Your MindTen 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
- Apr 293:00 PMPDE/Analysis SeminarSpeakers: Xuerui Yang (University of Illinois, Urbana-Champaign)Title: On the Gauss Circle ProblemAbstract: The circle problem has been a notorious problem in number theory. It boils down to derive an effective bound on certain two-dimensional exponential sum over the integer ring. I will talk about how to connect this pointwise bound problem to a mean-value-estimate problem. Then, I will explain how decoupling theory can help us solve the mean value problem.