COMPUTATIONAL RESEARCH in BOSTON and BEYOND (CRIBB)

Welcome! This is an archive page for a previous or upcoming year of the Computational Research in Boston and Beyond Seminar (CRiBB). To see current seminar information visit the Home Page.

To subscribe to a low-traffic mailing list for announcements related to the forum, please visit the CRiB-list web page.

For more information, e-mail Professor Alan Edelman (edelman AT math.mit.edu) and/or Professor Jeremy Kepner (kepner AT ll.mit.edu).

Organizers : 2022

Dr. Patrick Dreher (MIT - Laboratory for Nuclear Science)
Professor Alan Edelman (MIT - Math & CSAIL)
Dr. Chris Hill (MIT - Earth and Atmospheric Science)
Professor Steven G. Johnson (MIT - Math & RLE)
Dr. Jeremy Kepner (MIT - Lincoln Laboratory)
Dr. Albert Reuther (MIT - Lincoln Laboratory)

Meetings : 2022

Meetings will be held virtually via ZOOM on the first Friday of the month from 12:00 PM - 1:00 PM. Upcoming talks are listed below:

https://mit.zoom.us/j/96155042770 | Meeting ID: 961 5504 2770

Jan 7

NO SEMINAR

Feb 4

NO SEMINAR

Mar 4

Justin Finkel (University of Chicago)

"Short weather forecasts inform long-term climatology of sudden stratospheric warming"

Apr 1

Paul Zhang (Massachusetts Institute of Technology)

"Local Decomposition of Hexahedral Singular Nodes into Singular Curves"

May 6

Madelyn Cain (Harvard University)

"Quantum Optimization of Maximum Independent Set using Rydberg Atom Arrays"

Jun 3

Dipti Jasrasaria (University of California,Berkeley)

"Interplay of Surface and Interior Modes in Exciton-Phonon Coupling at the Nanoscale"

Jul 1

NO SEMINAR

Aug 5

Baolin Li (Northeastern University)

"Leveraging Heterogeneous Hardware Resources for Efficient Machine Learning Inference Service"

Sep 2

NO SEMINAR

Oct 7

Christiane Adcock (Stanford)

"Hybrid Modeling for Energy System Simulation and Control"

Nov 4

NO SEMINAR

Dec 2

Kyle Ravi Lennon (Massachusetts Institute of Technology)

"Math, Methods, and Models for Data-Driven Rheology"

Dec 16

Cristina Martin-Linares (The Johns Hopkins University)

Physics-assisted Machine-learning Models in Fluid Mechanics and Agent-based Systems

Archives

Acknowledgements

We thank the MIT Department of Mathematics, Student Chapter of SIAM, ORCD, and LLSC for their generous support of this series.

MIT Math CSAIL EAPS Lincoln Lab Harvard Astronomy

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