[Mathmajors] Jan. 12 1-2pm talk by Prof. Steven Brunton - Machine Learning & Dynamic Systems

[Math & ACMS Student Services Office]

Dear all,

Unfortunately our speaker had to cancel the talk for tomorrow.  We hope to reschedule and will let you know when that happens.

Best regards,

Math & ACMS Advising
Department of Mathematics
Padelford Hall C-36

Drop-in Advising Hours<https://math.washington.edu/advising-academic-support#ZoomDrop-in>
Math and ACMS Blog<https://uwmathandacms.wordpress.com/blog/>
math.washington.edu<https://math.washington.edu/>      acms.washington.edu<http://acms.washington.edu/>

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________________________________
From: Math & ACMS Student Services Office <mathadv at uw.edu>
Sent: Monday, January 9, 2023 8:38 AM
To: mathmajors at uw.edu <mathmajors at uw.edu>
Subject: Jan. 12 1-2pm talk by Prof. Steven Brunton - Machine Learning & Dynamic Systems

Dear Math Majors,

ACMS is hosting a talk that you might be interested in.  Please join us!

Thursday, January 12
Professor Steve Brunton<https://www.me.washington.edu/facultyfinder/steve-brunton> from Mechanical Engineering to talk about machine learning and dynamic systems
1-1:50pm in CSE2<https://www.washington.edu/students/maps/map.cgi?CSE2> G20
All ACMS & MATH majors are encouraged to attend.


Title: Machine Learning for Scientific Discovery


Abstract: Accurate and efficient nonlinear dynamical systems models are essential understand, predict, estimate, and control complex natural and engineered systems.  In this talk, I will explore how machine learning may be used to develop these models purely from measurement data.  We will emphasize techniques that yield models that are interpretable and generalizable, capturing the essential “physics” of the system.  We also discuss the importance of learning effective coordinate systems in which the dynamics may be learned.  This machine learning modeling approach will be demonstrated on a range of challenging modeling problems, for example in fluid dynamics.  Because fluid dynamics is central to transportation, health, and defense systems, we will emphasize the importance of machine learning solutions that are interpretable, explainable, generalizable, and that respect known physics.


We are making an effort to reduce the number of emails you receive from our office.  We do receive a lot of announcements and have been posting those here: https://uwmathandacms.wordpress.com/blog/


Best regards,

Math & ACMS Advising
Department of Mathematics
Padelford Hall C-36

Drop-in Advising Hours<https://math.washington.edu/advising-academic-support#ZoomDrop-in>
Math and ACMS Blog<https://uwmathandacms.wordpress.com/blog/>
math.washington.edu<https://math.washington.edu/>      acms.washington.edu<http://acms.washington.edu/>

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