BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Memento EPFL// BEGIN:VEVENT SUMMARY:MEchanics GAthering -MEGA- Seminar: Charting dynamics from data DTSTART:20210923T161500 DTEND:20210923T173000 DTSTAMP:20260407T184057Z UID:89008d03086e3c4c4133f277193b0e546e4e18d4440a9304f822dbb3 CATEGORIES:Conferences - Seminars DESCRIPTION:Daniel Floryan (Mechanical Engineering\, University of Housto n)\nAbstract We often find ourselves working with systems for which gover ning equations are unknown\, or if they are known\, they may be high-dimen sional to the point of being difficult to analyze and prohibitively expens ive to make predictions with. These difficulties\, together with the ever- increasing availability of data\, have led to the new paradigm of data-dri ven model discovery.\n \nI will present recent work that fruitfully combi nes a classical idea from applied mathematics with modern methods of machi ne learning to learn minimal dynamical models directly from time series da ta. In full analogy with cartography\, we learn a representation of a syst em as an atlas of charts. This approach allows us to obtain dynamical mode ls of the lowest possible dimension\, leads to computational benefits\, an d can separate state space into regions of distinct behaviours.\n \nBio  Daniel Floryan is the Kalsi Assistant Professor of Mechanical Engineering at the University of Houston. He received his B.S. in mechanical engineeri ng and B.A. in economics from Cornell University\, and his M.A. and Ph.D. in mechanical and aerospace engineering from Princeton University. Daniel has received Princeton's Porter Ogden Jacobus Fellowship and the U.S. Nati onal Committee for Theoretical and Applied Mechanics' inaugural Thomas J.R . Hughes Fellowship. At Houston\, Daniel is starting a group working at th e intersection of fluid mechanics and nonlinear dynamics. LOCATION:MED 0 1418 https://plan.epfl.ch/?room==MED%200%201418 https://epf l.zoom.us/j/67873367071?pwd=b0NEeWY2MFJqNGUzUitJV256YSt6QT09 STATUS:CONFIRMED END:VEVENT END:VCALENDAR