MEchanics GAthering -MEGA- Seminar: Charting dynamics from data
Event details
| Date | 23.09.2021 |
| Hour | 16:15 › 17:30 |
| Speaker | Daniel Floryan (Mechanical Engineering, University of Houston) |
| Location | Online |
| Category | Conferences - Seminars |
| Event Language | English |
Abstract We often find ourselves working with systems for which governing equations are unknown, or if they are known, they may be high-dimensional to the point of being difficult to analyze and prohibitively expensive to make predictions with. These difficulties, together with the ever-increasing availability of data, have led to the new paradigm of data-driven model discovery.
I will present recent work that fruitfully combines a classical idea from applied mathematics with modern methods of machine learning to learn minimal dynamical models directly from time series data. In full analogy with cartography, we learn a representation of a system as an atlas of charts. This approach allows us to obtain dynamical models of the lowest possible dimension, leads to computational benefits, and can separate state space into regions of distinct behaviours.
Bio Daniel Floryan is the Kalsi Assistant Professor of Mechanical Engineering at the University of Houston. He received his B.S. in mechanical engineering 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. National Committee for Theoretical and Applied Mechanics' inaugural Thomas J.R. Hughes Fellowship. At Houston, Daniel is starting a group working at the intersection of fluid mechanics and nonlinear dynamics.
I will present recent work that fruitfully combines a classical idea from applied mathematics with modern methods of machine learning to learn minimal dynamical models directly from time series data. In full analogy with cartography, we learn a representation of a system as an atlas of charts. This approach allows us to obtain dynamical models of the lowest possible dimension, leads to computational benefits, and can separate state space into regions of distinct behaviours.
Bio Daniel Floryan is the Kalsi Assistant Professor of Mechanical Engineering at the University of Houston. He received his B.S. in mechanical engineering 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. National Committee for Theoretical and Applied Mechanics' inaugural Thomas J.R. Hughes Fellowship. At Houston, Daniel is starting a group working at the intersection of fluid mechanics and nonlinear dynamics.
Practical information
- General public
- Free
Organizer
- MEGA.Seminar Organizing Committee