![The Engineered-Mind Podcast | Engineering, AI & Technology artwork](https://is3-ssl.mzstatic.com/image/thumb/Podcasts113/v4/76/db/78/76db7819-74d4-9661-bd96-3a4ba50d4f6f/mza_6257212625292705640.jpg/100x100bb.jpg)
Steven Brunton - Machine Learning For Fluid Mechanics | Podcast #50
The Engineered-Mind Podcast | Engineering, AI & Technology
English - May 13, 2021 08:26 - 1 hour - 114 MBEducation Homepage Download Google Podcasts Overcast Castro Pocket Casts RSS feed
Dr. Steven Brunton's research focuses on combining techniques in dimensionality reduction, sparse sensing, and machine learning for the data-driven discovery and control of complex dynamical systems. He is also interested in how low-rank coherent patterns that underlie high-dimensional data facilitate sparse measurements and optimal sensor and actuator placement for control. He is developing adaptive controllers in an equation-free context using machine learning. Specific applications in fluid dynamics include closed-loop turbulence control for mixing enhancement, bio-locomotion, and renewable energy. Other applications include neuroscience, medical data analysis, networked dynamical systems, and optical systems.
—————————————————————————————
Connect with me here:
✉️ My weekly email newsletter: jousef.substack.com
🧠 Subscribe for more free videos!
🐤 Follow me on Twitter: @jousefm2
📷 Follow me on Instagram: @jousefmrd
Feel free to support the podcast on Patreon: patreon.com/theengiineer