Teaches math to engineers: https://xitter-newx.xyz-mikolabs.workers.dev/t.co/TJ5i3Pg678 Professor @UW researching #MachineLearning for #Dynamics and #Control, especially for #FluidDynamics.
Joined April 2016
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HydroGym: A Reinforcement Learning Platform for Fluid Dynamics
Now published in Nature!! nature.com/articles/s41586-0…
GitHub: github.com/dynamicslab/hydro…
Amazing collaboration with Christian Lagemann, S Mokbel, M Gondrum, M Rüttgers, Y Wang, P Suárez, L Paehler, D A Bezgin, A B Buhendwa, J L Callaham, S Ahnert, N Zolman, X Shao, J-Ch Loiseau, N A. Adams, M Meinke, W Schröder, K Lagemann, E Lagemann, R Vinuesa & S L Brunton
Steven Brunton retweeted
teaching the SVD this week.
some historical elements i've learned...
beltrami wrote the decomposition down in 1873.
jordan found it independently the next year.
sylvester called the stretches canonical multipliers in 1889.
schmidt proved the best low-rank approximation property in 1907.
by the time eckart & young put the same theorem in psychometrika in 1936, it was already decades old.
what was missing was a way to compute it that didn’t square every number in sight: golub & kahan fixed that in 1965. the version that ran for the next twenty years was golub & reinsch, 1970.
golub drove a car whose license plate read PROF SVD. lol...
Steven Brunton retweeted
A bestiary of chaotic attractors, each carrying its own dihedral Dₙ symmetry.
Every disk holds a different attractor of the generalized Field–Golubitsky map:
z ↦ {a₀ + a₁|z|² + a₂ Re(zⁿ) + a₃|z| Re[(z/|z|)ⁿᵖ]} z + a₄ z̄ⁿ⁻¹
#builtWithMarimo
I really enjoyed taking part in this discussion, especially at this moment in time. Thanks Lex, Alex, and Ankur for the great conversation!
This is an incredible moment in this history of mathematics, computer science, physics & science with some of the hardest problems in human history being solved by AI over a period of weeks. Depending on your perspective, it's either a crisis, a triumph, or both. I don't think anyone knows for sure. We're all trying to make sense of it. I oscillate between fear/dread and optimism/excitement on a daily basis. The rate of progress is insane, including today's announcement from OpenAI of more problems solved.
To help make sense of all of it, here's my conversation with three mathematicians about this moment. Each of them is an expert in the field of each of the biggest problems solved: Navier-Stokes, quasi-Riemann hypothesis, the unique games conjecture and complexity theory more generally.
Ankur Moitra is a mathematician and theoretical computer scientist at MIT, visiting the Institute for Advanced Study in Princeton. Steven Brunton (@eigensteve) is a mathematician and fluid dynamics expert at UW. Alex Kontorovich (@AlexKontorovich) is a mathematician at Rutgers specializing in number theory.
Steven Brunton retweeted
This is an incredible moment in this history of mathematics, computer science, physics & science with some of the hardest problems in human history being solved by AI over a period of weeks. Depending on your perspective, it's either a crisis, a triumph, or both. I don't think anyone knows for sure. We're all trying to make sense of it. I oscillate between fear/dread and optimism/excitement on a daily basis. The rate of progress is insane, including today's announcement from OpenAI of more problems solved.
To help make sense of all of it, here's my conversation with three mathematicians about this moment. Each of them is an expert in the field of each of the biggest problems solved: Navier-Stokes, quasi-Riemann hypothesis, the unique games conjecture and complexity theory more generally.
Ankur Moitra is a mathematician and theoretical computer scientist at MIT, visiting the Institute for Advanced Study in Princeton. Steven Brunton (@eigensteve) is a mathematician and fluid dynamics expert at UW. Alex Kontorovich (@AlexKontorovich) is a mathematician at Rutgers specializing in number theory.
Steven Brunton retweeted
This is a fantastic video explaining orbital dynamics and the resulting economics, and security considerations of cislunar space. Well worth the 8.5 minutes to watch. youtu.be/kdpOdSMzXTA?is=By6z…
Steven Brunton retweeted
Nice to see the Earth-Moon cycler orbits our lab recently discovered featured in @GarretsonPeter's overview of the cislunar space economy. Lots of interesting possibilities for transportation, surveillance, and infrastructure.
This is a fantastic video explaining orbital dynamics and the resulting economics, and security considerations of cislunar space. Well worth the 8.5 minutes to watch. youtu.be/kdpOdSMzXTA?is=By6z…
Steven Brunton retweeted
Launched our new AI Institute in Dynamic Systems, funded with $20M by @NSF! We will push generative AI methods to dramatically reduce the aerodynamic design cycle, together with @Boeing!
aero.engin.umich.edu/2026/10…
#AI4Science #GoBlue!
@eigensteve 🔵 🟡
Steven Brunton retweeted
U-M Prof. @ricardovinuesa is one of the leaders of a new $20M NSF grant to support the AI Institute in Dynamic Systems. Led by the University of Washington, the institute brings together academic and industry partners to develop new ways to model and simulate complex systems.
The @NSF has awarded $20 million to the AI Institute in Dynamic Systems to advance fundamental research on complex robotic manufacturing systems, with an emphasis on aerospace applications.
bit.ly/4zrjuSd
Steven Brunton retweeted
The @NSF has awarded $20 million to the AI Institute in Dynamic Systems to advance fundamental research on complex robotic manufacturing systems, with an emphasis on aerospace applications.
bit.ly/4zrjuSd
The passing of a legend. Less well known is that she coded and simulated the ODEs that Lorenz ended up using for the “Lorenz” system (with Linda Fetter).
We’ve lost an icon. Margaret Hamilton, a computer science pioneer best known for her work at MIT leading development of the flight software for the Apollo missions to the moon, has died at 90. Read about her legacy via MIT News: news.mit.edu/2026/margaret-h…
ALT Margaret Hamilton is reclined inside a NASA spacecraft module, surrounded by control panels and switches.
Steven Brunton retweeted
Very proud of my PhD students Yuning Wang and Pol Suárez Morales. Our recent work on #DRL for turbulence control, HydroGym, has made it to the cover of @Nature!!
Paper: nature.com/articles/s41586-0…
#AI4SCience
Steven Brunton retweeted
It's Fortran Thursday! 🔥
Why does my OpenMP Jacobi stop scaling past 2 threads on a 2048² grid? A roofline model built from 3 likwid numbers predicts it: 279 sweeps/s vs 272 measured. Memory-bound, not a bug.
loiseaujc.github.io/posts/bl…
#Fortran #HPC
Awesome work, and really interesting collaboration!!!
Rivers, pendulums and the thalamus: how the brain balances stable and flexible dynamics, and what changes when consciousness fades.
Our latest journey into how the thalamus is shaping cortical dynamics in @ScienceAdvances 🧵1/10
science.org/doi/10.1126/scia…
Steven Brunton retweeted
Rivers, pendulums and the thalamus: how the brain balances stable and flexible dynamics, and what changes when consciousness fades.
Our latest journey into how the thalamus is shaping cortical dynamics in @ScienceAdvances 🧵1/10
science.org/doi/10.1126/scia…
Steven Brunton retweeted
The Navier-Stokes equations are among the most important — and most challenging — equations in physics. So, what makes them so difficult? And how could a new OpenAI proof finally resolve the problem? Watch our new video: youtube.com/watch?v=PsWR1rQE…
Steven Brunton retweeted
Very nice video by @MichiganAero highlighting the research in the VinuesaLab! Thanks to everyone in my group as well for your excellent work! More on understanding and control turbulent flows and on generative AI for aerodynamic design and optimization!!
youtube.com/watch?v=cbamiovW…
Very cool benchmark environment for robot learning!!
The NSF AI Institute in Dynamic Systems is optimistically developing benchmark environments for learning across the engineering and natural sciences -- try this one out!!
Steven Brunton retweeted
GPT-6 Astra is impressive, but agentic robotics ≠ just control.
Physical agents should control robots, learn new skills, and design their own hardware.
So we introduce RLE-Bench: 48 everyday robotics engineering tasks spanning closed-loop control, policy learning, perception, and mechanical design.
Steven Brunton retweeted
New post: quantifying Gauss-Seidel's loop-carried dependency with OSACA, and a loop-unrolling fix that cuts it from 12 to 2 cycles/element. Three compiler experiments included to isolate the effect from vectorization.
👉 tinyurl.com/3h79t8fn
