We present Panda: a foundation model for nonlinear dynamics pretrained on 20,000 chaotic ODE discovered via evolutionary search. Panda zero-shot forecasts unseen ODE best-in-class, and can forecast PDE despite having never seen them during training (1/8) arxiv.org/abs/2505.13755

Releasing the Energy-Book 🔋 from its first appendix's chapter, where I explain how I create my figures. 🎨 Feel free to report errors via the issues' tracker, contribute to the exercises, and show me what you can draw, via the discussion section. 🥳 github.com/Atcold/Energy-…

Plankton of symmetric attractors Made with #sympy #numpy #matplotlib

🎉 Honored to be selected as the Donald R.F. Harleman Keynote Speaker at the #IAHRWorldCongress in Singapore! I'll present our work on turbulence control with explainable deep learning, where #AI meets #WaterScience & #Ecohydraulics. Looking forward! 🌊🤖 #XAI #FluidMechanics

We now have another open Ph.D. position at ETH Zurich in data-driven nonlinear reduced-order modelling, with applications in system ID and control. Interested candidates may apply here: jobs.ethz.ch/job/view/JOPG_…

Today, NSF announced an add’l 500 NSF Graduate Research Fellowship Program awardees for the 2025-2026 cohort, bringing the total to approx 1,500. #NSFGRFP supports grad students as they pursue their dreams, build STEM skills, & become the next generation of innovators & leaders.

Apply to Our New Online Graduate Certificate: Data-Driven Dynamical Systems & Controls! 4 Brand New Courses: Foundations of Data-Driven Dynamics & Controls Data-Driven Dynamic Systems Data-Driven Controls Data-Driven Sensing me.washington.edu/future-student… App deadline: July 1, 2025

🌀Just out in Nature Machine Intelligence: Can generative AI enhance fluid simulations? We explore how diffusion models enable fast, interpretable, stochastic flow modelling, reshaping the simulation pipeline. 📝 With Luca Guastoni 🔗 nature.com/articles/s4225… #FluidMech #AI #DiffusionModels

The final chapter of my book is on autoencoder neural networks. This lecture starts with the theory: youtube.com/watch?v=tn61dh…

Honored to receive the 2025 Harleman Lecture Award at the #IAHR2025 World Congress in Singapore 🇸🇬 Grateful to the IAHR community and proud to contribute to the future of AI for fluid mechanics! #AI #ML #FluidMechanics #Sustainability #Singapore

100k on my mathematics channel !! 🥹 what video should i do to celebrate?

🎉 Great news: Our Machine Learning and Physical Sciences workshop at NeurIPS Conference will be back again this year! 🎉 Keep an eye out for updates on deadlines etc, we will be updating the website soon ml4physicalsciences.github.io #ML4PS2025 Machine Learning And The Physical Sciences

New Book & Video Series!!! (late 2025) Optimization Bootcamp: Applications in Machine Learning, Control, and Inverse Problems Comment for a sneak peak to help proofread and I'll DM (proof reading, typos, HW problems, all get acknowledgment in book!)

General relativity 🤝 neural fields This simulation of a black hole is coming from our neural networks 🚀 We introduce Einstein Fields, a compact NN representation for 4D numerical relativity. EinFields are designed to handle the tensorial properties of GR and its derivatives.

Honored to be featured in BBC Future’s article: “How aircraft designers are beating rising turbulence” ! ✈️ Proud to play a part in pushing aviation safety forward with XAI and DRL!! BBC bbc.com/future/article… #FlightTech #Turbulence #ClimateAction #AviationInnovation

I've done it! I've finished the complete series of video lectures to complement my book. Here's the last one on model identification with autoencoders: youtube.com/watch?v=cFpyjE…

🧠💨 New from #VinuesaLab in Communications Engineering (Nature Portfolio): We use multi-agent #DRL to control 3D turbulent flows, achieving up to 21% drag reduction on cylinders! First-ever MARL training on 3D cylinders 🚥 🌀 Stabilized wakes 💡 Efficient control 🔗 nature.com/articles/s4417…

What if a spacecraft could cycle between Earth and Moon orbits, performing multiple circuits of each, naturally and indefinitely, with zero propulsion? We’ve discovered a new class of stable, prograde, low-energy cycler orbits that do just that. Why these orbits matter:

New Video Series: Statistics & Data Analysis! youtube.com/watch?v=QIXUTs… 35 videos, 10 hours: Random sampling, Central limit theorem, Distribution estimation, Method of moments, Maximum likelihood estimation, Hypothesis testing, Monte Carlo sampling, Bayesian statistics, and more!

I now have a full YouTube playlist of video lectures with coding demonstrations that accompanies every chapter of my book! Check it out here: youtube.com/watch?v=A1AvIj…