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Bernat Font

@fontb.bsky.social
359 followers 293 following 63 posts

Assistant Professor in Data-Informed CFD at TU Delft. Interested in turbulent flow simulations 🌀 data-driven models 🤖 numerical methods ∫→∑ and high-performance computing ⚡️. I generally talk about open source, music, and science.

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Graham Kendall @grahamkendall.bsky.social · 13/11/2025
The inner workings of a paper mill: deevybee.blogspot.com/2025/11/the-...
buff.ly
The inner workings of a paper mill:
My Norxin sting operation Guest post by Csaba Szabo Chair of Pharmacology, University of Fribourg, Switzerland   After the limited success ...
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Bernat Font @fontb.bsky.social · 28/09/2025
the best things are also thanks to fluid dynamics!
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Lorena A Barba @labarba.bsky.social · 26/09/2025
𝗖𝗼𝗺𝗲𝘁 𝗿𝘂𝗻𝘀 𝗰𝗶𝗿𝗰𝗹𝗲𝘀 𝗮𝗿𝗼𝘂𝗻𝗱 𝗝𝘂𝗽𝘆𝘁𝗲𝗿 Friends, I watched an AI agent complete my students' coding exercises in real-time, and I'm shook 🤯 I tested Perplexity's Comet browser on a Jupyter notebook with eigenvalue problems I assigned to my class… (video at the bottom of this thread)
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Bernat Font @fontb.bsky.social · 26/08/2025
Slides for the talk avaliable here! b-fg.github.io/EFDC2_2025/m... I'm loving this quarto + reveal.js for creating html presentations. Now that's portable!
b-fg.github.io
main
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Bernat Font @fontb.bsky.social · 25/08/2025
Tomorrow at noon, I will be presenting at EFDC2 in Dublin! I will talk about our new mesh-free SINDy framework, collaboration with M. Gao and N. Kutz, for system dynamics identification on unstructured, scarce, and noisy data 🗓️ Session: tinyurl.com/c7up564z 🔗 Preprint: arxiv.org/abs/2505.16058
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Adrian Hill @adrianhill.de · 25/08/2025
Just noticed my "Julia for Machine Learning" course got 2^8 stars on GitHub, yay! 🎉 github.com/adrhill/juli...
github.com
GitHub - adrhill/julia-ml-course: Julia Programming for Machine Learning course at TU Berlin
Julia Programming for Machine Learning course at TU Berlin - adrhill/julia-ml-course
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JuliaCon 2026 @juliacon.org · 23/07/2025
Exciting talks, brilliant minds, and a community that keeps pushing the boundaries of what’s possible with Julia.#JuliaCon2025 #JuliaLang #OpenSource #ScientificComputing #DayOne #CommunityVibes #TechConference #JuliaCommunity
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Bernat Font @fontb.bsky.social · 22/07/2025
The WaterLily.jl article is now available on Computer Physics Comms! @gabrielweymouth.bsky.social and I review our CFD solver's design, performance, accuracy, and also show some very cool examples (like the one below). Check it out! 🔗 doi.org/10.1016/j.cpc.2025.109748 #CFD #GPU #HPC #JuliaLang
CFD simulation of a whale tail
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Gabriel Weymouth @gabrielweymouth.bsky.social · 18/06/2025
Want to see what the flow past a semi-infinite array of randomly shifted and scaled circles looks like? I did too! Code is modified from the examples here: github.com/WaterLily-jl... #JuliaLang
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Bernat Font @fontb.bsky.social · 17/07/2025
I am happy to share that I have been awarded a Dutch Research Council (NWO) Veni personal grant! www.nwo.nl/en/news/200-...
nwo.nl
200 researchers receive Veni grants | NWO
Identifying when children are most at risk of being taken into care within youth protection programmes. Improving the quality of surgery with video analysis. The interaction between wind and vegetation for optimising the resilience of coastal dunes. Developing reliable algorithms for statistical learning with interactive decision science. These are four of the two hundred research projects by researchers who have been awarded a Veni grant. Each researcher will receive a maximum of 320,000 euros. The grant is an incentive for adventurous, talented and groundbreaking researchers to further develop their own research ideas over the next three years.
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Tiina Roose @tiinaroose.bsky.social · 16/07/2025
Today’s vibecode achievement using @gabrielweymouth.bsky.social WaterLily. We went from 10 cylinders to 100 in no time at all; all on a standard laptop #vibecoding #julia #waterlily
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JuliaHub @juliahub.bsky.social · 02/07/2025
Makie v0.24 is out! One of the biggest architectural updates yet—bringing better performance, cleaner internals, and new plotting capabilities. A big step toward Makie 1.0. makie.org/website/blog... #JuliaLang #OpenSource #Visualization #Plotting #HPC #MakiePlots #WGLMakie #Makie
makie.org
Makie v0.24 focuses on a comprehensive overhaul of our internal architecture, specifically replacing Observables in our backend code with a more robust system. This fundamental change touches nearly every component of the codebase, making it one of our most ambitious refactoring efforts to date.
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Steven Strogatz @stevenstrogatz.com · 23/06/2025
Dear #mathsky, if you repost this, it will let people see the article for free. Thanks! www.nytimes.com/interactive/...
nytimes.com
How Bees, Beer Cans and Data Solve the Same Packing Problem (Gift Article)
Trying to fit it all in? There’s a trick to it, even in 24 dimensions.
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Bernat Font @fontb.bsky.social · 06/06/2025
making #quarto slides can be a bit painful, but the end result is amazing. Feels like #Beamer, but it comes with the benefits of #markdown and #html
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Bernat Font @fontb.bsky.social · 29/05/2025
LLMs with uncertainty quantification output with be nice too
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Bernat Font @fontb.bsky.social · 25/05/2025
New WaterLily version is out 🌀! github.com/WaterLily-jl... #JuliaLang #CFD #GPU #LES 1/2
Flow past the Julia logo
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Bernat Font @fontb.bsky.social · 23/05/2025
Our latest preprint on "Mesh-free sparse identification of nonlinear dynamics" is out! In collaboration with Mars Gao and Nathan Kutz, we explore a novel SINDy framework to uncover dynamical systems from scarce, noisy, and non-uniformly sampled data. 🔗 arxiv.org/abs/2505.16058 #SINDy #PDE #SciML #ML
Mesh-free SINDy framework and 1D Burgers' equation as example.
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Bernat Font @fontb.bsky.social · 14/05/2025
#Overleaf is down and some are freaking out about a deadline coming right up... The standard work-local & push-to-remote approach is clearly not as widespread as I thought!
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Guillaume Dalle @gdalle.bsky.social · 12/05/2025
How to make #autodiff user-friendly? What lies beyond the safety of Python-world? Why does it matter for scientific machine learning? All this, and more, in our latest preprint with @adrhill.bsky.social! Spoiler alert: it describes the most useful software I ever wrote. arxiv.org/abs/2505.05542
A comparison of automatic differentiation paradigms between Python and Julia:
- In Python, one chooses the autodiff framework first (PyTorch / JAX), then the appropriate scientific library
- In Julia, one writes the scientific library first, then one tries to make it compatible with several autodiff frameworks (Enzyme, Zygote, etc)
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Bernat Font @fontb.bsky.social · 05/05/2025
WaterLily and @makie.org make a great team! #CFD #JuliaLang #GPU #DataViz
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JuliaHub @juliahub.bsky.social · 14/04/2025
Say goodbye to vendor lock-in in GPU programming! Learn how Julia + KernelAbstractions.jl make writing fast, portable GPU code across architectures easier than ever. youtu.be/QvlBmh1t9I4 #JuliaLang #GPU #HPC #AI #ML #CUDA #OpenCL #DeepLearning #OpenSource
youtu.be
Vendor Neutral GPU Programming in Julia
YouTube video by JuliaHub
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dave @beesandbombs.bsky.social · 14/04/2025
:)
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Bernat Font @fontb.bsky.social · 31/03/2025
This seminar is now available in our YouTube channel. Check it out! 🔗 youtu.be/ly7mBFf8esM
youtu.be
Large-Scale CFD seminar series 8. Dr. Francesc Verdugo
YouTube video by Large-scale CFD
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Guillaume Dalle @gdalle.bsky.social · 27/03/2025
Fellow #JuliaLang enthusiasts, here's your chance to shine: the call for proposals of JuliaCon Local Paris 2025 is finally open. Send us your coolest, nerdiest contributions and we'll prepare a scientific program for the ages! pretalx.com/juliacon-loc...
The logo for JuliaCon Local Paris 2025. Pretty cool tbh.
Design by cormullion.
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Bernat Font @fontb.bsky.social · 27/03/2025
Reminder for today's seminar at 5pm CET!
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Bernat Font @fontb.bsky.social · 26/03/2025
using an explicit LES model and a central difference scheme for the convective flux, we match nicely experimental results from the 70s! (doi.org/10.1017/S002...) Results with N=64^3 cells and Smagorinsky-Lilly turbulence model
Energy cascade of decaying homogeneous isotropic turbulence with N=64^3 cells
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Bernat Font @fontb.bsky.social · 20/03/2025
We would like to invite you to join the next Large-scale CFD online seminar by Dr. Francesc Verdugo (UV Amsterdam) on "Large-scale sparse linear algebra with PartitionedArrays" github.com/PartitionedA... Date: 27/03/2025, 5pm CET Seminar link: tinyurl.com/4hy47ezv #HPC #MPI #JuliaLang
Abstract: We present PartitionedArrays, a large-scale sparse linear algebra library fully implemented in the Julia programming language. The key differentiating feature of PartitionedArrays with respect to related libraries is that it introduces an alternative programming model to implement its distributed algorithms. This model allows one to decouple the logic behind data partition and communication from the number of processing units used to run the code. A logically distributed algorithm can be run both on a single and multiple process. This delivers an improved balance between code productivity and performance in the development of large-scale scientific computing applications. The parallel logic can be debugged on a single process, avoiding deadlocks, race conditions, and other practical challenges of debugging parallel code, and permits using standard sequential debuggers. At the same time, the resulting code can be deployed on a supercomputer with performance similar of native MPI-based applications. PartitionedArrays provides distributed linear algebra data structures (vectors and sparse matrices), and key computational kernels (distributed sparse matrix-vector product and sparse matrix-matrix products), as well as distributed algebraic multigrid preconditioners. These tools have been successful in the implementation of finite element solvers scaling to tens of thousands of CPU cores. In this presentation, we show the software design of PartitionedArrays and a hands-on overview to its main features. The source code of the library is freely available at https://github.com/PartitionedArrays/PartitionedArrays.jl.
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Bernat Font @fontb.bsky.social · 14/03/2025
S'ha quedat un bon divendres www.youtube.com/watch?v=RVZV...
youtube.com
Sin Exagerar
YouTube video by O'Funk'illo - Topic
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Guillaume Dalle @gdalle.bsky.social · 11/03/2025
Fellow #JuliaLang enthusiasts in Europe, I've got 4 words for you. JuliaCon Local Paris 2025 Yes, it's happening. Like the global @juliacon.bsky.social event, but with more croissants. Stay tuned!
juliacon.org
JuliaCon Local Paris 2025
JuliaCon Local Paris 2025
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Bernat Font @fontb.bsky.social · 12/03/2025
Playing a bit with our WaterLily.jl #CFD #JuliaLang solver and homogeneous isotropic decaying turbulence 🌀 128^3 grid running on my local #GPU ⚡ visualizing in real-time with @makie.org github.com/WaterLily-jl...
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Bernat Font @fontb.bsky.social · 06/03/2025
Another great output from our DRL for active flow control team! Lead by Pol Suarez, in this paper we show how DRL helps to achieve significant drag reduction for flow around a cylinder at Re=3900 with reduced mass cost efficiency! #CFD #RL #DRL #turbulence 📎 doi.org/10.1007/s10494-025-00642-x
Flow past a circular cylinder at Re=3900 with/without active flow control
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Grant Sanderson @3blue1brown.com · 23/02/2025
Part 2 of the collaboration with Terence Tao on the cosmic distance ladder is now out. It covers how we first learned the distances to planets, stars, and galaxies far, far away. youtu.be/hFMaT9oRbs4
youtu.be
The cosmic distance ladder with Terence Tao, part 2
YouTube video by 3Blue1Brown
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Bernat Font @fontb.bsky.social · 18/02/2025
#JuliaLang Pkg and #ArchLinux pacman are such great tools. The best package managers I have ever used.
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Joe Chou @incidentalfindings.org · 14/02/2025
I've often struggled to explain _why_, even as a novice, I enjoy #julialang so much, often falling back to "It just feels nice." Apparently, I should have just let the Julia developers explain it. Came across the following from "Why We Created Julia" from 2012-02 and it all makes more sense now.
Excerpt from "Why we created Julia", J Bezanson, S Karpinski, VB Shah, A Edelman, from https://julialang.org/blog/2012/02/why-we-created-julia/

"We want a language that's open source, with a liberal license. We want the speed of C with the dynamism of Ruby. We want a language that's homoiconic, with true macros like Lisp, but with obvious, familiar mathematical notation like Matlab. We want something as usable for general programming as Python, as easy for statistics as R, as natural for string processing as Perl, as powerful for linear algebra as Matlab, as good at gluing programs together as the shell. Something that is dirt simple to learn, yet keeps the most serious hackers happy. We want it interactive and we want it compiled."
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Bernat Font @fontb.bsky.social · 13/02/2025
One of my favorite tunes lately, by Tower of Power www.youtube.com/watch?v=QBMX...
youtube.com
Walkin' up Hip Street
YouTube video by Tower Of Power - Topic
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Bernat Font @fontb.bsky.social · 13/02/2025
I only realised during the second season of #Severance !
Actor John Turturro in The Big Lebowski (movie) and Severance (TV show)
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Bernat Font @fontb.bsky.social · 13/02/2025
Tuesday next week (18th February, 5pm CET), Dr. Soledad Le Clainche from Universidad Politécnica de Madrid will present at the Large-scale CFD online seminar series: "From modal decompositions to machine learning: new tools and applications in fluid dynamics".
Details of the seminar in image format. Written format available in https://www.linkedin.com/events/7295741410593443841
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BSC-CNS @bsc-cns.bsky.social · 11/02/2025
🆕 New paper by BSC researchers published in Nature Communications on a critical challenge in fluid dynamics: turbulence 💻The researchers investigated how #AI can improve active flow control to reduce turbulence. 🔗 www.nature.com/articles/s41...
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Jorge Bravo Abad @bravo-abad.bsky.social · 07/02/2025
Font et al. show a deep reinforcement learning-driven controller that cuts turbulent separation bubbles more effectively than periodic forcing. Trained on a coarser grid, it transfers smoothly to fine-grid simulations. www.nature.com/articles/s41...
nature.com
Deep reinforcement learning for active flow control in a turbulent separation bubble - Nature Communications
The control of turbulent flows is crucial for improving efficiency in engineering systems. Here, authors show in a numerical simulation that using deep reinforcement learning to control surface actuat...
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Bernat Font @fontb.bsky.social · 10/02/2025
We have succeeded in controlling a turbulent separation bubble at a high Reynolds number using deep reinforcement learning! The paper, published in @naturecomms.bsky.social (@natureportfolio.nature.com), can be accessed here: www.nature.com/articles/s41... #ML #DRL #CFD #LES
A turbulent separation bubble visualized with Q-criterion vortical structures.
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Grant Sanderson @3blue1brown.com · 08/02/2025
New video! Terence Tao on how we measure the cosmos: youtu.be/YdOXS_9_P4U
youtu.be
Terence Tao on how we measure the cosmos | Part 1
YouTube video by 3Blue1Brown
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Gabriel Weymouth @gabrielweymouth.bsky.social · 03/02/2025
Getting excited about an upcoming numerical method paper... Here's a hint: This is the 𝐞𝐧𝐭𝐢𝐫𝐞 numerical domain!
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Adrian Hill @adrianhill.de · 30/01/2025
You think Jacobian and Hessian matrices are prohibitively expensive to compute on your problem? Our latest preprint with @gdalle.bsky.social might change your mind! arxiv.org/abs/2501.17737 🧵1/8
Figure comparing automatic differentiation (AD) and automatic sparse differentiation (ASD).

(a) Given a function f, AD backends return a function computing vector-Jacobian products (VJPs). (b) Standard AD computes Jacobians row-by-row by evaluating VJPs with all standard basis vectors. (c) ASD reduces the number of VJP evaluations by first detecting a sparsity pattern of non-zero values, coloring orthogonal rows in the pattern and simultaneously evaluating VJPs of orthogonal rows. The concepts shown in this figure directly translate to forward-mode, which computes Jacobians column-by-column instead of row-by-row.
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Chris Rackauckas @chrisrackauckas.bsky.social · 29/01/2025
Using higher order automatic differentiation to improve stiff ODE solvers? Using a third order Newton-like method (Halley's) inside the #sciml #julialang ODE solvers with Taylor-mode AD, ~25% faster. arxiv.org/abs/2501.16895
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Bernat Font @fontb.bsky.social · 28/01/2025
After 1-2 months of grant writing, I am happy to be coding again...
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Samuel Vaiter @samuelvaiter.com · 27/01/2025
Ok, so can we get some cheap GPUs now - to, you know, play video games and all that?
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Bernat Font @fontb.bsky.social · 17/01/2025
changing the default downloads directory from ~/Downloads/ to /tmp/ is self-care
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Bernat Font @fontb.bsky.social · 09/01/2025
I compiled some of the learning resources I point out to students in this repo github.com/b-fg/learnin... These are free online books/articles/posts/webs/repos on #CFD, #ML, #HPC, and #academic writing. Very preliminary, but I will be adding some more as they come up. Please feel free to contribute!
github.com
GitHub - b-fg/learning-resources: Free learning resources on CFD, ML, HPC, and scientific writing
Free learning resources on CFD, ML, HPC, and scientific writing - b-fg/learning-resources
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Bernat Font @fontb.bsky.social · 30/12/2024
There is only one week left to apply for this PhD position!
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Gabriel Weymouth @gabrielweymouth.bsky.social · 25/12/2024
Merry Christmas 🎄
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