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Causal vs. Acausal Modeling: Unlocking Flexibility in System Design - Blog - JuliaHub

November 6, 2025 at 12:09 PM Everybody can reply

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JuliaHub

@juliahub.bsky.social

Causal modeling defines signal flow, but it gets rigid as systems scale. Acausal modeling focuses on physical relationships—letting equations form automatically. See how Dyad, built on Julia and #SciML, makes system #modeling more scalable and reusable. juliahub.com/blog/causal-...
#JuliaLang #Dyad

Explore the shift from causal to acausal modeling and how it improves flexibility, scalability, and simulation performance in complex engineering systems.

November 5, 2025 at 1:49 PM Everybody can reply

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Mitsubishi Electric – Building High-Fidelity HVAC Models with Dyad and Scientific Machine Learning - Event - JuliaHub

JuliaHub

@juliahub.bsky.social

Accurate refrigerant mass estimation is key to #HVAC efficiency and compliance. Join Mitsubishi Electric + JuliaHub to see how #ModelingToolkit and #SciML enable a #digitaltwin estimator with <2% error using only pressure & temperature data.
juliahub.com/events/mitsu...
#JuliaLang #Simulation #Dyad

Learn how Mitsubishi Electric used Dyad and SciML to build a high-fidelity HVAC model that predicts refrigerant mass with less than 2% error.

Mitsubishi Electric – Building High-Fidelity HVAC Models with Dyad and Scientific Machine Learning - Event - JuliaHub

November 4, 2025 at 4:39 PM Everybody can reply

JuliaHub

@juliahub.bsky.social

Refrigerant mass estimation in #HVAC just got easier. Join experts from Mitsubishi Electric & JuliaHub for a #webinar on using #SciML + #ModelingToolkit to build a high-accuracy, non-invasive model using just pressure & temp data. juliahub.com/events/mitsu...
#julialang #DigitalTwin #Dyad

Learn how Mitsubishi Electric used Dyad and SciML to build a high-fidelity HVAC model that predicts refrigerant mass with less than 2% error.

October 28, 2025 at 5:39 PM Everybody can reply

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Chris Rackauckas

@chrisrackauckas.bsky.social

#Dyad #SciML tutorial! Use Dyad's graphical/textual #acausal system to build models from validated model components and transform into your #digitaltwin!

#Dyad = component-based modeling tool (e.g. #Modelica, #Amesim, #Simulink) + AI/ML autocomplete!

www.youtube.com/watch?v=ttQI...

www.youtube.com

October 28, 2025 at 1:11 PM Everybody can reply

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Get Your Modeling Problems Reviewed by a Dyad Expert At No Cost - Blog - JuliaHub

JuliaHub

@juliahub.bsky.social

Got a tough #modeling or Digital Twin challenge? Get a free expert review of your
SciML/controls/deployment problems with Dyad. See how our next-gen platform simplifies everything.
juliahub.com/blog/get-you...
#julialang #DigitalTwin #SciML #Dyad

Interested to learn how Dyad can help your specific modeling and simulation use case? Set up a free review session with our experts and learn how you can make the most of this platform.

Acausal vs Causal Modeling Explained with Dyad

October 27, 2025 at 6:42 PM Everybody can reply

JuliaHub

@juliahub.bsky.social

Scientific Modeling Cheatsheet: SciML has published a quick reference cheatsheet translating hundreds of functions between Julia, Python and MATLAB. Click here for more. sciml.github.io/Scientific_M...
#JuliaLang #SciML #Python #MATLAB #ScientificComputing #DataScience #Cheatsheet #Engineering

October 24, 2025 at 3:10 PM Everybody can reply

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Chris Rackauckas

@chrisrackauckas.bsky.social

What is #acausal modeling and how does it lead to better reproducibility and modularity in modeling and simulation? Check out this video which goes step-by-step into building acausal models using the RC circuit and RLC circuit

www.youtube.com/watch?v=rMb4...

#julialang #dyad #sciml

GitHub - SciML/Julia_Modeling_Workshop: High-Performance Scientific Modeling with Julia and SciML

www.youtube.com

October 20, 2025 at 1:23 PM Everybody can reply

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JuliaHub

@juliahub.bsky.social

High-Performance Scientific #Modeling with Julia and SciML: This workshop offers in-depth training on advanced scientific computing techniques using the Julia programming language and the SciML (Scientific Machine Learning) ecosystem. github.com/SciML/Julia_...
#JuliaLang #SciML #ScientificComputing

High-Performance Scientific Modeling with Julia and SciML - SciML/Julia_Modeling_Workshop

github.com

October 16, 2025 at 6:25 PM Everybody can reply

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Chris Rackauckas

@chrisrackauckas.bsky.social

#LLMs make mistakes. Modeling languages like #Dyad have static analysis to compile-time check whether models are physically possible. What happens when you mix the two in an #agentic workflow? Automated construction of accurate models!

www.youtube.com/watch?v=hIkb...

#julialang #sciml

Agentic modeling of a friction brake with Dyad, LLMs for Model-Based Systems Engineering

SciML Developer Chat Episode 1: Trimming Support and Symbolics Precompilation

www.youtube.com

October 16, 2025 at 6:00 AM Everybody can reply

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Chris Rackauckas

@chrisrackauckas.bsky.social

SciML Developer Chat Episode 1: Base Splits and Symbolics Precompilation

Welcome to the first episode of the SciML Dev Chat! We discuss the latest developments in the #SciML (Scientific Machine Learning) ecosystem for #julialang!

youtu.be/0yQ4aZ-ABhY

YouTube video by The Julia Programming Language

David Bortz - Weak form SciML for Learning Models on Different Scales - IPAM at UCLA

October 9, 2025 at 7:48 PM Everybody can reply

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richbartlebaugh.bsky.social

@richbartlebaugh.bsky.social

New from IPAM at UCLA: David Bortz of the University of Colorado, Boulder, presents "Weak form SciML for Learning Models on Different Scales" at IPAM's Bridging Scales from Atomistic to Continuum in Electrochemical Systems Workshop. Watch on YouTube-> youtu.be/XPOzYCrUWCE

YouTube video by Institute for Pure & Applied Mathematics (IPAM)

Demonstration of AI-Assisted Modeling in Dyad with Cursor AI

October 9, 2025 at 5:02 PM Everybody can reply

JuliaHub

@juliahub.bsky.social

AI-assisted modeling just got smarter.
Our latest demo shows how Dyad and Cursor AI work together to accelerate system modeling — from natural language circuit creation to real-time analysis and visualization.
youtu.be/awwJPWIlXXM
#Dyad #JuliaLang #AI #SciML #EngineeringSimulation #CursorAI

October 8, 2025 at 5:28 PM Everybody can reply

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Stop Re-Inventing the Wheel: Modeling with Dyad’s Standard Libraries - Blog - JuliaHub

Chris Rackauckas

@chrisrackauckas.bsky.social

MIT Julia Lab: looking for postdoctoral researchers in #julialang open source software development, scientific machine learning (#SciML), and systems biological / pharmacological modeling (#QSP) for research in equation discovery for large stiff systems.

julia.mit.edu/projects/#po...

Postdoc Projects

julia.mit.edu

October 8, 2025 at 6:50 AM Everybody can reply

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JuliaHub

@juliahub.bsky.social

Stop rewriting code! #Dyad’s acausal libraries accelerate your workflow. Use ready-to-use components across all major physical domains (electrical, mechanical, thermal, fluid) to streamline multi-domain #modeling in one Julia-native environment.
juliahub.com/blog/modelin... #JuliaLang #SciML

Discover how Dyad’s standard libraries simplify system modeling with ready-to-use, extensible components across electrical, mechanical, thermal, and fluid domains. Build faster, reuse models, and inte...

Fröhlich Lab | Scientific Machine Learning for Signal Transduction

October 7, 2025 at 4:44 PM Everybody can reply

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Fabian Fröhlich

@frohlichlab.com

🌊 Signals intertwine,
🔬 cells tell hidden stories,
🤖✨ SciML maps their future.

Come do a PhD with us www.crick.ac.uk/careers-stud...

www.crick.ac.uk

October 7, 2025 at 1:44 PM Everybody can reply

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Chris Rackauckas

@chrisrackauckas.bsky.social

Claude code sucks... but it's still very useful! Check out this blog post that details how Claude is deployed to solve problems in the #Julialang #SciML open source scientific computing infrastructure.

stochasticlifestyle.com/claude-code-...

#llm #vibecoding #physics #opensource #oss

Claude Code in Scientific Computing: Experiences Maintaining Julia's SciML Infrastructure - Stochastic Lifestyle

Claude Code in Scientific Computing: Experiences Maintaining Julia’s SciML Infrastructure So it’s pretty public that for about a month now I’ve had 32 processes setup on one of the 64 core 128gb RAM s...

www.stochasticlifestyle.com

October 6, 2025 at 6:40 AM Everybody can reply

4 reposts 1 quotes 14 likes

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Cian O'Donnell

@cianodonnell.bsky.social

had a nice group discussion on "Is NeuroAI the next great thing? Or just a branding trick?"

Some very interesting arguments, summarised in slides below

Slides: "WHAT ARE THE POSSIBLE NEUROAI ARGUMENTS FOR
FUTURE NEUROSCIENCE/NEUROSCIENTISTS?
• Neural-network models of the brain as a tool for doing computational neuroscience
(perturbations of brain components, parameters etc)
• SciML methods to fit our biologically-faithful model to data/task
• Ideas and methods developed in AI, might give us new ideas for how the brain works.
• Better data analysis tools.
• Can AI help with linking bottom-up and top-down approaches to neuroscience.
• Get a well paid job."

Slide with text: "WHAT ARE THE POSSIBLE NEUROAI ARGUMENTS FOR
FUTURE AI?
Future AI could be improved by neuroscience inspired ideas:
• energy efficiency
• resources
• compactness
• resilience/robustness
• learning from less data
• continual learning/lifelong learning
• uncertainty
• Brain-computer interfaces
• Run natively on neuromorphic hardware"

October 2, 2025 at 1:36 PM Everybody can reply

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Amivi Ayelle

@amiviayelle.bsky.social

I am very curious about "Model Discovery of Dynamics using Universal Differential Equations and SciML". The workflow looks pretty elegant!

October 1, 2025 at 10:52 AM Everybody can reply

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Advancing the Goals of the ARPA-E’s DIFFERENTIATE Program with Julia - Case Study - JuliaHub

JuliaHub

@juliahub.bsky.social

We partnered with ARPA-E to unlock 30% energy savings. See how JuliaHub drove massive efficiency by taking complex HVAC simulations from weeks to real-time.
juliahub.com/case-studies...
#JuliaLang #JuliaHub #ModelingToolkit #SciML #DigitalTwins #MachineLearning #HVAC #SystemModeling #Simulation

Explore how JuliaHub empowered ARPA-E's DIFFERENTIATE program to optimize HVAC systems, boosting energy efficiency, reducing simulation times, and integrating machine learning for real-time results.

September 30, 2025 at 6:25 PM Everybody can reply

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Julia for Engineers: Modeling Steady State and Dynamic Systems with Dyad - Video - JuliaHub

MACSYS

@macsys.bsky.social

It's been a thrill to host Dr Chris Rackauckas for a 2-day visit to our node at QUT. Chris presented a seminar, ran a workshop on High-Performance Scientific Modelling with Julia & SciML, & met with our researchers. Chris is VP of Modelling and Simulation at JuliaHub. @chrisrackauckas.bsky.social

September 30, 2025 at 7:27 AM Everybody can reply

2 reposts 1 likes

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JuliaHub

@juliahub.bsky.social

Julia and #ModelingToolkit.jl are a powerful combination for engineers. This video explores how to model and analyze both steady-state and dynamic systems, showing how to efficiently set up, solve, and interpret system responses.
juliahub.com/videos/julia...
#JuliaLang #SciML #Engineering

This webinar recording demonstrates how to model and simulate hydraulic actuators in Julia using ModelingToolkit.jl—covering steady-state and dynamic system behavior in one session.

What's New With ModelingToolkit - Blog - JuliaHub

September 24, 2025 at 4:14 PM Everybody can reply

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MACSYS

@macsys.bsky.social

It's been a thrill to host Dr Chris Rackauckas for a 2-day visit to our node at The University of Melbourne. Today, he presented a workshop for our researchers on High-Performance Scientific Modelling with Julia & SciML. Yesterday, he gave a public seminar. Now he's headed to meet our team at UNSW.

September 24, 2025 at 4:07 AM Everybody can reply

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JuliaHub

@juliahub.bsky.social

The package now includes MTKParameters for optimization, improved initialization, dynamic optimization, and new polynomial solvers. It's a major boost for modeling and simulation.
juliahub.com/blog/what-s-...
#JuliaLang #SciML #ModelingToolkit #Engineering #NumericalMethods #ScientificComputing

This is a short preview of Aayush Sabharwal's JuliaCon 2025 talk that explored the growth of ModelingToolkit over the past couple of years.