Tag Archives: Julia

A Hands on Introduction to Applied Scientific Machine Learning / Physics-Informed Learning

By: Christopher Rackauckas

Re-posted from: https://www.stochasticlifestyle.com/a-hands-on-introduction-to-applied-scientific-machine-learning-physics-informed-learning/

Presented at JuliaEO25

This is a hands-on introduction to Scientific Machine Learning that does not assume a background in machine learning. We start scratch, showing the mathematical basis of “what is a neural network?” all the way up through adding physical intuition to the neural network and using it solve problem in epidemic outbreaks to improving sensor tracking of Formula 1 cars.

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Open Source Component-Based Modeling with ModelingToolkit

By: Christopher Rackauckas

Re-posted from: https://www.stochasticlifestyle.com/open-source-component-based-modeling-with-modelingtoolkit/

Component-based modeling systems such as Simulink and Dymola allow for building scientific models in a way that can be composed. For example, Bob can build a model of an engine, and Alice can build a model of a drive shaft, and you can then connect the two models and have a model of a car. These kinds of tools are used all throughout industrial modeling and simulation in order to allow for “separation of concerns”, allowing experts to engineer their domain and compose the final digital twins with reusable scientific modules. But what about open source? In this talk we will introduce ModelingToolkit, an open source component-based modeling framework that allows for composing pre-built models and scales to large high-fidelity digital twins.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

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Julia and MATLAB can coexist. Let us show you how.

By: Great Lakes Consulting

Re-posted from: https://blog.glcs.io/juliacon-2025-preview

This post was written by Steven Whitaker.

Have you ever wished you could start using the Julia programming languageto develop custom models?Does the idea of replacingoutdated MATLAB code and modelsseem overwhelming?

Or maybe you don’t plan to replace all MATLAB code,but wouldn’t it be excitingto integrate Julia codeinto existing workflows?

Also, technicalities aside,how do you convince your colleaguesto make the leapinto the Julia ecosystem?

I’m excited to sharean announcement!At this year’s JuliaCon,I will be speaking abouta small but significant stepyou can take to start adding Juliato your MATLAB codebase.

Great news!You can transition to Julia smoothlywithout completely abandoning MATLAB.There’s a straightforward methodto embrace the best of both worlds,so you won’t needto rewrite your legacy models from scratch.

I’ll give my full talk in July,but if you don’t want to wait,keep readingfor a sneak peek!

Background

The GLCS.io teamhas been developing Julia-based solutions since 2015.Over the past 4 years,we’ve had the pleasure of redesigning and enhancing Julia modelsfor our clients in the finance, science, and engineering sectors.Its incredible speed and versatility have transformedhow we tackle complex computations together.However,we also fully acknowledge the reality:MATLAB continues to hold a significant placein countless companies and research labs worldwide.

For decades,MATLAB has been the benchmarkfor data analysis, modeling, and simulationacross scientific and engineering fields.There are likely hundreds of thousands of MATLAB licenses in use,with millions of userssupporting an unimaginable number of models and codebases.

Even for a single company,fully transitioning to Juliaoften feels insurmountable.The vast amount of existing MATLAB codepresents a significant challenge for any team considering adopting Julia.

Yet, unlocking Julia’s power is vital for companiesaiming to excel in today’s competitive landscape.The question isn’t if companiesshould adopt Julia—it’s how to do it.

Companies should blend Juliawith their MATLAB environments,ensuring minimal disruption and optimal resource use.This strategic integrationdelivers meaningful gainsin accuracy, performance, and scalabilityto transform operations and drive success.

JuliaCon Preview

At JuliaCon,I’m excited to share how youcan seamlessly integrate Juliainto existing MATLAB workflows—a processthat has delivered up to 100x performance improvementswhile enhancing code quality and functionality.Through a real-world model,I’ll highlight design patterns,benchmark comparisons,and valuable business case insightsto demonstrate the transformative potential of integrating Julia.

(Spoiler alert:the performance improvement is more than 100xfor the example I will show at JuliaCon.)

What We Offer

Unlock high-performance modeling!Our dedicated team is hereto integrate Julia into your MATLAB workflows.Experience a strategic, step-by-step process tailoredfor seamless Julia-MATLAB integration,focused on efficiency and delivering measurable results:

  1. Tailored Assessment:Pinpoint challenges and opportunities for Julia to address.
  2. MATLAB Benchmarking:Establish a performance baseline to measure progress and impact.
  3. Julia Model Development:Convert MATLAB models to Juliaor assist your team in doing so.
  4. Julia Integration:Combine Julia’s capabilities with your existing MATLAB workflows for optimal results.
  5. Roadmap Alignment:Validate performance improvements,create a strong business case for leadership,and agree on future support and innovation.

Check out our website for more details.

Summary

By attending my JuliaCon talk,you will learnhow to seamlessly integrate Juliainto your existing MATLAB codebase.And by leveraging our support at GLCS,you can adopt Juliawithout disruption—unlocking faster computations,improved models,and better scalabilitywhile retaining the strengthsof your MATLAB codebase.

Are you or someone you knowexcited about harnessing the power of Julia and MATLAB together?Let’s connect! Schedule a consultation todayto discover incredible performance gains of 100x or more.

Additional Links

MATLAB is a registered trademarkof The MathWorks, Inc.

Cover image:The JuliaCon 2025 logowas obtained from https://juliacon.org/2025/.

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