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Excited to be here
Get ready to roll up your sleeves at MATLAB EXPO 2025 – our global online event is back, and this year we’re offering 10 hands-on workshops designed to spark innovation and deepen your skills with MATLAB Online and Simulink Online.
Whether you're exploring AI, modeling batteries, or building carbon trackers, these live workshops are your chance to:
- Work directly in MATLAB and Simulink Online
- Solve real-world challenges with guidance from MathWorks experts
- Connect with peers across industries
- Ask questions and get live feedback
Join the Experience to learn more about each workshop below!
Which workshop are you most excited to attend?!
Day 1:
- Beyond the Labels: Leveraging AI Techniques for Enlightened Product Choices
- A Hands-On Introduction to Reinforcement Learning with MATLAB and Simulink
- Curriculum Development with MATLAB Copilot and Generative AI
- Simscape Battery Workshop
- Generating Tests for your MATLAB code
Day 2:
- Hands-On AI for Smart Appliances: From Sensor Data to Embedded Code
- A Hands-On Introduction to Reduced Order Modeling with MATLAB and Simulink
- Introduction to Research Software and Development with Simulink
- Hack Your Carbon Impact: Build and Publish an Emissions Tracker with MATLAB
- How to Simulate Scalable Cellular and Connectivity Networks: A Hands-On Session
We look forward to Accelerating the Pace of Engineering and Science together!
It’s an honor to deliver the keynote at MATLAB EXPO 2025. I'll explore how AI changes the game in engineered systems, bringing intelligence to every step of the process from design to deployment. This short video captures a glimpse of what I’ll share:
What excites or challenges you about this shift? Drop a comment or start a thread!
Please share with us how you are using AI in your control design workflows and what you want to hear most in our upcoming talk, 4 Ways to Improve Control Design Workflows with AI.
Arkadiy
Hello Everyone, I’m Vikram Kumar Singh, and I’m excited to be part of this amazing MATLAB community!
I’m deeply interested in learning more from all of you and contributing wherever I can. Recently, I completed a project on modeling and simulation of a Li-ion battery with a Battery Management System (BMS) for fault detection and management.
I’d love to share my learnings and also explore new ideas together with this group. Looking forward to connecting and growing with the community!
Excited for MATLAB EXPO 2025!
I’m a Master’s student in Electrical Engineering at UNSW Sydney, researching EV fleet charging and hybrid energy strategies integrating battery-electric and hydrogen fuel cell vehicles.
LinkedIn link: www.linkedin.com/in/yuanzhe-chen-6b2158351
ResearchGate link: https://www.researchgate.net/profile/Yuanzhe-Chen-9?ev=hdr_xprf
#MATLABEXPO #EV #FCEV #SmartGrid
Excited to link and sync to be a part of better learning experience
Automating Parameter Identifiability Analysis in SimBiology
Is it possible to develop a MATLAB Live Script that automates a series of SimBiology model fits to obtain likelihood profiles? The goal is to fit a kinetic model to experimental data while systematically fixing the value of one kinetic constant (e.g., k1) and leaving the others unrestricted.
The script would perform the following:
Use a pre-configured SimBiology project where the best fit to the experimental data has already been established (including dependent/independent variables, covariates, the error model, and optimization settings).
Iterate over a defined sequence of fixed values for a chosen parameter.
For each fixed value, run the estimation to optimize the remaining parameters.
Record the resulting Sum of Squared Errors (SSE) for each run.
The final output would be a likelihood profile—a plot of SSE versus the fixed parameter value (e.g., k1)—to assess the practical identifiability of each model parameter.
happy to be here
Excited to link up
Hello everyone , i am excited to learn more!
AI for Engineered Systems
47%
Cloud, Software Factories, & DevOps
0%
Electrification
13%
Autonomous Systems and Robotics
13%
Model-Based Design
7%
Wireless Communications
20%
15 votos
Hi. I'm interested to learn more about MATLAB.
excited to learn more on Mathworks
Looking forward to the Expo!
Registration is now open for MathWorks annual virtual event MATLAB EXPO 2025 on November 12 – 13, 2025!
Register now and start building your customized agenda today!
Explore. Experience. Engage.
Join MATLAB EXPO to connect with MathWorks and industry experts to learn about the latest trends and advancements in engineering and science. You will discover new features and capabilities for MATLAB and Simulink that you can immediately apply to your work.
For the www, uk, and in domains,a generative search answer is available for Help Center searches. Please let us know if you get good or bad results for your searches. Some have pointed out that it is not available in non-english domains. You can switch your country setting to try it out. You can also ask questions in different languages and ask for the response in a different language. I get better results when I ask more specific queries. How is it working for you?
Hello MATLAB Central community,
My name is Yann. And I love MATLAB. I also love Python ... 🐍 (I know, not the place for that).
I recently decided to go down the rabbit hole of AI. So I started benchmarking deep learning frameworks on basic examples. Here is a recording of my experiment:
Happy to engage in the debate. What do you think?
Large Language Models (LLMs) with MATLAB was updated again today to support the newly released OpenAI models GPT-5, GPT-5 mini, GPT-5 nano, GPT-5 chat, o3, and o4-mini. When you create an openAIChat object, set the ModelName name-value argument to "gpt-5", "gpt-5-mini", "gpt-5-nano", "gpt-5-chat-latest", "o4-mini", or "o3".
This is version 4.4.0 of this free MATLAB add-on that lets you interact with LLMs on MATLAB. The release notes are at Release v4.4.0: Support for GPT-5, o3, o4-mini · matlab-deep-learning/llms-with-matlab
作ったコードは公開して使ってもらいましょう！ということでその方法をブログで紹介します。
GitHub や File Exchange で公開しているコードがあれば、ぜひこのスレで教えてください！
ブログで紹介している大まかな３ステップをここにまとめます。
1. GitHub でコードを公開・開発する
- GitHub 上でのリポジトリ公開はコミュニティ形成にもつながります。
- R2025a 以降は MATLAB の Markdown サポートも強化されており、README.md を充実させると理解や導入が促進されます。
2. File Exchange に展開（GitHub と連携して自動同期）
- File Exchangeで公開することで MATLAB 内から検索・インストールが可能になります。
- GitHub と File Exchange の連携設定により、GitHub の更新を自動的に File Exchange に反映させることも可能です。
3. 「Open in MATLAB Online」ボタンやリンクを追加
- GitHub リポジトリに「Open in MATLAB Online」リンクやボタンを埋め込むことで、ブラウザ上でコードを試せます。
