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I have been a loyal MATLAB user for 25 years, starting from my university days. While many of my peers migrated to Python, I stayed for the stability, compatibility, and clean environment. However, I am finding the 2025 version exceptionally laggy. Despite running it on an $10k high-end machine, simple tasks like viewing variables and plotting take up to 60 seconds - actions that were near instantaneous in the 2020 version. I want to stay continue with MATLAB, but this performance gap is a major hurdle and irritation. I hope these optimization issues can be addressed quickly.
MATLAB EXPO India | 7 May | Bengaluru
Get inspired by the latest trends and real-world customer success stories transforming industries. Learn from trusted experts across 4 tracks.
- AI & Autonomous Systems
- Electrification
- Systems & Software Engineering
- Radar, Wireless & HDL
Register at bit.ly/matlabexpocommunity
Do we know if MATLAB is being used on the Artemis II (moon mission) spacecraft itself? Like is the crew running MATLAB programs? I imagine it was probably at least used in development of some of the components of the spacecraft, rockets, or launch building. Or is it used for any of the image analysis of the images collected by the spacecraft?
MATLAB interprets the first block of uninterupted comments in a function file as documentation. Consider a simple example.
% myfunc This is my function
%
% See also sin
function z = myfunc(x, y)
z = x + y;
end
Those comments are printed in the command window with "help myfunc" and displayed in a separate window with "doc myfunc". A lot of useful things happen behind the scenes as well.
- Hyperlinks are automatically added for valid file names after "See also".
- When dealing with classes, the doc command automatically appends the comment block with a lists of properties and methods.
All this is very handy and as been around for quite some time. However, the doc browser isn't great (forward/back feature was removed several versons ago), the text formatting isn't great, and there is no way to display math.
Although pretty text/math can be displayed in a live document, the traditional *.mlx file format does not always play nice with Git and I have avoided them. However, live documents can now (since 2025a?) be saved in a pure text format, so I began to wonder if all functions should be written in this style. Turns out that all you have to do is append these lines:
%[appendix]{"version":"1.0"}
%---
to the end of any function file to make it a live function. Doing so changes how MATLAB manages that first comment block. The help command seems to be unaffacted, although [text] may appear at the start of each comment line (depending on if the file was create as a live function or subsequently converted). The doc command behaves very different: instead of bringing up the traditional window for custom documentation, the comment block looks like it gets published to HTML and looks more similar to standard MATLAB help. This is a win in some ways, but the "See also" capabilitity is lost.
Curiously, the same text can be appended to the end of a class definition file with some affect. It does not change how the file shows up in the editor, but as in live functions, comments are published when using the doc command. So we are partway to something like a "live class", but not quite.
Should one stick with traditional *.m files or make everything live? Neither does a great job for functions/classes in a namespace--references must explicitly know absolute location in traditional functions, and there is no "See also" concept in a live function. Do we need a command, like cdoc (custom documentation), that pulls out the comment block, publishing formatted text to HTML while simultaneously resolving "See also" references as hyperlinks? If so, it would be great if there were other special commands like "See examples" that would automatically copy and then open an example script for the end user.
Hi all,
I'm a UX researcher here at MathWorks working on the MathWorks Central Community. We're testing a new feature to make it easier to ask a question, and we'd love to hear from community members like you.
Sessions will be next week. They are remote, up to 2 hours (often shorter), and participants receive a $100 stipend. If you're interested, you can click here to schedule.
Thanks in advance! Your feedback directly shapes what gets built.
--David, MathWorks UX Research
Digital Twin Development of PEARL Autonomous Surface System Thermal Management
The top session of the countdown showcases how the PEARL engineering team used a digital twin to solve real‑world thermal challenges in a solar‑powered autonomous marine platform operating in extreme environments. After thermal shutdown events in the field, the team built a model that predicts temperatures at multiple locations with ~1% accuracy, while balancing accuracy with model complexity.
Beyond the technology, this keynote delivers practical lessons for predictive modeling and digital twins that apply well beyond marine systems.
We hope you’ve enjoyed the Top 10 countdown series—and a big thank‑you to Olivier de Weck at Massachusetts Institute of Technology, for delivering such a compelling and insightful keynote.
🎥 If you missed it live, be sure to watch the recording to see why it earned the #1 spot at MATLAB EXPO 2026.
MATLAB EXPO India is Back!
This in-person events brings together engineers, scientists, and researchers to explore the latest trends in engineering and science, and discover new MATLAB and Simulink capabilities to apply to your work.
May 7, 2026 l Bengaluru
Register at bit.ly/matlabexpocommunity
Hello Community,
Registration is now open for the MathWorks Automotive Conference 2026 North America. Join industry leaders and MathWorks experts to learn about the latest trends in:
- Software-defined vehicles
- Generative AI
- Virtual vehicles
- AI and machine learning
Event details
- Date: April 28, 2026
- Location: Saint John’s Resort, Plymouth, MI
This conference is a great opportunity to connect with MathWorks and industry peers—and to explore what’s next in automotive engineering. We encourage you to register today.
We hope to see you there.
It’s no surprise this keynote landed at #2. MaryAnn Freeman, Senior Director of Engineering, AI, and Data Science explores how AI, especially generative AI, is transforming the way engineers design, build, and innovate. From accelerating the design loop with faster, data‑driven solutions, to blending human creativity with AI insights, to evolving engineering tools that turn ideas into build‑ready systems. This keynote shows how embedded intelligence helps engineers push past traditional limits and bridge imagination with real‑world impact.
If you’re curious about how AI is reshaping engineering workflows today (and what that means for the future of design), this is a must‑watch.
👉 Watch the keynote recording and see why it was one of the most popular sessions of MATLAB EXPO Online 2025.
Absolutely!
65%
Probably
9%
Sometimes yes, sometimes no
4%
Unlikely
17%
Never!
4%
23 votes
PLEASE, PLEASE, PLEASE... make MATLAB Copilot available as an option with a home license.
Please change the documentation window (https://www.mathworks.com/help/index.html) so I don't have to first click a magnifying glass before I can to get to a text field to enter my search term.
Matlab seems to follow a rule that iterative reduction operators give appropriate non-empty values to empty inputs. Examples include,
sum([])
prod([])
all([])
any([])
Is it an oversight not to do something similar for min and max?
max([])
For non-empty A and B,
max([A,B])= max(max(A), max(B))
The extension to B=[] should therefore satisfy,
max(A)=max(max(A),max([]))
for any A, which will only be true if we define max([])=-inf.
The 550,000th question has been asked on Answers.
Software‑defined vehicles are becoming reality—and this #3 ranked session shows how. In this keynote, Daniel Scurtu (NXP) demonstrates how MathWorks and NXP are working together to accelerate system‑level embedded development.
🔋 Using a vehicle electrification demo that runs across multiple NXP processors, you’ll see:
- Model‑Based Design workflows from concept to deployment
- Intelligent battery management and motor control
- Automatic code generation and hardware deployment
- ☁️ Real‑time cloud analytics and over‑the‑air updates
🛠️ Featuring MATLAB and Simulink products alongside NXP tools like Model-based Design Toolbox (MBDT), S32 Design Studio IDE, and Real-Time Drivers (RTD), this session highlights an end‑to‑end approach that reduces complexity and speeds the transition to software‑defined vehicles.
If you have published add-ons on File Exchange, you may have noticed that we recently added a new, unique package name field to all add-ons. This enables future support for automated installation with the MATLAB Package Manager. This name will be a unique identifier for your add-on and does not affect the existing add-on title, any file names, or the URL of your add-on.
📝 Update and review until April 10
We generated default package names for all add-ons. You can review and update the package name for your add-ons until April 10, 2026. Review your package names now:
After April 10, you will need to create a new version to change your package name.
🚀 More changes coming with the MATLAB R2026b prerelease
Starting with the MATLAB R2026b prerelease, these package names will take effect. At that time, the package name may appear on the File Exchange page for your add-on.
Keep your eyes peeled for exciting changes coming soon to your add-ons on File Exchange!
Cantera is an open-source suite of tools for problems involving chemical kinetics, thermodynamics, and transport processes. Dr. Su Sun, a recent graduate from Northeastern Chemical Engineering Ph.D. program made significant contributions to MATLAB interface for Cantera in Cantera Release 3.2.0 in collaboration with Dr. Richard West, other Cantera developers, and MathWorks Advanced Support and Development Teams. As part of this Release, MATLAB interface for Cantera transitioned to using the new MATLAB- C++ interface and expanded their unit testing. Further information is available here.
I began coding in MATLAB less than 2 months ago for a class at community college. Alongside the course content, I also completed the MATLAB onramp and introduction to linear algebra self-paced online courses. I think this is the most fun I've had coding since back when I used to make Scratch projects in elementary school. I'm kind of curious if I could recreate some of my favorite childhood Scratch games here.
Anyways, I just wanted to introduce myself since I plan to be really active this year. My name is Mehreen (meh like the meh emoji from the Emoji movie, reen like screen), I'm a data science undergrad sophomore from the U.S. and it's nice to meet you!
Dear all,
Recently I started working on a VS Code-style integrated terminal for the MATLAB IDE.
The terminal is installed as an app and runs inside a docked figure. You can launch the terminal by clicking on the app icon, running the command integratedTerminal or via keyboard shortcut.
It's possible to change the shell which is used. For example, I can set the shell path to C://Git//bin//bash.exe and use Git Bash on Windows. You can also change the theme. You can run multiple terminals.
I hope you like it and any feedback will be much appreciated. As soon as it's stable enough I can release it as a toolbox.
What’s New in MATLAB and Simulink in 2025
If you missed this session live, this is one of those “everyone’s talking about it” updates you’ll want to catch up on. 👀
This session is packed with the kinds of enhancements that quietly (and not so quietly) change how you work every day.
Here’s why it earned a spot in our Top 4:
- A redesigned MATLAB desktop with customizable sidebars and light/dark themes—built to adapt to how you work
- New side panels for coding and development tasks, plus more control over organizing and customizing figures
- MATLAB Copilot, a generative AI assistant optimized for MATLAB to help you explore ideas, learn techniques, and boost productivity directly in the desktop
- Simulink workflow improvements like a redesigned Simulink scope, more detailed info in quick insert, and automatic signal line straightening
- Enhanced Python integration across MATLAB and Simulink
- New AI deployment options optimized for Qualcomm and Infineon hardware targets
If staying current with MATLAB and Simulink is part of your role—or your edge—this session is a must‑watch. Missing it means missing context for features that will shape how you work in 2026 and beyond.
💬 Discussion topic:
Which single update from this release do you think will most improve your day‑to‑day workflow, and why?
