搜索
Featuring: Dr. Arthur Clavière, Collins Aerospace
How can we be confident that a machine learning model will behave safely on data it’s never seen—especially in avionics? In this session, Dr. Arthur Clavière introduces a formal methods approach to verifying maching learning generalization. The talk highlights how formal verification can be apploied toneural networks in safety-critical avionics systems.
💬 Discussion question:
Where do you see formal verification having the biggest impact on deploying ML in safety‑critical systems—and what challenges still stand in the way?
Join the conversation below 👇
I was reading Yann Debray's recent post on automating documentation with agentic AI and ended up spending more time than expected in the comments section. Not because of the comments themselves, but because of something small I noticed while trying to write one. There is no writing assistance of any kind before you post. You type, you submit, and whatever you wrote is live.
For a lot of people that is fine. But MATLAB Central has users from all over the world, and I have seen questions on MATLAB Answers where the technical reasoning is clearly correct but the phrasing makes it hard to follow. The person knew exactly what they meant. The platform just did not help them say it clearly.
I want to share a few ideas around this. They are not fully formed proposals but I think the direction is worth discussing, especially given how much AI tooling MathWorks has built recently.
What the platform has today
When you write a post in Discussions or an answer in MATLAB Answers, the editor gives you basic formatting options. Code blocks, some text styling, that is mostly it. The AI Chat Playground exists as a separate tool, and MATLAB Copilot landed in R2025a for the desktop. But none of that is inside the editor where people actually write community content.
Four things are missing that I think would make a real difference.
Grammar and clarity checking before you post
Not a forced rewrite. Just an optional Check My Draft button that highlights unclear sentences or anything that might trip a reader up. The user reviews it, decides what to change, then posts.
What makes this different from plugging in Grammarly is that a general-purpose tool does not know that readtable is a MATLAB function. It does not know that NaN, inf, or linspace are not errors. A MATLAB-aware checker could flag things that generic tools miss, like someone writing readTable instead of readtable in a solution post.
The llms-with-matlab package already exists on GitHub. Something like this could be built on top of it with a prompt that includes MATLAB function vocabulary as context. That is not a large lift given what is already there.
Translation support
MATLAB Central already has a Japanese-language Discussions channel. That tells you something about the community. The platform is global but most of the technical content is in English, and there is a real gap there.
Two options that would help without being intrusive:
- Write in your language, click Translate, review the English version, then post. The user is still responsible for what goes live.
- A per-post Translate button so readers can view content in a language they are more comfortable with, without changing what is stored on the platform.
A student who has the right answer to a MATLAB Answers question might not post it because they are not confident writing in English. Translation support changes that. The community gets the answer and the contributor gets the credit.
In-editor code suggestions
When someone writes a solution post they usually write the code somewhere else, test it, copy it, paste it, and format it manually. An in-editor assistant that generates a starting scaffold from a plain-text description would cut that loop down.
The key word is scaffold, not a finished answer. The label should say something like AI-generated draft, verify before posting so it is clear the person writing is still accountable. MATLAB Copilot already does something close to this inside the desktop editor. Bringing a lighter version of it into the community editor feels like a natural extension of what already exists.
A note on feasibility
These ideas are not asking for something from scratch. MathWorks already has llms-with-matlab, the MCP Core Server, and MATLAB Copilot as infrastructure. Grammar checking and translation are well-solved problems at the API level. The MATLAB-specific vocabulary awareness is the part worth investing in. None of it should be on by default. All of it should be opt-in and clearly labeled when it runs.
One more thing: diagrams in posts
Right now the only way to include a diagram in a post is to make it externally and upload an image. A lightweight drag-and-drop diagram tool inside the editor would let people show a process or structure quickly without leaving the platform. Nothing complex, just boxes and arrows. For technical explanations it is often faster to draw than to write three paragraphs.
What I am curious about
I am a Data Science student at CU Boulder and an active MATLAB user. These ideas came up while using the platform, not from a product roadmap. I do not know what is already being discussed internally at MathWorks, so it is entirely possible some of this is in progress.
Has anyone else run into the same friction points when writing on MATLAB Central? And for anyone at MathWorks who works on the community platform, is the editor something that gets investment alongside the product tools?
Happy to hear where I am wrong on the feasibility side too.
AI assisted with grammar and framing. All ideas and editorial decisions are my own.
🚀 Unlock Smarter Control Design with AI
What if AI could help you design better controllers—faster and with confidence?
In this session, Naren Srivaths Raman and Arkadiy Turevskiy (MathWorks) show how control engineers are using MATLAB and Simulink to integrate AI into real-world control design and implementation.
You’ll see how AI is being applied to:
🧠 Advanced plant modeling using nonlinear system identification and reduced order modeling
📡 Virtual sensors and anomaly detection to estimate hard-to-measure signals
🎯 Datadriven control design, including nonlinear MPC with neural statespace models and reinforcement learning
⚡ Productivity gains with generative AI, powered by MATLAB Copilot
I coded this app to solve the 20 or so test cases included with the Cody problem 'visually' and step-by-step. For extra fun, it can also be used to play the game... Any comments or suggestions welcome!
At #9 in our MATLAB EXPO 2025 countdown: From Tinkerer to Developer—A Journey in Modern Engineering Software Development
A big thank‑you to Greg Diehl at NAVAIR and Michelle Allard at MathWorks, the team behind this session, for sharing their multi‑year evolution from rapid‑fire experimenting to disciplined, scalable software development.
If you’ve ever wondered what it really takes to move MATLAB code from “it works!” to “it’s ready for production,” this talk captures that transition. The team highlights how improved testing practices, better structure, and close collaboration with MathWorks experts helped them mature their workflows and tackle challenges around maintainability and code quality.
Curious about the pivotal moments that helped them level up their engineering software practices?
Couldn’t catch everything at MATLAB EXPO 2025? You’re not alone. Across keynotes and track talks, there were too many gems for one sitting. For the next 9 weeks, we’ll reveal the "Top 10" sessions attended (workshops excluded)—one per week—so you can binge the best and compare notes with peers.
Starting at #10: Simulation-Driven Development of Autonomous UAVs Using MATLAB
A huge thanks to Dr. Shital S. Chiddarwar from Visvesvaraya National Institute of Technology Nagpur who delivered this presentation online at MATLAB EXPO 2025. Are you curious how this workflow accelerates development and boosts reliability?
In 2025, we saw the growing impact of GenAI on site traffic and user behavior across the entire technical landscape. Amid all this change, MATLAB Central continued to stand out as a trusted home for MATLAB and Simulink users. More than 11 million unique visitors in 2025 came to MATLAB Central to ask questions, share code, learn, and connect with one another.
Let’s celebrate what made 2025 memorable across three key areas: people, content, and events.
People
In 2025, nearly 20,000 contributors participated across the community. We’d like to spotlight a few standout contributors:
- @Sam Chak earned the Most Accepted Answers Badge for both 2024 and 2025. Sam is a rising star in MATLAB Answers with 2,000+ answers and 1,000+ votes.
- @Rodney Tan has been actively contributing files to File Exchange. In 2025, his submissions got almost 20,000 downloads!
- @Dyuman Joshi was recognized as a top contributor on both Cody and Answers. Many may not know that Dyuman is also a Cody moderator, doing tremendous behind-the-scenes moderation work to keep the platform running smoothly.
- A warm welcome to @Steve Eddins, who joined the Community Advisory Board. Steve brings a unique perspective as a former MathWorker and long-time top community contributor.
- Congratulations to @Walter Roberson on reaching 100 followers! MATLAB Central thrives on people-to-people connections, and we’d love to see even more of these relationships grow.
Of course, there are many contributors we didn’t mention here—thank you all for your outstanding contributions and for making the community what it is.
Content
Our high-quality community content not only attracts users but also helps power the broader GenAI ecosystem.
Popular Blog Post & File Exchange Submission
- Zoomed Axes, submitted by @Caleb Thomas, enables zoomed-in views of selected regions in a plot.This submission was featured in the Pick of the Week blog post, “MATLAB Zoomed Axes: Showing zoomed-in regions of a 2D plot,” which generated 5,000 views in just one month.
Popular Discussion Post
- What did MATLAB/Simulink users wait for most in 2025? It's R2025a! “Where is MATLAB R2025a?” became the most-viewed discussion post, with 10,000 views and 30 comments. Thanks for your patience — MATLAB R2025a turned out to be one of the biggest releases we’ve ever delivered.
Most Viewed Question
- “How do I create a for loop in MATLAB?” was the most-viewed community question of the year. It’s a fun reminder that even as MATLAB evolves, the basics remain essential — and always in demand.
Most Voted Poll
- “Did you know there is an official MATLAB certification?”, created by @goc3, was the most-voted poll of 2025.While 50% of respondents voted “No”, it’s exciting to see 3% are certified MATLAB Professionals. Will you be one of them in 2026?
Events
The Cody Contest 2025 brought teams together to tackle challenging but fun Cody problems. During the contest:
- 20,000+ solutions were submitted
- 20+ tips & tricks articles were shared by top players
While the contest has ended, you can still challenge yourself with the fun contest problem group. If you get stuck, the tips & tricks articles are a great resource—and you’ll be amazed by the creativity and skill of the contributors.
Thank you for being part of an incredible 2025. Your curiosity, generosity, and expertise are what make MATLAB Central a trusted home for millions—and we look forward to learning and growing together in 2026.
Currently, the open-source MATLAB Community is accessed via the desktop web interface, and the experience on mobile devices is not very good—especially switching between sections like Discussion, FEX, Answers, and Cody is awkward. Having a dedicated app would make using the community much more convenient on phones.
Similarty,github has Mobile APP, It's convient for me.
I struggle with animations. I often want a simple scrollable animation and wind up having to export to some external viewer in some supported format. The new Live Script automation of animations fails and sabotages other methods and it is not well documented so even AIs are clueless how to resolve issues. Often an animation works natively but not with MATLAB Online. Animation of results seems to me rather basic and should be easier!
Frequently, I find myself doing things like the following,
xyz=rand(100,3);
XYZ=num2cell(xyz,1);
scatter3(XYZ{:,1:3})
But num2cell is time-consuming, not to mention that requiring it means extra lines of code. Is there any reason not to enable this syntax,
scatter3(xyz{:,1:3})
so that I one doesn't have to go through num2cell? Here, I adopt the rule that only dimensions that are not ':' will be comma-expanded.
In the sequence of previous suggestion in Meta Cody comment for the 'My Problems' page, I also suggest to add a red alert for new comments in 'My Groups' page.
Thank you in advance.
Give your LLM an easier time looking for information on mathworks.com: point it to the recently released llms.txt files. The top-level one is www.mathworks.com/llms.txt, release changes use www.mathworks.com/help/relnotes. How does it work for you??
(Requested for newer MATLAB releases (e.g. R2026B), MATLAB Parallel Processing toolbox.)
Lower precision array types have been gaining more popularity over the years for deep learning. The current lowest precision built-in array type offered by MATLAB are 8-bit precision arrays, e.g. int8 and uint8. A good thing is that these 8-bit array types do have gpuArray support, meaning that one is able to design GPU MEX codes that take in these 8-bit arrays and reinterpret them bit-wise as other 8-bit array types, e.g. FP8, which is especially common array type used in modern day deep learning applications. I myself have used this to develop forward pass operations with 8-bit precision that are around twice as fast as 16-bit operations and with output arrays that still agree well with 16-bit outputs (measured with high cosine similarity). So the 8-bit support that MATLAB offers is already quite sufficient.
Recently, 4-bit precision array types have been shown also capable of being very useful in deep learning. These array types can be processed with Tensor Cores of more modern GPUs, such as NVIDIA's Blackwell architecture. However, MATLAB does not yet have a built-in 4-bit precision array type.
Just like MATLAB has int8 and uint8, both also with gpuArray support, it would also be nice to have MATLAB have int4 and uint4, also with gpuArray support.
Missed a session or want to revisit your favorites? Now’s your chance!
Explore 42 sessions packed with insights, including:
✅4 inspiring keynotes
✅ 22 Customer success stories
✅5 Partner innovations
✅11 MathWorks-led technical talks
Each session comes with video recordings and downloadable slides, so you can learn at your own pace.
The Cody Contest 2025 has officially wrapped up! Over the past 4 weeks, more than 700 players submitted over 20,000 solutions. In addition, participants shared 20+ high-quality Tips & Tricksarticles—resources that will benefit Cody users for years to come.
Now it’s time to announce the winners.
🎉 Week 4 winners:
Weekly Prizes for Contest Problem Group Finishers:
@JKMSMKJ, @Yu Zhang, @Oliver Jaros, @Pauli Huusari, @Karl, @Marcos Silveira, @goc3, @Ildeberto de los Santos Ruiz, @Norberto, @Eric
Weekly Prizes for Contest Problem Group Solvers:
Weekly Prizes for Tips & Tricks Articles:
This week’s prize goes to @WANG Zi-Xiang. See the comments from our judge and problem group author @Matt Tearle:
‘We had a lot of great tips for solving Cody problems in general and the contest problems specifically. But we all know there are those among us who, having solved the problem, still want to tinker and make their code better. There are different definitions of "better", but code size remains the base metric in Cody. Enter Wang Zi-Xiang who compiled a list of many tips for reducing Cody size. This post also generated some great discussion (even prompting our insane autocrat, Lord Ned himself, to chime in). I particularly like the way that, while reducing Cody size often requires some arcane tricks that would normally be considered bad coding practice, the intellectual activity of trying to "game the system" makes you consider different programming approaches, and sometimes leads you to learn corners of MATLAB that you didn't know.’
🏆 Grand Prizes for the Main Round
Team Relentless Coders:
2nd Place: @Roberto
Team Creative Coders:
Team Cool Coders
Congratulations to all! Securing a top position on the leaderboard requires not only advanced MATLAB skills but also determination and consistency throughout the four-week contest. You will receive Amazon gift cards.
🥇 Winning Team
The competition was incredibly tight—we even had to use the tie-breaker rule.
Both Team Cool Coders and Team Relentless Coders achieved 16 contest group finishers. However, the last finisher on Cool Coders completed the problem group at 1:02 PM on Dec 7, while the last finisher on Relentless Coders finished at 9:47 PM the same day.
Such a close finish! Congratulations to Team Cool Coders, who have earned the Winning Team Finishers badge.
🎬 Bonus Round
Invitations have been sent to the 6 players who qualified for the Bonus Round. Stay tuned for updates—including the Big Watch Party afterward!
Congratulations again to all winners! We’ll be reaching out after the contest ends. It has been an exciting, rewarding, and knowledge-packed journey.
See you next year!
I believe that it is very useful and important to know when we have new comments of our own problems. Although I had chosen to receive notifications about my own problems, I only receive them when I am mentioned by @.
Is it possible to add a 'New comment' alert in front of each problem on the 'My Problems' page?
Over the past three weeks, players have been having great fun solving problems, sharing knowledge, and connecting with each other. Did you know over 15,000 solutions have already been submitted?
This is the final week to solve Cody problems and climb the leaderboard in the main round. Remember: solving just one problem in the contest problem group gives you a chance to win MathWorks T-shirts or socks.
🎉 Week 3 Winners:
Weekly Prizes for Contest Problem Group Finishers:
@Umar, @David Hill, @Takumi, @Nicolas, @WANG Zi-Xiang, @Rajvir Singh Gangar, @Roberto, @Boldizsar, @Abi, @Antonio
Weekly Prizes for Contest Problem Group Solvers:
Weekly Prizes for Tips & Tricks Articles:
This week’s prize goes to @Cephas. See the comments from our judge and problem group author @Matt Tearle:
'Some folks have posted deep dives into how to tackle specific problems in the contest set. But others have shared multiple smaller, generally useful tips. This week, I want to congratulate the cumulative contribution of Cool Coder Cephas, who has shared several of my favorite MATLAB techniques, including logical indexing, preallocation, modular arithmetic, and more. Cephas has also given some tips applying these MATLAB techniques to specific contest problems, such as using a convenient MATLAB function to vectorize the Leaderboard problem. Tip for Problem 61059 – Leaderboard for the Nedball World Cup:'
Congratulations to all Week 3 winners! Let’s carry this momentum into the final week!
In just two weeks, the competition has become both intense and friendly as participants race to climb the team leaderboard, especially in Team Creative, where @Mehdi Dehghan currently leads with 1400+ points, followed by @Vasilis Bellos with 900+ points.
There’s still plenty of time to participate before the contest's main round ends on December 7. Solving just one problem in the contest problem group gives you a chance to win MathWorks T-shirts or socks. Completing the entire problem group not only boosts your odds but also helps your team win.
🎉 Week 2 Winners:
Weekly Prizes for Contest Problem Group Finishers:
@Cephas, @Athi, @Bin Jiang, @Armando Longobardi, @Simone, @Maxi, @Pietro, @Hong Son, @Salvatore, @KARUPPASAMYPANDIYAN M
Weekly Prizes for Contest Problem Group Solvers:
Weekly Prizes for Tips & Tricks Articles:
This week’s prize goes to @Athi for the highly detailed post Solving Systematically The Clueless - Lord Ned in the Game Room.
Comment from the judge:
Shortly after the problem set dropped, several folks recognized that the final problem, "Clueless", was a step above the rest in difficulty. So, not surprisingly, there were a few posts in the discussion boards related to how to tackle this problem. Athi, of the Cool Coders, really dug deep into how the rules and strategies could be turned into an algorithm. There's always more than one way to tackle any difficult programming problem, so it was nice to see some discussion in the comments on different ways you can structure the array that represents your knowledge of who has which cards.
Congratulations to all Week 2 winners! Let’s keep the momentum going!
Thank you to everyone who attended the workshop A Hands-On Introduction to Reinforcement Learning! Now that you all have had some time to digest the content, I wanted to create a thread where you could ask any further questions, share insights, or discuss how you're applying the concepts to your work. Please feel free to share your thoughts in the thread below! And for your reference, I have attached a PDF version of the workshop presentation slides to this post.
If you were interested in joining the RL workshop but weren't able to attend live (maybe because you were in one of our other fantastic workshops instead!), you can find the workshop hands-on material in this shared MATLAB Drive folder. To access the exercises, simply download the MATLAB Project Archive (.mlproj) file or copy it to your MATLAB Drive, extract the files, and open the project (.prj). Each exercise has its own live script (.mlx file) which contains all the instructions and individual steps for each exercise. Happy (reinforcement) learning!
Is it possible to get the slides from the Hands-On-Workshops?
I can't find them in the proceedings. I'm particularly interested in the Reinforcement Learning workshop, but unfortunately I couldn't participate.
Thanks in advance!
