다음에 대한 결과:
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.
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!
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!
In just one week, we have hit an amazing milestone: 500+ players registered and 5000+ solutions submitted! We’ve also seen fantastic Tips & Tricks articles rolling in, making this contest a true community learning experience.
And here’s the best part: you don’t need to be a top-ranked player to win. To encourage more casual and first-time players to jump in, we’re introducing new weekly prizes starting Week 2!
New Casual Player Prizes:
- 5 extra MathWorks T-shirts or socks will be awarded every week.
- All you need to qualify is to register and solve one problem in the Contest Problem Group.
Jump in, try a few problems, and don’t be shy to ask questions in your team’s channel. You might walk away with a prize!
Week 1 Winners:
Weekly Prizes for Contest Problem Group Finishers:
@Mazhar, @Julien, @Mohammad Aryayi, @Pawel, @Mehdi Dehghan, @Christian Schröder, @Yolanda, @Dev Gupta, @Tomoaki Takagi, @Stefan Abendroth
Weekly Prizes for Tips & Tricks Articles:
We had a lot of people share useful tips (including some personal favorite MATLAB tricks). But Vasilis Bellos went *deep* into the Bridges of Nedsburg problem. Fittingly for a Creative Coder, his post was innovative and entertaining, while also cleverly sneaking in some hints on a neat solution method that wasn't advertised in the problem description.
Congratulations to all Week 1 winners! Prizes will be awarded after the contest ends. Let’s keep the momentum going!
Great material, examples and skillfully guided. And, of course, very useful.
Thanks!
Hi, what’s the best way to learn MATLAB, Simulink, and Simscape? Do you recommend a learning path? I work in the Electrical & Electronics area for automotive systems.
Don’t miss out on two incredible keynotes that will shape the future of engineering and innovation:
1️⃣What’s New in MATLAB and Simulink in 2025
Get an inside look at the latest features designed to supercharge your workflows:
- A redesigned MATLAB desktop with customizable sidebars, light/dark themes, and new panels for coding tasks
- MATLAB Copilot – your AI-powered assistant for learning, idea generation, and productivity
- Simulink upgrades, including an enhanced quick insert tool, auto-straightening signal lines, and new methods for Python integration
- New options to deploy AI models on Qualcomm and Infineon hardware
2️⃣Accelerating Software-Defined Vehicles with Model-Based Design
See how MathWorks + NXP are transforming embedded system development for next-gen vehicles:
- Vehicle electrification example powered by MATLAB, Simulink, and NXP tools
- End-to-end workflow: modeling → validation → code generation → hardware deployment → real-time cloud monitoring
📅 When: November 13
💡Why Join? Stay ahead with cutting-edge tools, workflows, and insights from industry leaders.
Submit your questions about this work in the comment section below.
In the FAQs, I saw the procedure to download the "mobile background", is the the same thing as an award? If yes, good, else how can we get an award and what are the available ones?
iaabdulhameed@knu.ac.kr
Glad to have watched the session, especially the part when the speaker, Arthur gave an answer to my question on "speech recognition use case" in Avionics.
