Bridging Academia and Industry: 2026 DATA-ENG Hackathon Recap

A Collaboration Behind the Idea

The hackathon builds on an ongoing collaboration between SciEngineer and AUMOVIO, as well as a long-term relationship with the University of Pannonia. On a regional level, we work closely with AUMOVIO’s Hungarian and Romanian teams, supporting simulation-focused projects and contributing to joint workshops on the effective use of engineering tools.

AUMOVIO develops braking systems and supports a range of comfort and safety-critical functions, where simulation plays a central role. Our tools are part of their development workflows, creating a direct link between industrial application and engineering practice.

At the same time, both SciEngineer and AUMOVIO maintain active connections with the University of Pannonia—from academic collaboration to dual education programs. The university complements this with campus-wide access to MATLAB and Simulink, ensuring that students are already familiar with industry-standard tools.

The idea for the hackathon emerged naturally from this shared ecosystem—where industry, academia, and tooling are already closely connected—making it a natural next step to bring these elements together in a hands-on format.

The Challenge

The task was to estimate the difference in circumferential speeds between the front and rear wheels using inputs such as vehicle speed and lean angle. The key difficulty was not the obvious rotational differences, but capturing the actual difference in motion between the two wheels.

Two Phases, Two Approaches

The hackathon was structured in two rounds. In the first phase, AI-based and black-box components were not allowed. Teams had to rely on physical modeling, system dynamics, and transparent logic within MATLAB and Simulink.

In the final round, these restrictions were lifted, allowing teams to extend their solutions with machine learning methods. During this phase, an expert team from AUMOVIO and SciEngineer supported participants in working efficiently and making the most of the tools available.

Solution Diversity

We saw a wide range of strategies—from detailed physics-based models to data-driven parameter estimation, as well as combinations of both. Some teams focused on system modeling in Simulink, while others approached the task through data analysis in MATLAB.

Generative AI tools were allowed, but the strongest teams used them selectively and demonstrated clear understanding of their own solutions. Approaches supported by literature research or academic consultation stood out.

Outcomes

By the end of the final round, three teams delivered robust and well-justified solutions. What set them apart was not only performance, but clarity, consistency, and sound engineering reasoning.

Tools and Preparation

Students at the University of Pannonia benefit from Campus-Wide Access to MATLAB and Simulink, ensuring they are already familiar with industry-standard tools when they arrive at challenges like this. As part of this access, they can also take advantage of Online Training Courses, with more than 100 hours of free learning materials available, which further supported their preparation for the competition.

This kind of access makes a visible difference. Teams were able to focus on problem-solving and modeling rather than tooling, which is essential not only in a hackathon setting, but also for building skills that translate directly to the job market.

Looking Ahead

From an educational perspective, the event reinforced the value of integrating applied, industry-relevant problems into the curriculum. MATLAB and Simulink provided an effective environment for connecting theory with practice.

We are continuing to expand the Hackathon series and are looking to collaborate with universities, educators, and industry partners interested in developing similar hands-on experiences.

If this aligns with your organization, we would be happy to connect and explore potential collaboration. You can reach us via our contact form.

Featured products

All products mentioned are developed by MathWorks:

• MATLAB
• Simulink
• MATLAB Campus-Wide License

Learn more

• Self-Paced Online Courses – MATLAB & Simulink
  Learn MATLAB for free with MATLAB Onramp and access interactive self-paced online courses and tutorials on Deep Learning, Machine Learning and more.
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• MATLAB Campus-Wide License Page
  Unlock the full potential of your institution’s academic pursuits with the MATLAB Campus-Wide License, which provides access to a comprehensive suite of tools for computational analysis, modeling, and data visualization.
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• On-demand Webinar: The Benefits of the MATLAB Campus-Wide License – Focusing on AI Applications
  Watch this video to get acquainted with all the tools and opportunities the MATLAB Campus License offers, including artificial intelligence applications with MATLAB.
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• Blog: MATLAB AI Chat Playground: A New Era in Generative AI for MATLAB Users
  MATLAB AI Chat Playground is a groundbreaking tool for MATLAB users. In this interactive chat environment, users can experiment with generative AI, get code examples, and explore MATLAB functionalities.
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