Thesis award winners: AI for controlling heavy-duty machinery, fractal geometry and reducing sulfate in pharmaceutical plant wastewater

Academic Engineers and Architects in Finland TEK and Tekniska Föreningen i Finland TFiF have awarded the doctoral thesis award to Mehdi Heydari Shahna, Doctor of Science in Technology. In his doctoral research at Tampere University, he developed a method for using artificial intelligence safely in robotised heavy-duty machinery.

Learning neural network control can improve the performance of heavy-duty machinery, but a separate safety system must monitor its operation to ensure safety.

In Heydari Shahna’s solution, safety monitoring ensures that the neural network control operates safely by transferring control to a safe backup controller when necessary and, as a last resort, stopping the machine. The stability of the entire control system has been mathematically proven.

“We can therefore harness the performance of AI without compromising safety, as mathematically justified, fault-tolerant safety control keeps the machine safe even in exceptional situations,” says Mehdi Heydari Shahna.

The doctoral thesis was completed in less than three years and included seven component publications. During his doctoral studies, Heydari Shahna published a total of 14 scientific studies.

Fractal geometry is a branch of mathematics that studies irregular geometric shapes and sets whose structure repeats in a similar way at all scales. The award for the best master’s thesis in mathematics went to University of Oulu mathematics student Eeva Kuure, whose thesis explored one of the central problems in fractal geometry.

“The thesis is a mathematically rigorous, clear and exceptionally high-quality piece of work,” the awards committee stated. The master’s thesis award in mathematics is presented by TEK and MAL.

The year’s best master’s thesis in technology was also completed at the University of Oulu. Aamu Mykkänen, who graduated with a Master of Science in Environmental Engineering, identified a practical way to reduce the sulfate load in wastewater from a pharmaceutical factory.

“I was inspired by the topic because it was a significant practical problem for which no clear solution had previously been found,” says Aamu Mykkänen.

The study identified a significant root cause of the sulfate load. When sulfur dioxide gases were scrubbed in a gas scrubber, the resulting sulfites could oxidise to sulfates in the wastewater.

The work has helped Fermion’s Oulu factory reduce its sulfate emissions. Mykkänen’s findings are likely to be applicable to other similar industrial processes as well.

“Finland produces high-quality research in technology that deserves to be seen. With these awards, we want to recognise talented researchers and students and highlight the significance of their work. It is wonderful to see how research combines scientific expertise with solutions to practical challenges,” says TFiF’s CEO Annika Nylander.

For many students, their thesis is a springboard to permanent employment in technology.

“A thesis is much more than the final requirement of a degree. It provides an opportunity to demonstrate your expertise and tackle problems whose solutions have wider significance. The award-winning theses show how research can lead to new knowledge, a new direction for your career and new business,” says TEK’s CEO Jari Jokinen.

All of this year’s winners are continuing to work on the topics of their award-winning theses.

Heydari Shahna continues as a postdoctoral researcher at Tampere University. The Futura project, in which his doctoral research was conducted, involved a number of Finnish machinery manufacturers: Sandvik, Normet, Novatron, Hiab and GIM Robotics. His current collaboration with Sandvik aims to increase the autonomy of mining drilling equipment using the methods developed in his dissertation.

Iranian-born Heydari Shahna wants to put his research findings into practice in collaboration with companies.

“I want to help them grow and succeed, or perhaps start my own company in Finland.”

Eeva Kuure was inspired to pursue fractal research by an interesting research article shared by her master’s thesis supervisor, Esa Järvenpää. He is also supervising Kuure’s ongoing doctoral dissertation.

“In my doctoral research, I am continuing to study the visibility problem in fractal geometry,” says Kuure, who now works in the fractal geometry research group at the University of Oulu.

Aamu Mykkänen’s career also continued at the company where she completed her thesis.

“I continued at Fermion as an EHS (environment, health, safety) specialist working in environmental safety. I want to deepen my expertise and tackle environmental challenges.”

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Best doctoral thesis of 2025, EUR 7,500

"Robust Deep Learning Control with Guaranteed Performance for Safe and Reliable Robotization in Heavy-Duty Machinery"

Mehdi Heydari Shahna, Postdoctoral Researcher, Tampere University

mehdi.heydarishahna@tuni.fi

Best master’s thesis in mathematics of 2025, EUR 5,000

"On the Hausdorff Dimension of Visible Parts of Sets"

Eeva Kuure, Doctoral Researcher, University of Oulu

eeva.kuure@oulu.fi

Best master’s thesis in technology of 2025, EUR 5,000

"Teollisuusjäteveden sulfaattipitoisuuden syyt ja hallinta Fermionin Oulun tehtaalla"

("Causes and Control of Sulfate Concentration in Industrial Wastewater at Fermion’s Oulu Plant")

Aamu Mykkänen, EHS Specialist, Fermion Oy

aamu.mykkanen@fermion.fi