Siemens honours its best Inventors of 2023
Siemens has presented awards to its 12 leading innovators with a focus on AI and sustainability.
Each year, Siemens presents the Inventors of the Year award to outstanding inventors in six categories: Newcomers, Open Innovation, Outstanding Invention, Lifetime Achievement, Design and User Experience and the recently added PhD Award.
The company spends €6.2 billion on research and development and published 5,383 inventions in fiscal 2023, amounting to around 24 inventions every working day.
Since the European Unitary Patent was launched in June 2023, the European Patent Office has received over 12,000 applications for this type of patent – the majority of which came from Siemens.
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In addition to helping explain artificial intelligence (AI), the prize-winning inventions also make power grids more sustainable, railcar axles more stable and charging stations for electric vehicles more universal. The 2023 award will be presented today to twelve Inventors of the Year from the U.S., the UK, China, India, Kazakhstan and Germany.
“Our innovations are our strength and the best way to predict the future of Siemens,” said Peter Körte, Chief Technology Officer at Siemens. “We firmly believe that AI has the potential to revolutionize our work and the way we manufacture products. We already play a leading role in generating industrial artificial intelligence. The AI we create is responsible, comprehensible and trustworthy.”
Abhijit Kadam has developed a procedure for adapting charging electronics to a vehicle’s requirements. What makes his invention so special isn’t just the fact that all cars can be charged at the same charging station. It’s also that when the charging voltage is adapted in the DC-DC converter, there is zero switching loss, making his procedure especially energy-efficient.
Another award honoured the use of AI in configuring complex factory automation solutions. Swathi Shyam Sunder developed an AI system which helps derive context-aware recommendations from historical data on product configurations and from facts relating to products and components. This system makes the design process easier and faster. Siemens is already using this development in its factory automation business.
For many applications, such as medical diagnostics or safety-critical systems, it is important that people are able to follow the reasoning process of the algorithms to better understand the results and gain trust in the models. In her PhD thesis, Yushan Liu is developing ways in which machine learning processes can achieve good performance while also communicating how they have arrived at their decisions, for example by using logical rules or a graphical representation of the decision-making process.
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