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Connecting real crash data with standards (Euro NCAP, UNECE, ISO…) and ASAM OpenSCENARIO model

I’m grateful to have participated Formula Student event this year again as a Judge for the driverless racing category, and delivered a lecture on recent Digital Twin and Generative AI technologies in the industry. Above all, it’s always a pleasure to see Siemens well presented in the event and on many of those cars :).

FYI, interesting PhD position on data-driven optimal control for Air Mobility and Battery Management in Oxford Control Group.

Nice pieces on suspension design, from 1D target cascading to 3D design requirements.

Launched in June 2025 with a total budget of 9.3M€. The project aims to develop a rigorous design and deployment methodology tailored for reliable, robust and trustworthy Generative AI.

Bring Real data into Simulation (Real2Sim) and to... Movies.

Bridging the gap of Real and Simulation (Real2Sim - Sim2Real) toward engineering values is interesting and motivating to see how far we could push the boundary. Take a look at our 3D scene reconstruction demo in a parking scene, compare virtual and real side by side.

One often overlooked topic in control systems engineering is explainability. Control engineers are typically trained, through university or research, to design systems from the ground up, starting with physics-based modeling, model identification, stability analysis, control design, and then iterating with performance evaluation. This process provides engineers insight into the system, enabling intuitive for parameter calibration.

When reconstructing 3D traffic model from real world data (Real2Sim), one of the challenges is incorporating physical properties such as materials and textures.

I am honored to have opportunity to speak at this distinguished gathering alongside experts in AI and industry

Great discussions with Prof. Holger Caesar (Intelligent Vehicles Group, TU Delft) with his visiting to our R&D team in Siemens Leuven office last Friday.

Transform the vehicle sensor data into a large AI neural network model. The Gaussian Splatting model captures very well all details of the street from other cars, road terrains, trees, buildings… with high texture, color performance.