Pulse Mag | Interview with Dr Roberto Castello on the use of AI in the energy transition

The Swiss Data Science Center (SDSC), in collaboration with Empa and Bühler Group, co-organized a workshop to explore data-driven control methods in energy and manufacturing. The event brought together experts from academia and industry to discuss cutting-edge approaches like Rule-Based (RB) Controllers, Model Predictive Control (MPC) and Reinforcement Learning (RL). Participants examined real-world applications and addressed the challenges of adopting these advanced methods in production environments.

Researchers at Eawag and the Swiss Data Science Center have trained AI algorithms with a comprehensive ecotoxicological dataset. Now their machine learning models can predict how toxic chemicals are to fish.

We’ve developed a smart solution for wind tunnel testing that learns as it works, providing accurate results faster. It provides an accurate mean flow field and turbulence field reconstruction while shortening the sampling time.

The lack of transparency of black-box models is a fundamental problem in modern Artificial Intelligence and Machine Learning. This work focuses on how to unbox deep learning models for image classification problems.