The newly appointed CAI associates will be integrated into the life of the AI centre, engage in common research projects with CAI members and internal or external partners, contribute to teaching and student supervision, and help establishing new or intensifying existing research areas in AI. The associates have an excellent research track record and demonstrated their qualification through a thorough selection process.

The following four ZHAW researchers have been appointed for a three-year period:

• Dr. Elena Gavagnin (Senior Lecturer, ZHAW School of Management and Law, Institute of Business Information Technology IWI): Elena brings a strong interest in astrophysical applications of deep learning, where a common ZHAW project embedded in the Swiss consortium within the Square Kilometre Array Observatory has just started. Her research interests extend into other applications of computer vision as well as AI for good and AI for society.

• Prof. Dr. Rudolf Marcel Füchslin (Professor for Complex Systems Science, ZHAW School of Engineering, Institute of Applied Mathematics and Physics IAMP): Ruedi has a long-standing research track record in AI, e.g., with evolutionary and morphological methods. On top of existing joint research projects in medical imaging, he is interested in physics-informed machine learning, ethics and philosophy of AI, and dynamical processes.

• Dr. Manuel Doemer (Senior Lecturer, ZHAW School of Engineering; Programme Director, BSc. Data Science; Head, ZHAW Datalab): Manuel is interested in computer vision as applied to earth observation (satellite) data, multimodal AI, as well as MLOps. His background as a senior data scientist in industry makes him also proficient in natural language processing.

• Prof. Dr. Christoph Heitz (Professor, ZHAW School of Engineering, Institute of Data Analysis and Process Design IDP): Christoph has a background in operations research and predictive maintenance. He is president of the largest Swiss innovation network, the data innovation alliance, where he also leads the Data Ethics group. His research interest is in algorithmic fairness, a topic that he also drives forward in joint teaching activities with the CAI.