Mirko Birbaumer

Mirko Birbaumer is a Professor at the Lucerne School of Engineering and Architecture (HSLU), specializing in data science and machine learning applications. He holds a PhD in computer-assisted image analysis from ETH Zurich and has completed advanced executive education at MIT in Innovation and Strategy.

• PhD in Systems Biology (ETH Zurich, 2010)
• Executive Certificate in Innovation and Strategy (MIT, 2022)
• Advanced Executive Certificate in Innovation, Strategy, and Technology (MIT, 2024)

His research integrates statistical data analysis, computer vision, and digital health, with applications spanning industrial quality control, medical imaging, and environmental monitoring. Recent work focuses on physics-informed neural networks, interpretable anomaly detection, and causal machine learning.

His projects include AI-driven solutions for medical diagnostics, predictive maintenance in manufacturing, and environmental anomaly detection. He has supervised over 20 student theses on topics like deep learning for knee osteoarthritis detection, monocular depth estimation, and AI-assisted logo similarity analysis.

He leads the Data Science profile in the Master of Science and Engineering program and teaches courses on deep learning, Bayesian machine learning, and computer vision. His methodological expertise includes agent-based modeling, statistical analysis, and explainable AI.