Ulrich Bodenhofer

Ulrich Bodenhofer serves as a full-time Professor for Artificial Intelligence at Upper Austria University of Applied Sciences (Hagenberg campus) since September 2020, while maintaining a part-time role as Chief Artificial Intelligence Officer at QUOMATIC.AI since June 2018. His institutional affiliations include Research Center Hagenberg AIST and multiple Centers of Excellence: Automotive/Mobility, Medical Technology/TIMed, Smart Production, Computed Tomography, and Digital Transformation within the Strength area of ICT - Information & Communication Technology.

His academic credentials include a Habilitation (2003), Dr. techn. (1998), and Dipl.-Ing. (1996), all in Technical Mathematics from Johannes Kepler University Linz. His research focuses on applying fuzzy logic systems to practical problems across healthcare, industry, and finance. Key areas include:

• Machine Learning & Artificial Intelligence in Sales Analytics
• Healthcare and Bioinformatics applications
• Nondestructive Testing methodologies
• Financial Condition Monitoring systems

His publication record shows consistent output since 1996 with 74 publications, demonstrating evolving expertise from foundational fuzzy logic research to current AI applications in medical imaging and industrial processes. Recent work emphasizes human-centered AI approaches, explainable systems, and practical implementations addressing real-world challenges in critical infrastructure and healthcare diagnostics.

Bodenhofer actively leads and participates in significant research projects including HCAI (2022-2027), FLARE (2025-2027), and iReduce (2025-2026), securing funding from diverse sources including FWF - doc.funds.connect and KIRAS cooperative research programs. His collaborative approach spans multiple disciplines and institutions, reflecting the interdisciplinary nature of modern AI research.

His professional activities include 54 scientific engagements through 2025, featuring numerous invited lectures on AI applications across finance, healthcare, and industrial contexts. He has supervised 9 academic works according to institutional records, mentoring the next generation of AI practitioners through hands-on research projects focused on practical implementation challenges.