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Gabriele KotsisView profile

Professor

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +6 more

Gabriele Kotsis is a Full Professor at the Institute of Telecooperation, Johannes Kepler University Linz, with extensive contributions to Artificial Intelligence research. Her institutional presence spans multiple departments through interdisciplinary projects while maintaining her primary affiliation with JKU's engineering-focused research units. Her research expertise encompasses: Natural Language Processing and Neural Machine Translation systems Reinforcement Learning applications for Smart Grid optimization Mobile Computing and Multimedia Intelligence frameworks Big Data Analytics and Database Systems innovation Human-centered AI development methodologies Recent publications (2024-2025) reveal a strategic focus on practical AI implementations addressing multilingual communication barriers and energy efficiency challenges. Her work consistently bridges theoretical AI advances with real-world applications across multiple domains. Professor Kotsis maintains an active supervision record with thesis guidance and leads multiple funded research initiatives. Her current portfolio includes: 'Enhancing Neural Machine Translation' project (2025-2026) for Southeast Asian languages 'INTES' regulatory compliance ecosystem (2023-2026) 'Human-centered Artificial Intelligence' initiative (2022-2026) Through her leadership in international conferences (iiWAS, MoMM, DEXA) and editorial roles for major proceedings, she maintains significant influence in the global computer science research community while advancing JKU's research profile.

• Business Informatics
• Data Science
• Knowledge Engineering
• +6 more

Michael Schrefl is a Full Professor at Johannes Kepler University Linz, affiliated with the Institute of Business Informatics - Data & Knowledge Engineering. He serves as Principal Investigator on multiple research projects including AWARE (2024-2026) and AISA (2020-2022), and is actively involved in European research collaborations as both PI and researcher on funded projects. His research interests span across several key areas in modern data science and business informatics: Business Informatics and Digital Transformation Data Science and Knowledge Engineering Database Systems and Data Mining Semantic Technologies and Information Systems Predictive and Prescriptive Analytics Enterprise Computing and Information Systems Professor Schrefl's recent publication activity shows a strong focus on reliability assessment in predictive analytics, conceptual modeling for business intelligence, and applications of data science in Industry 4.0 contexts. His work bridges theoretical foundations with practical applications in enterprise information systems, particularly examining data quality and reliability in predictive models. As an active member of the academic community, Professor Schrefl serves on program committees for major conferences including BI-WEEK, EDOC, and DATA. He has supervised 129 students throughout his career and contributes to educational technology through projects like eTutor++. His research spans multiple fields of science including Knowledge Engineering, IT Security, Web Engineering, and Distributed Systems. Professor Schrefl maintains strong engagement with both academic and public discourse, having given invited talks on AI topics in 2024 and scheduled media appearances including an Ö1 interview on autonomous weapons systems for 2025, demonstrating his commitment to science communication and societal impact of technological developments.

Hirut GrossbergerView profile

Professor

• Railway Engineering
• Sustainable Mobility
• Infrastructure Lifecycle Assessment
• +2 more

FH-Prof. Dr. Hirut Grossberger is a Senior Researcher at the Carl Ritter von Ghega Institute for Integrated Mobility Research and International Coordinator for the Department of Rail Technology and Mobility at University of Applied Sciences St. Pölten. She teaches in three programs: Rail Technology and Management of Railway Systems (MA), Rail Technology and Mobility (BA), and Rail Vehicle Technology (BA). Her research bridges railway engineering, sustainable infrastructure, and digital mobility solutions. Education includes: BSc in Agricultural Engineering (Debub University, Ethiopia) MSc in Water Management and Environment (BOKU Vienna) MSc in Land Management, Infrastructure and Civil Engineering (BOKU Vienna) Doctoral research at Institute of Structural Engineering (BOKU Vienna) Research focuses on: Railway Technology : Infrastructure lifecycle assessment, noise reduction, and sensor-based monitoring Sustainable Mobility : Eco-materials (e.g., clay noise barriers), emission reduction, and circular economy applications Digital Transformation : Mobile inspection tools, digital product passports, and acoustic sensing systems Recent publications (2019-2025) emphasize sustainability in transport infrastructure, with trends toward: Environmental action programs (CLEA) Eco-material innovation for noise control Distributed Acoustic Sensing for rail safety Digital tools for infrastructure management Leads/contributes to 20+ EU projects including: STAFFER (rail skill development) ZeroEmissionCityBahn (sustainable infrastructure) DPP4ALL (digital product passports) Smart Inspection (AI-assisted bridge maintenance) ECO-TCO (operational efficiency)