Simon Kranzer is a Senior Lecturer and Head of Research Group at the Department of Information Technologies and Digitalisation, FH Salzburg. His work bridges academic research and practical application in digital transformation. Location: Campus Urstein, Room 425 Contact: simon.kranzer@fh-salzburg.ac.at | +43-50-2211-1316 Research Focus: Digital Twins for industrial systems Collaborative Robotics (Co-Bots) in retail Knowledge Transfer between academia and industry Operational Technology (OT) Security Data Acquisition and Visualization Programming Language Applications in industrial contexts Research Trends: Recent publications show expertise in retail automation (service robots, customer behavior analysis), industrial digital twins, and OT security. Earlier work spans GIS-SCADA integration, medical software implementation, and 3D microstructure analysis. Collaborative Projects: Active in interdisciplinary living labs, smart factory bootcamps, and 5G-based robotics exploration.
Prof. Dr. rer. nat. Reiner Creutzburg is a professor at the Brandenburg University of Technology Cottbus-Senftenberg in the Department of Computer Science and Media , specializing in Applied Computer Science with a focus on Algorithms and Data Structures . Research Focus: Cybersecurity, Machine Learning, Computer Vision, IoT Security, Open Source Intelligence (OSINT), and Critical Infrastructure Protection Recent Trends: Over 15 recent publications explore AI-driven cybersecurity solutions, image/video processing for event management, and secure voting systems using blockchain.
Burcu ÇARKLI YAVUZ serves as an Assistant Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Information Systems Engineering. Her academic career spans over a decade with continuous contributions since 2013, including current administrative roles as Dean's Assistant (2023-2024) and Department Vice Chair (2021-2023). Education: PhD in Computer and Information Engineering (2019), Sakarya University - Thesis: 'Hemoglobin Protein Secondary Structure Prediction by Improved Clonal Selection Algorithm' MS in Computer and Information Engineering (2010), Sakarya University - Thesis: 'A Data Mining Application with Apriori Algorithm in the Healthcare Sector' BSc in Mathematics-Computer Programming (2005), Istanbul Cultural University Her research integrates artificial intelligence with critical applications across healthcare and renewable energy. Specializing in data mining and bioinformatics, she develops novel algorithms for protein structure prediction, medical diagnostics, and photovoltaic system optimization. Current work focuses on Marine Predators Algorithm applications for perinatal mental health screening and adaptive MPPT techniques for solar energy systems, demonstrating interdisciplinary impact from biomedical engineering to climate change mitigation. Publication analysis reveals three dominant research thrusts: (1) AI-driven healthcare solutions (depression/anxiety detection, diabetes diagnosis), (2) Photovoltaic optimization (MPPT algorithms, flicker analysis), and (3) Bioinformatics (protein structure prediction using clonal selection). Her work consistently bridges theoretical algorithm development with practical implementations, evidenced by industry collaborations like the 2023 'Electric Vehicle Regulation-Compliant Sound Alert Systems' project. Teaching responsibilities include graduate and undergraduate courses in Deep Learning, Python Programming, Operations Research, and Introduction to AI. She has supervised numerous graduation projects and taught specialized courses like 'Big Data Technologies' in collaboration with Havelsan. Her editorial service for IEEE Access (2018-2020) and conference organization roles demonstrate academic leadership beyond teaching and research.
Professor Fausto Pedro García Márquez is a faculty member at the University of Castilla-La Mancha leading the Ingenium Research Group. With 458 publications and active 2025 output, he specializes in Maintenance Management (16% research focus), Artificial Intelligence, IoT, and Renewable Energy systems. His research integrates AI and big data analytics for industrial applications including photovoltaic plant maintenance, hydropower condition monitoring, and sustainable textile manufacturing. International collaborations span India, Saudi Arabia, and Pakistan, with co-author networks reflecting strong cross-border research partnerships. Recent work emphasizes practical implementations of intelligent systems in energy infrastructure and business processes. Professor García Márquez's 2025 publications reveal converging trends: IoT-enabled predictive maintenance for renewable energy systems (3/5 papers), sustainable business innovation (1 paper), and AI-driven financial applications (1 paper). This demonstrates strategic focus on applying computational intelligence to sustainability challenges across multiple industrial sectors. The Ingenium Research Group provides a dynamic environment for interdisciplinary work at the AI-energy-sustainability nexus. With 4 active projects and continuous publication output, Professor García Márquez maintains strong research momentum. Prospective students would engage with real-world implementations including SCADA systems for solar plants and unmanned surface vehicle projects.
