جست‌وجوی استاد و پژوهشگر

Cord Hockemeyerمشاهده پروفایل

پژوهشگر

• Technology-supported learning
• Knowledge space theory
• Adaptive knowledge diagnosis
• +۸ مورد دیگر

Cord Hockemeyer is a Senior Research Associate at the Institute of Psychology , University of Graz, since 1999. He also served as a Project Manager at Graz University of Technology's Institute for Knowledge Management (2009-2011) and held a Marie Curie Fellowship at the University of Graz (1998-1999). His work bridges Cognitive Psychology , Knowledge Space Theory , and E-learning Systems through algorithmic modeling and software development. Education Diploma in Computer Science with Psychology focus, TU Braunschweig Research Interests center on adaptive learning technologies , including knowledge diagnosis , competency mapping , and mathematical modeling for educational games and clinical training systems. He specializes in Knowledge Space Theory and its applications in technology-enhanced learning , with a focus on micro-adaptivity and dynamic assessment in complex domains. Scientific Contributions span publications on adaptive algorithms , competency-based education , and simulation-driven learning frameworks. His work integrates ontologies , metadata standards , and grid architectures to enable personalized educational experiences. Awards & Appointments Marie Curie Fellowship (1998) Editorial Board Member, Testing, Psychometrics, Methodology in Applied Psychology (2016-present) Active reviewer for journals like Journal of Mathematical Psychology and Psychological Methods Additional Roles include membership in professional societies (IEEE, Austrian Computer Society) and contributions to EU-funded projects such as Higher Education Learning Platform for Quantitative Thinking (2019-2022). He combines academic research with central administrative duties at the Institute of Psychology.

• System of Systems Engineering
• Smart Grid Architecture
• Model-Based Systems Engineering
• +۳ مورد دیگر

Katharina Polanec serves as a Researcher at the Centre for Dependable Systems Engineering, St. Pölten University of Applied Sciences, and is an active co-investigator in the Josef Ressel Centre for Dependable System-of-Systems Engineering (DeSoS) project (2020-2025), focusing on critical infrastructure systems development. Her research expertise spans: System of Systems Engineering Smart Grid Architecture Model-Based Systems Engineering Cyber-Physical Systems Automotive Systems Reference Architectures With particular emphasis on interoperability frameworks, regulatory compliance mechanisms, and dependable systems modeling for energy and transportation infrastructure. Recent publications (2024) demonstrate concentrated activity in cross-domain architectural integration, EU AI Act compliance engineering, and co-simulation taxonomies, reflecting evolving research trajectories toward legally compliant cyber-physical systems and automotive-smart grid interoperability solutions. As part of the DeSoS project team, she contributes to advancing dependable system-of-systems engineering methodologies through collaborative research with principal investigator Christian Neureiter and colleagues across multiple engineering disciplines.

• Information Retrieval
• Recommender Systems
• Music Information Retrieval
• +۴ مورد دیگر

Associate Professor Peter Knees holds a position at the Technische Universität Wien's Faculty of Informatics, specifically within the Department of Data Science. He serves as a Curriculum Coordinator for the Bachelor's Specialization in Artificial Intelligence and Machine Learning. His research focuses on Information Retrieval, Music Information Retrieval, Recommender Systems, and Digital Humanism. Knees has coordinated major projects such as the Vienna Doctoral College on Digital Humanism (2024–2029) and contributes to initiatives like FAIR-AI and HumRec. He teaches courses including Digital Humanism and Introduction to Information Retrieval. His work bridges technical innovation with ethical considerations, emphasizing transparency and fairness in AI systems. Education: Holds Dipl.-Ing. (TU Wien) and Dr.techn. (Technical Doctorate). His interdisciplinary projects span music technology, ethical AI, and smart grid systems. He has supervised numerous theses on topics like music recommendation algorithms and audio processing techniques. Research Interests: Explores intersections of music technology and AI, including content-driven recommendation systems, reproducibility in machine learning, and the societal impact of digital technologies. Recent work emphasizes ethical frameworks for recommender systems and human-centered design principles. Grants & Projects: Lead roles in WWTF-funded Digital Humanism initiatives, FFG projects on AI innovation, and EU-backed MIR research. Active in organizing conferences like RecSys and ISMIR workshops. Labs/Teams: Involved with the Vienna Doctoral College, TU Wien's Data Science group, and collaborations with institutions like ASEA-UNINET for ethnomusicology data integration. Leads efforts in neural-symbolic systems for smart grids and generative music interfaces.

• Quality of Service
• Service Selection
• Heterogeneous Systems
• +۴ مورد دیگر

Peter Beran is affiliated with the Faculty of Computer Science as a Researcher specializing in distributed systems and service-oriented architectures. His primary research group focuses on Workflow Systems and Technology. His research spans Quality of Service optimization , Service Selection , and Heterogeneous Systems with emphasis on distributed databases and query execution. Key methodologies include genetic algorithms and adaptive frameworks for dynamic environments. His publication trends (2007-2013) reveal consistent contributions to Cloud-based service optimization (40%) QoS-aware distributed systems (35%) Query execution planning (25%) with notable work on grid services and cloud environments. Professional activities include conference presentations on distributed data management frameworks and query optimization techniques, demonstrating active engagement in the research community.

Bernhard Zettlمشاهده پروفایل

پژوهشگر

• Sorption Heat Storage
• Thermochemical Storage Materials
• Hydrogen Applications
• +۳ مورد دیگر

Bernhard Zettl is a researcher at the University of Applied Sciences Wels, affiliated with the ASiC Center of Excellence Energy. He specializes in sorption heat storage, thermochemical storage materials, and hydrogen applications, with a focus on sensor technology for energy storage systems. BioH2Region (2021–2027): Regional hydrogen and green gas research GaSe (2023–2025): Hydrogen application materials SorSens (2021–2022): Sensor development for thermal storage TCMix (2021–2024): Salt-mixture thermochemical storage His research explores sorption heat storage, zeolite-based systems, and microwave desorption techniques for efficient energy management. He collaborates on projects like RESINET, addressing energy grid resilience and renewable integration. Key topics include material characterization, load management, and sensor innovation. Recent publications highlight his work on virtual sensors, NIR spectrometry, and high-pressure hydrogen storage materials. Collaborations span institutions in Austria and Bavaria, with contributions to computed tomography and material diagnostics.

Andrea Scaglioniمشاهده پروفایل

پژوهشگر

• Uncertainty Quantification
• Partial Differential Equations
• Computational Mathematics
• +۳ مورد دیگر

Andrea Scaglioni is a Postdoctoral Researcher in computational mathematics at the University of Vienna since October 2024, working under Professor Ilaria Perugia. He received his Ph.D. from the Technical University of Vienna (TU Wien) in October 2024, focusing on stochastic dynamics in micromagnetic systems, and holds a Master's degree in Computational Science and Engineering from EPFL (Switzerland, 2019). His academic background includes: Ph.D. in Computational Mathematics, Technical University of Vienna (TU Wien), 2024 Master's in Computational Science and Engineering, EPFL, Switzerland, 2019 Scaglioni specializes in Uncertainty Quantification for Partial Differential Equations using high-dimensional interpolation methods like Sparse Grid Interpolation to construct surrogate models. His research targets stochastic micromagnetics, particularly the Landau-Lifshitz-Gilbert equation, with applications in modeling magnetic hysteresis phenomena. He actively contributes to Austria's numerical analysis community through conferences and collaborations within Prof. Perugia's research group. His recent presentations include talks at the Annual ÖMG-DMV Meeting (Linz, September 2025), the International Symposium on Hysteresis Modeling and Micromagnetics (Torino, May 2025), and workshops on stochastic PDEs at TU Wien (September 2024). These highlight his focus on surrogate modeling, reduced-order methods, and sparse grid techniques for stochastic dynamics in magnetic systems.

• Power Distribution Systems
• Smart Grids
• Machine Learning Applications
• +۴ مورد دیگر

David Fellner is a Senior Lecturer and Program Director for Renewable Energy Engineering at the University of Applied Sciences Technikum Vienna. He leads the Renewable Energies degree program (Bachelors & Masters) and is involved in the COIN research project 'GridEdge', which focuses on expanding lab infrastructure incorporating PV, EVSE, and DC microgrids for contract research. His educational background includes: Doctoral program in Engineering Sciences (Computer Sciences concentration) at Vienna University of Technology (2020-2024), graduating with distinction. Dissertation: 'Data Driven Detection of Misconfigurations in Power Distribution Systems' MSc in Energy and Automation Engineering (2016-2019) BSc in Electrical Engineering and Information Technology (2012-2016) ERASMUS Semester at NTNU, Trondheim, Norway (Spring 2018) ERASMUS Semester at Politecnico di Milano, Italy (Spring 2015) Dr. Fellner's research focuses on the intersection of power systems engineering and data science, particularly applying machine learning techniques to power distribution systems. His work addresses critical challenges in modern grid management including misconfiguration detection, anomaly identification, and reliability improvement. He has developed frameworks for data-driven malfunction detection in power systems, with applications in both public and industrial grids. His expertise spans DC microgrids, renewable energy integration, and AI applications for grid monitoring and optimization. His publication record demonstrates a clear trajectory of increasingly sophisticated applications of machine learning to power system challenges. Starting with foundational work on data-driven malfunction detection, his research has evolved to include transformer profile disaggregation, deep learning applications, and the development of open-source frameworks like DeMaDs. The publications reveal a strong focus on practical implementations that address real-world grid issues, particularly as renewable energy sources become more integrated into power distribution systems. Dr. Fellner has been actively involved in research projects including DeMaDsPilot (data-driven malfunction detection), Parmenides (AI-based state estimation), and support for projects like PoSyCo, TheBuilding, and EASE. He has also provided training for OVE on 'Power Quality' and has supervised numerous Bachelor theses. His laboratory work centers around the COIN research project 'GridEdge', which expands lab infrastructure incorporating photovoltaics, electric vehicle supply equipment, and DC microgrids for contract research purposes. This facility enables practical testing and validation of his theoretical work on grid monitoring and optimization.

Jounes-Alexander Grossمشاهده پروفایل

پژوهشگر

• Co-simulation
• Smart Grid
• System of Systems
• +۵ مورد دیگر

Jounes-Alexander Gross is a Researcher at Salzburg University of Applied Sciences, affiliated with the Information Technologies and Digitalization Center for Dependable Systems Engineering. He contributes to two major projects: the Research Campus Urstein Castle (RCSU, 2023-2025) and the Josef Ressel Centre for Model-Based Development of Safe Systems (JRZ DeSoS, 2020-2025). His primary research interests span co-simulation , smart grid architectures , system-of-systems engineering , and reference modeling . He investigates cross-domain interoperability between automotive and energy systems, develops domain-specific modeling frameworks, and addresses sector coupling in low-temperature anergy grids. His work aligns with UN Sustainable Development Goals for affordable and clean energy. Recent publications (2024-2025) reveal a concentrated effort on co-simulation techniques for integrating smart grids and automotive systems. Key contributions include model taxonomies, interoperability solutions, and architectural assessments that advance dependable systems engineering. Scientific recognition includes: Best Paper Candidate award (2024) for research on architectural models in smart grid co-simulations. Gross participates as project staff in externally funded research initiatives (RCSU and JRZ DeSoS) but no student advising information is available. He operates within the Center for Dependable Systems Engineering at the Research Campus Urstein Castle, collaborating on cutting-edge projects in dependable systems and digitalization.

Christoph Langمشاهده پروفایل

مدرس

• Physiotherapy
• Musculoskeletal Disorders
• Digital Forensics
• +۴ مورد دیگر

Christoph Lang is a Lecturer at the Department of Health Sciences within the Institute of Health Sciences at the University of Applied Sciences St. Pölten (FH St. Pölten). Holding degrees of PT (Physiotherapist), BSc, and MSc, his academic and professional work bridges health sciences and digital forensics/cybersecurity education. Research Interests : Musculoskeletal disorder rehabilitation (e.g., frozen shoulder treatment) Digital forensics aligned with the NICE Framework Cybersecurity education through simulation games Agent-based modeling of network behavior Biometric authentication on mobile devices Advanced metering infrastructures Publications highlight interdisciplinary work spanning physiotherapy, cybersecurity, and simulation technologies. While no scientific awards are explicitly mentioned in the provided texts, his contributions to practice-oriented education and musculoskeletal research are notable.

Leopold Haimbergerمشاهده پروفایل

استاد

• Atmospheric General Circulation Diagnostics
• Radiosonde Data Homogenization
• Numerical Weather Prediction
• +۴ مورد دیگر

Leopold Haimberger is a Professor at the University of Vienna , affiliated with the Institute of Meteorology and Geophysics under the Faculty of Earth Sciences, Geography and Astronomy . He has been actively involved in teaching courses such as Climate Dynamics and Diagnostics , Data Assimilation and Ensemble Methods , and Scientific Communication . His research focuses on atmospheric general circulation diagnostics, radiosonde data homogenization, and numerical weather prediction, with significant projects including Arctic energy budget analysis and European climate reanalysis initiatives. Research Themes Atmospheric transport mechanisms Climate model validation Ocean-atmosphere interactions Historical climate data recovery Recent Publications 2024: StraitFlux for ocean modeling 2024: Radiosonde position correction 2023: North Atlantic heat flux trends 2023: Indonesian Throughflow validation Scientific Collaborations Working with international teams on CMIP6 models Leading Arctic climate analysis projects Contributing to global radiosonde homogenization

• Autonomous Systems
• Computer Vision
• Sensor Technology
• +۵ مورد دیگر

Prof. Daniel Watzenig is a Full Professor at Graz University of Technology's Faculty of Electrical Engineering and Information Technology, affiliated with the Institute of Visual Computing and the Institute of Electrical Measurement and Sensor Technology. He serves as Dean of Studies for Digital Engineering (DE), overseeing academic programs in this field. His research focuses on autonomous systems, sensor fusion, and advanced control strategies for vehicles, with a strong emphasis on LiDAR technology, path planning algorithms, and real-time environmental perception systems. He holds academic qualifications including Dipl.-Ing. (FH) and Dr.techn. degrees. Research interests span robotics, computer vision, and machine learning applications in transportation systems. His work addresses challenges in autonomous vehicle navigation, sensor reliability under adverse conditions, and safety-critical system validation. Recent publications highlight innovations in thermal-LiDAR fusion, trajectory optimization, and radar-based occupancy grids. He actively contributes to interdisciplinary projects involving co-simulation frameworks and virtual validation methodologies for automated driving functions. Professional roles include leading academic programs in digital engineering and managing research collaborations at TU Graz. His technical expertise is reflected in over 100 publications (2020-2025) covering sensor technology, path planning algorithms, and autonomous system validation. Key labs/teams associated include the Institute of Visual Computing's autonomous systems group and the Electrical Measurement Institute's sensor innovation team.

Thomas Takacsمشاهده پروفایل

پژوهشگر

• Isogeometric Analysis
• Computational Mechanics
• Numerical Analysis
• +۳ مورد دیگر

Dr. Thomas Takacs is a Project Leader in the Geometry in Simulations research group at the RICAM (Research Institute for Symbolic Computation), part of the Austrian Academy of Sciences. His work focuses on advancing computational methods for solving partial differential equations, particularly through isogeometric analysis and spline-based numerical techniques . His research interests include smooth basis constructions, multi-patch domain coupling, and adaptive mesh refinement strategies. Key contributions involve developing C1-continuous spline spaces over planar mixed meshes and unstructured quadrilateral meshes, with applications to engineering problems like linear elasticity. He explores the integration of machine learning (e.g., CNNs) for optimizing quad meshing and employs artificial neural networks in adaptive optimization frameworks. His work bridges geometric modeling and numerical analysis, addressing challenges such as singularity treatment in isogeometric analysis and approximation properties over self-similar meshes. Dr. Takacs collaborates on multi-institutional projects, including the Geometry in Simulations group at RICAM. His publications span computational mechanics, numerical methods, and geometric algorithms, with a focus on advancing the theoretical foundations and practical implementations of isogeometric analysis.

• Cyber-Physical Systems
• Smart Grids
• Swarm Intelligence
• +۵ مورد دیگر

Prof. Wilfried Elmenreich is a Professor at the Department of Networked and Embedded Systems at Alpen-Adria-Universität Klagenfurt. He serves as a Member of the Senate and Member of the Works Council for Academic Staff. His research focuses on Cyber-Physical Systems, Smart Grids, Swarm Intelligence, and Sustainability Technologies. He leads projects involving swarm robotics, decentralized energy management, and educational technology. Key research areas include: Design of swarm-based algorithms for production scheduling and robotics Development of frameworks like SwarmFabSim for bottom-up optimization Non-Intrusive Load Monitoring (NILM) using neural networks and edge computing Integration of federated learning into smart grid systems Sustainability education and pandemic-related behavioral studies His work combines theoretical contributions with practical implementations, such as the CPSwarm project for swarm system design and the Yomopie energy monitoring tool. Recent publications emphasize interdisciplinary approaches, blending robotics, machine learning, and electrical engineering to address challenges in energy systems and autonomous systems.

Dieter Fellnerمشاهده پروفایل

استاد

• Computer Graphics
• Digital Libraries
• Computational Geometry
• +۱۰ مورد دیگر

Dieter Fellner is a Professor of Computer Science at Technical University of Darmstadt, Germany , and Director of the Fraunhofer Institute of Computer Graphics (IGD) . He also serves as Founding Director of the Institute of Computer Graphics and Knowledge Visualization at Graz University of Technology, Austria. His career spans multiple prestigious institutions including University of Bonn, Memorial University of Newfoundland, and University of Technology Braunschweig. Dr. Fellner's research focuses on algorithms integrating modeling and rendering , digital libraries , virtual/augmented reality , collision detection , and radio wave propagation simulation . His work in digital libraries led to a DFG-funded strategic initiative (1997-2005) involving 50 researchers annually across 21 groups. The 15 most recent articles highlight his expertise in 3D document modeling , stereoscopic projection , subdivision surfaces , and color quantization . His publications include influential textbooks like the German standard on computer graphics (1988) and Digitale Bibliotheken (2000). 2000 Fellow of the Eurographics Association Best Technical Paper Award (Günther Enderle Award) at Eurographics’98 2007 IST Advisory Group (ISTAG) Member for the European Commission 2019 Honorary Doctorate from University of Rostock Dr. Fellner actively participates in editorial boards of journals like Computer Graphics Forum , IEEE CG&A , and JOCCH , and serves on program committees for conferences such as Eurographics, VSMM, and ACM Web3D. His leadership roles include Chairmanship of the Eurographics Association (1999-2000) and Directorship of Fraunhofer IGD (since 2006).

• Power Grid Optimization
• Electric Vehicle Technology
• Automation Systems
• +۳ مورد دیگر

Franz Auinger is a Professor at the University of Applied Sciences Wels, affiliated with the Research Center Wels Center of Excellence in Automotive/Mobility. His research focuses on power grid optimization, electric vehicle technology, automation systems, and optimization algorithms. He has led projects like the SSH Basssaiten (2012-2013) and Clean Motion Offensive (2011-2012) as Principal Investigator. His work spans theoretical advancements in metaheuristic optimization for power systems, practical applications in autonomous robotics education, and human-computer interaction studies. Notable contributions include developing control policies for smart grids and project-based learning methodologies in mechatronics. Projects: 2 completed research projects Publications: 33 outputs with 272 citations (h-index 8) His advising and grants include supervising two academic works and managing research initiatives focused on automotive innovation and clean mobility technologies.