جست‌وجوی استاد و پژوهشگر

Joaquín Tintore Subiranaمشاهده پروفایل

استاد پژوهشی

• Ocean observing systems
• Mesoscale and submesoscale eddies
• Physical oceanography
• +۱ مورد دیگر

Joaquín Tintore Subirana is a Research Professor at the Mediterranean Institute for Advanced Studies (IMEDEA) , a joint research institute of the Spanish National Research Council (CSIC) and the University of the Balearic Islands (UIB) . He serves as Director of SOCIB (Balearic Islands Coastal Observing and Forecasting System) since 2009 and as Institutional Coordinator of CSIC in the Balearic Islands since 2006. His career spans over 35 years in physical oceanography and operational oceanography. Education : Grade in Physics (1984), University of Barcelona PhD in Physics (1988), University of Barcelona Awarded CSIC Research Professor (2000) Research Interests : Specializing in ocean observing systems , his work focuses on mesoscale and submesoscale eddies , coastal ocean dynamics , and climate change impacts on marine environments. His research integrates glider-based microstructure measurements , high-frequency radar , and satellite data to study Western Mediterranean processes . Recent publications examine turbulence datasets , greenhouse gas distributions , and extreme weather impacts on coastal zones. He has developed digital twin tools for coastal adaptation planning and contributed to international marine policy frameworks. Scientific Awards : 2003 National Research Award 'Alejandro Malaspina' for mesoscale oceanography contributions Advising & Leadership : Supervisor of 10 PhD theses , he has led major multi-platform oceanographic campaigns like AlborEX and SMART missions . As director of IMEDEA (1999-2008), he coordinated 55 peer-reviewed projects and shaped Spain's marine infrastructure policy . Labs & Collaborations : Leads the Marco Zavatarelli Lab at IMEDEA, collaborating with European research networks including Euro-GOOS , Euro-Argo ERIC , and Science Europe Working Group . His work integrates with Copernicus Marine Service and OceanGliders programs.

Daniel Sieberمشاهده پروفایل

مدرس

• Medical Technology
• Health Technologies
• Surgical Simulation
• +۶ مورد دیگر

Dr. Daniel Sieber serves as Head of the Department and Study Programs in Medical, Health, and Sports Technologies at MCI | The Entrepreneurial School®. He holds a Dr. rer. biol. hum. (Summa Cum Laude) from Hannover Medical School and a Dipl.-Ing. in Mechanical Engineering (Biomedical Engineering) from the University of Stuttgart. His academic roles include full-time lecturer and researcher with a clinical-medical focus. Research Interests: Dr. Sieber specializes in medical technologies, particularly focusing on surgical simulation using virtual reality (VR), cochlear implant innovation, minimally invasive surgery techniques, and 3D printing applications in healthcare. His work bridges engineering and medicine, emphasizing translational research and interdisciplinary education. Teaching & Leadership: He leads courses in Medical Technologies, Product Development, and Implantable Devices at MCI. Recent activities include visiting professorships in Shenzhen, China, and supervising over 20 bachelor's and master's theses in medical device engineering and surgical training technologies. Key Awards: 2023 MCI Teaching Award Patents: Includes designs for cochlear implant electrodes and surgical tools Networks: Member of Tyrol's Life Sciences Cluster Advisory Board Grants & Labs: His research has driven partnerships with institutions like Hannover Medical School and MED-EL GmbH. Active in developing VR surgical training platforms and digital twins for healthcare systems.

Anita Onayمشاهده پروفایل

استاد

• Production Management
• Supply Chain Management
• Operations Research
• +۵ مورد دیگر

Anita Onay is a Professor of Production Management at MCI Management Center Innsbruck. She holds a PhD in Production Management from the University of Innsbruck (2012–2016) and a Mag. rer. soc. oec. in Business Administration with a focus on Production and Logistics (2004–2010). Her academic career includes roles as Senior Lecturer (2021–2023), Lecturer (2018–2021), and Research Assistant (2016–2018) at MCI. She is actively involved in professional associations including the EURO Working Group on Behavioral OR (Coordination Board Member since 2022) and the Industry 5.0 Community of Practice (EU member since 2023). Her research focuses on integrating behavioral aspects into production and supply chain systems, with emphasis on simulation-based decision support, stochastic processes, and human factors in operations. Key areas include hierarchical production planning, lead time management, and behavioral workload control. She has led projects such as the Tyrolean Innovation Funding initiative on digital traceability in timber trade (2022–2024) and a TWF-funded study on lean production in SMEs (2017). Teaching responsibilities span Industrial Engineering and Mechatronics programs at MCI, covering courses like Production Planning & Control, Simulation & Optimization, and Lean Practice Lab. She advises over 40 students in bachelor and master theses, focusing on topics like production simulation, lean manufacturing, and Industry 4.0 implementation. Notable achievements include the 2023 Innsbruck Prize for Research and Innovation for her doctoral work on behavioral operations. She also received a PhD Program Support Grant from the University of Innsbruck (2014). Her professional experience includes roles as a project manager in quality management (GE Jenbacher, 2008–2009) and IT project leadership (Auviso Ltd., 2010–2014).

• Causal Inference
• Machine Learning
• Statistical Modeling
• +۴ مورد دیگر

Dr. Lucas Kook is a Researcher at the Department of Statistics and Mathematics, WU Vienna University of Economics and Business. His research focuses on causal inference, machine learning, and statistical modeling, with applications in sports analytics, medical data analysis, and healthcare outcomes. He actively develops R packages such as deeptrafo for neural network-based statistical inference. His work bridges theoretical advancements in distributional regression and practical implementations in healthcare and sports domains. Key research areas include algorithm development for significance testing in supervised learning, causal feature selection, and nonparametric methods for conditional independence. Recent studies explore the efficacy of thrombolytic therapies in retinal artery occlusion and the predictive power of deep learning models in stroke patient outcomes. Collaborations span interdisciplinary fields, emphasizing reproducibility and methodological rigor in simulation studies.

Elisa Davoliمشاهده پروفایل

استاد

• Materials Science
• Partial Differential Equations (PDEs)
• Calculus of Variations
• +۷ مورد دیگر

Elisa Davoli is a Professor of Multiscale Calculus of Variations at the Vienna University of Technology (TU Wien), leading the Research Group Multiscale Variational Calculus . She holds a PhD from SISSA (Trieste) and has earned prestigious awards including the Richard von Mises Prize (2020) and FWF START Prize (2020). Her research focuses on materials science, calculus of variations, and PDEs, with applications to elasticity, phase transitions, and image reconstruction. She teaches courses like Mathematics for Electrical Engineering and Gamma Convergence , and actively organizes international workshops on topics like Shape Optimization and Multiscale Modeling . Her work bridges mathematical analysis and material science, addressing challenges in metamaterials, homogenization, and nonlocal effects. Research Interests : Homogenization, magnetoelasticity, fracture mechanics, calculus of variations, nonlocal models. Key Projects : FWF-SFB grants, START Prize research on tunable materials, and international collaborations with institutions like UTIA (Prague). Awards : Richard von Mises Prize (GAMM, 2020), FWF START Prize (2020), Faculty Teaching Award (2018). Her publications span over 60 papers in journals like Archive for Rational Mechanics and Analysis and SIAM Journal on Mathematical Analysis , addressing topics from morphoelasticity to Cahn-Hilliard systems. She also supervises research groups and contributes to the SFB Taming Complexity in Partial Differential Systems initiative.

• Disaster Risk Management
• Environmental Policy
• Public Safety
• +۳ مورد دیگر

Renate Renner is a Professor and Chair of Thermal Processing Technology. Her research focuses on disaster risk management, environmental policy, public safety, and climate change adaptation. She has actively contributed to interdisciplinary studies involving Serbia, Austria, and other regions, addressing issues like security perceptions among students, vulnerability to climate change impacts, and governance challenges in environmental management. Recent activities include organizing the CRETE 2025 conference on industrial waste management, chairing international symposiums, and serving on committees for risk assessment. Her work emphasizes qualitative and quantitative methodologies to analyze societal resilience and policy effectiveness. Collaborations span academic and governmental institutions, with a focus on Balkan and Central European regions. She has published extensively in peer-reviewed journals and contributed to edited volumes on quality of life and environmental sustainability.

• Infectious Disease Research
• Virology
• Transfusion Medicine
• +۳ مورد دیگر

Christoph Grabmer is a Senior Consultant at the University Institute for Transfusion Medicine, Paracelsus Medical University. His work focuses on virology, immunology, and transfusion medicine with a strong emphasis on SARS-CoV-2 research, including antibody persistence, reinfection dynamics, and blood donor surveillance. He has organized multiple conferences such as the Apheresis Symposium St. Gilgen and serves on committees like the Austrian Society for Blood Group Serology and Transfusion Medicine. His research integrates clinical and epidemiological approaches to address infectious disease challenges, particularly related to pandemic response and healthcare technology innovation. Contact: christoph.grabmer@stud.pmu.ac.at Education: Not explicitly listed in text Research Interests: SARS-CoV-2 pathogenesis, reinfection mechanisms, transfusion safety, and medical device optimization Recent activities include evaluating photopheresis systems and investigating health literacy impacts on infection risks. His work bridges basic science with clinical applications, emphasizing translational outcomes.

• Model-Driven Engineering
• AutomationML
• Cyber-Physical Systems (CPS)
• +۵ مورد دیگر

Manuel Wimmer is a Professor affiliated with the Department of Business Informatics at TU Wien's Faculty of Informatics. His main research area is Model-Driven Engineering , focusing on topics such as AutomationML, Cyber-Physical Systems (CPS), and industrial standards like IEC 62264 and ISA-95. He leads the Network Lab and contributes to interdisciplinary projects involving robotics, cloud computing, and blockchain applications. Research Interests: Model Transformation, Tool Interoperability, Industrial Automation, Educational Methodologies in Software Engineering. Key Technologies: UML, ATL, OPC UA, AutomationQL. Recent work emphasizes bridging metamodeling platforms (e.g., ADOxx/EMF integration) and adapting robotic mission planning systems. He has published extensively in workshops like MDE 2023 and conferences on model-driven engineering. Teaching activities include remote-learning strategies for software engineering education, as documented in his 2021 paper. No explicit awards are listed, but his contributions to standards like AutomationML reflect industry recognition.

Thomas Michael Fischerمشاهده پروفایل

پژوهشگر

• Technostress
• NeuroIS
• Digital Stress
• +۴ مورد دیگر

Thomas Michael Fischer is a Researcher at FH Steyr, affiliated with the LOGISTIKUM and Research Center Steyr. His work focuses on Technostress, NeuroIS, Digital Stress, and Artificial Intelligence in Supply Chain Management. He leads and collaborates on projects such as 'Taking an Active Approach to AI Capability Maturity Engineering' and 'LOG-Logistikum.Retail 2.0', addressing digital transformation and resilience in logistics. His research includes developing assessment tools like the Digital Stressors Scale (DSS) and exploring cybersecurity in supply chains. Fischer has published widely on topics ranging from AI capabilities in Austrian supply chains to the impact of digital badges on education. He holds a doctoral degree and is actively involved in academic conferences and peer-review activities. Key collaborations include projects with industry partners and international teams, addressing challenges in cyber risks, supply chain resilience, and retail logistics. His contributions span over 40 publications, with a strong focus on applying digital technologies to solve real-world logistical and organizational issues.

• Virtual Reality in Rehabilitation
• Biomechanics
• Motion Analysis
• +۳ مورد دیگر

Mark Simonlehner is a Junior Researcher at the Institute of Health Sciences, Department of Health Sciences at Steyr University of Applied Sciences. His work focuses on applying virtual reality (VR) and advanced motion capture technologies to study human movement biomechanics and rehabilitation engineering. He holds an MSc in Biomedical Engineering and has contributed to projects such as VReeze, ULTRASKEL3D, and ReMoCap-Lab, exploring applications of VR in healthcare and motion analysis. Education: Master's in Health and Rehabilitation Technology (2017–Present), Bachelor's in Biomedical Engineering (2013–2017). Prior to academia, he worked as a carpenter and attended the Holztechnikum Kuchl (2004–2009). Research interests include gait analysis, wearable sensor technologies, and improving clinical assessment methods through VR. His publications emphasize the effects of VR on dynamic balance, motion variability, and joint alignment in rehabilitation contexts. Key collaborations involve studies on exergame development for physical activity promotion and biomechanical validation of VR systems against traditional force plate measurements. His work bridges clinical needs with innovative engineering solutions in health sciences.

• Stochastic Processes
• Applied Mathematics
• Computational Mathematics
• +۳ مورد دیگر

Erika Hausenblas holds the position of Chair of Applied Mathematics. Her research focuses on stochastic processes, computational mathematics, and their applications in fluid dynamics and mathematical biology. She actively participates in international conferences such as the World Congress in Probability and Statistics and the Symposium on Sparsity and Singular Structures. Her work spans theoretical developments in stochastic partial differential equations and practical applications in ecological modeling and financial mathematics. Research Interests: Stochastic Analysis, Numerical Methods for SDEs, Fluid Dynamics, and Mathematical Biology. Recent Activities: Invited talks at CRC 1283 and participation in workshops on aggregation-diffusion equations.

• Statistical Methods
• Machine Learning
• Materials Science
• +۵ مورد دیگر

Matthias Neumann is an Assistant Professor at the Institute of Statistics, Graz University of Technology . He completed his PhD in 2020 at Ulm University under Prof. Volker Schmidt, earning the PhD prize of Ulm University . His research focuses on stochastic 3D modeling and statistical analysis of micro- and nanostructures for functional materials, including battery electrodes , fuel cells , and paper-based materials . He has received start-up funding from ProTrainU (2020-2022) and served as principal investigator in the POLiS Cluster of Excellence (2022-2023). Research Interests: His work integrates mathematical morphology , machine learning , and spatial statistics to develop methods for microstructure quantification , estimation of geometrical descriptors (e.g., tortuosity, constrictivity), and data-driven models linking morphology to effective physical properties . He utilizes random fields , point processes , and copulas for virtual microstructure generation and parameter estimation. Teaching: He lectures on Applied Statistics , Statistical Modeling , and Mathematical Statistics at Graz University of Technology, with prior teaching experience at Ulm University in Multivariate Stochastic Modeling , Point Processes , and Spatial Statistics . Scientific Achievements: PhD prize of Ulm University (2020) ProTrainU start-up funding (2020-2022) POLiS Cluster of Excellence grant (2022-2023) Publications: His 15 most recent articles (2023-2025) emphasize machine learning techniques for microstructure segmentation , stochastic 3D modeling of nanoporous materials , and data-driven quantification of transport-property relationships . Key topics include random forests , neural networks , and R-vine copulas applied to fuel cells , sodium-ion batteries , and polymer electrolytes .

• Freshwater Ecology
• Aquaculture
• Fisheries Management
• +۴ مورد دیگر

Gerold Winkler is a researcher at the Institute of Hydrobiology and Aquatic Ecosystem Management , part of the Department of Ecosystem Management, Climate and Biodiversity at the University of Natural Resources and Life Sciences, Vienna (BOKU) . With a focus on freshwater ecosystems in Eastern Africa and Europe, his work bridges ecological research with capacity-building initiatives. Projects: FreshNet (2024-2027), SWAQ Uganda (2021-2025), AQUAHUB II (2021-2024) Research interests center on fish ecology , water quality management , and ecosystem-based conservation . His work emphasizes sustainable fisheries, climate adaptation, and the ecological significance of large river systems, particularly the Danube and Eastern African lakes. Knowledge transfer includes leadership in educational programs like the International Joint Master Degree in Limnology & Wetland Management, with publications spanning genetic analysis , habitat modeling , and development policy . Current projects address freshwater conservation in the Lake Victoria basin and aquaculture optimization in Ethiopia.

• Symbolic Computation
• Machine Learning
• Computer Algebra
• +۲ مورد دیگر

Tereso del Rio Almajano is a Researcher at the Research Institute for Symbolic Computation (RISC), Johannes Kepler University, Linz, Austria. His work focuses on optimizing Cylindrical Algebraic Decomposition (CAD) algorithms through machine learning and heuristic development to address doubly exponential computational complexity in symbolic computation. He earned his PhD from Coventry University's Centre for Computer Science and Mathematical Modelling under supervisors Dr. Matthew England, Dr. AmirHosein Sadeghimanesh, Prof. Vasile Palade, and Dr. Kamal Bentahar. His dissertation, "Heuristics and Machine Learning to Improve Symbolic Computation Algorithms: Speeding Up Quantifier Elimination", pioneered methodologies for accelerating CAD while ensuring output validity. His research spans Symbolic Computation, Machine Learning, and Computer Algebra, with specific expertise in Quantifier Elimination and variable ordering optimization. Key contributions include dataset augmentation techniques that reduced CAD construction time by 38%, the state-of-the-art gmods heuristic derived from complexity analysis, and the first application of Explainable AI in symbolic computation to extract human-interpretable heuristics from machine learning models. As part of RISC, he addresses computational challenges in algebraic geometry and quantifier elimination, demonstrating how machine learning can surpass human-designed heuristics in symbolic computation efficiency while maintaining mathematical certainty.

Felix Holzmeisterمشاهده پروفایل

استاد

• Experimental Economics
• Behavioral Finance
• Philosophy of Science
• +۳ مورد دیگر

Felix Holzmeister is a Professor in the Department of Economics at the University of Innsbruck, affiliated with the 'Innsbruck Decision Sciences' research center. His work focuses on experimental and behavioral economics, finance, and the philosophy of science. He coordinates interdisciplinary research efforts and collaborates with a team including Markus Walzl, Rudolf Kerschbamer, and others. Research Interests: Holzmeister investigates researcher variability in social science experiments, replicability challenges, and methodological rigor. His work spans lab-, field-, and online-based experiments, emphasizing crowd-sourced science and multi-analyst approaches. Key contributions include studies on risk perception among financial professionals and global societal trends. Notable Publications: He co-authored influential papers in Nature (2020) on neuroimaging dataset variability and Management Science (2020) analyzing risk perception. His research also addresses replication crises in social sciences and methodological transparency. Awards: None explicitly listed, though his work has garnered significant academic attention. Collaborations focus on interdisciplinary work, workshops, and disseminating findings through open science frameworks. Labs/Teams: Active in the Innsbruck Decision Sciences team, emphasizing collaborative research and innovation in experimental methods.