جست‌وجوی استاد و پژوهشگر

• High-Performance Computing
• Big Data Processing
• Performance Portability
• +۳ مورد دیگر

Enes Bajrovic is a researcher affiliated with the Faculty of Computer Science, focusing on high-performance computing (HPC), big data processing, and performance portability. His work spans task-based parallelism, runtime systems, and optimization frameworks for heterogeneous architectures. He has contributed to major European projects like PEPPHER and AutoTune, which aim to advance HPC software tools and autotuning methodologies. His research emphasizes practical applications of parallel computing in domains such as mobile networks and scientific simulations. Education: Dipl.-Ing. Dr.techn., BSc in Computer Science His research interests include developing frameworks for compute- and data-intensive applications, leveraging technologies like Kubernetes, OpenCL, and Intel Xeon Phi coprocessors. He has authored numerous peer-reviewed publications on topics such as pipeline patterns, autotuning algorithms, and hybrid execution models. His work bridges theoretical advancements in parallel computing with real-world software engineering challenges. Bajrovic has collaborated on projects funded by the European Commission’s FP7 program, contributing to deliverables like runtime systems, tuning frameworks, and benchmarking tools. His research also addresses the integration of big data processing with HPC, particularly in telecommunications and distributed computing environments.

Stefan Finkمشاهده پروفایل

استاد

• Computational Finance
• Genetic Programming
• Time Series Modeling
• +۳ مورد دیگر

Stefan Fink is a Professor at the University of Applied Sciences Steyr, specializing in Controlling, Accounting, and Financial Management. He is a Chief Economist at KPMG Austria GmbH and Director of Financial Risk Management since 2016. His work bridges Computational Finance, Genetic Programming, and Climate Risk Modeling, with a focus on regulatory frameworks like IFRS 9 and sustainability. Doctoral studies in Quantitative Economics (1991–2002) Master’s in Economics (1995–1998) Technical Physics education (1994–1995) His research interests include Genetic Programming and Time Series Modeling , applied to Computational Finance and Econometric Modeling . Recent projects like FinCoM and Credit Default Prediction address financial risk monitoring and climate risk impact on enterprise value. Stefan has delivered invited lectures on topics such as IFRS 9 compliance and volatility modeling , with a publication record spanning from 2000 to 2024. He is also involved in collaborative research with multiple co-authors and institutions.

• Machine Learning
• System Architecture
• MLOps
• +۶ مورد دیگر

Stephen John Warnett is a researcher affiliated with the Faculty of Computer Science, specializing in Software Architecture. His work focuses on architectural design decisions for machine learning systems, particularly MLOps and RLOps frameworks. Research Interests: Primary areas include Machine Learning, System Architecture, and Reinforcement Learning. Key subtopics involve architectural design decisions, quality assessment, understandability, data integration, and deployment practices in cyber-physical systems. Publications Trends: Recent work emphasizes model-driven metrics for MLOps architectures, understandability in machine learning systems, and decision-making support for training strategies in reinforcement learning. Scientific Awards: Best Paper Award (2022)

• Resource-efficient machine learning
• Data-efficient machine learning
• On-device learning
• +۵ مورد دیگر

Olga Saukh is an Associate Professor at TU Graz's Institute of Computer Engineering, leading the Embedded Learning and Sensing Systems (ELSS) group. Her research focuses on resource-efficient AI, on-device learning, and robust sensing systems for IoT and environmental monitoring applications. She holds a Dr.rer.nat. and MSc in Computer Science, with expertise in embedded systems and wireless sensor networks. Her work integrates machine learning with hardware constraints, addressing challenges in energy efficiency, real-time adaptation, and adversarial robustness. Notable projects include PCDCNet for air quality forecasting and SensorFormer for sensor calibration. She has contributed to OpenSense Zurich's air pollution monitoring and automated pollen sensing systems. Her research spans over 50 publications since 2006, emphasizing practical deployments in structural health monitoring, smart agriculture, and urban environmental sensing. She leads interdisciplinary projects combining AI, embedded hardware, and data-driven decision-making.

Xiaoming Fuمشاهده پروفایل

استاد

• Mobile Computing
• Social Computing
• Cloud Computing
• +۷ مورد دیگر

Xiaoming Fu is a Full Professor of Computer Science at the University of Göttingen, Germany, and Founding Director of the Sino-German Institute of Social Computing. He earned a Ph.D. from Tsinghua University (2000) and has held academic positions at TU Berlin (2000-2002) and the University of Göttingen since 2002. His research spans mobile computing, social computing, cloud computing, big data analysis, and networked systems, with a focus on (mobile) social networks, Internet of Things, and software-defined networking. Education : Ph.D. (2000) from Tsinghua University, Beijing, China. Key Positions : Founding Director, Sino-German Institute of Social Computing (2015-present); University Professor and Head of Computer Networks Group (2007-present); Assistant Professor (2002-2007); DAAD Visiting Professor at Columbia University (2008-2009); Fulbright Scholar at UCLA (2009). Editorial Leadership : Editor-in-Chief of the Journal of Social Computing and ACM Transactions on Social Computing; served on editorial boards of IEEE Network, IEEE Communications Magazine, and others. Research Leadership : Principal Investigator for EU FP6-ENABLE, FP7-GreenICN, H2020 COSAFE, and MobileCloud projects; coordinator of EU H2020 ICN2020 and CleanSky projects. Leadership in Professional Organizations : Vice Chair of IEEE Communications Society Technical Committee on Computer Communications (2010-2012); Chair of IEEE Communications Society and Internet Society Internet Technical Committee (2011-2013); founding co-chair of IEEE Vehicular Technology Society Germany Chapter. Honors and Awards : IEEE Fellow (2022), ACM Distinguished Member (2021), Member of acatech (2024), Fellow of the Institute of Engineering and Technology (2017), and more.

• Computer Science
• Operating Systems
• Computational Thinking
• +۷ مورد دیگر

Peter Denning is a Distinguished Professor of Computer Science at the Naval Postgraduate School (NPS) in Monterey, CA, serving as Department Chair. He has held prominent roles including Professor and Department Chair at George Mason University, Director of NASA's Research Institute for Advanced Computer Science (RIACS), and faculty positions at Purdue University, Princeton University, and MIT. His research focuses on computational thinking, great principles of computing, operating systems, security, performance modeling, and innovation adoption. Denning has contributed to foundational work in virtual memory, working set theory, and queueing networks. He has authored influential books such as The Innovator's Way and Computational Thinking . His honors include IEEE Fellow (1982), ACM Distinguished Service Award (1989), ACM Karlstrom Educator Award (1996), and the IEEE Computer Society Pioneer Award (2021). He has received eight best paper awards across his career. Denning has led NSF-funded initiatives like the 'Resparking Innovation' project and pioneered interdisciplinary education in computing principles. His work bridges theoretical computing foundations with real-world applications in education and innovation leadership.

Michael Affenzellerمشاهده پروفایل

استاد

• Genetic Programming
• Symbolic Regression
• Evolutionary Algorithms
• +۶ مورد دیگر

Michael Affenzeller is a Professor at the University of Applied Sciences Upper Austria, leading the HEAL AIST Center of Excellence for Smart Production with a focus on Digital Transformation. His research spans Genetic Programming, Symbolic Regression, and Evolutionary Algorithms, with applications in optimization, AI, and manufacturing automation. He has authored over 400 publications and led major projects such as HCAI (Human-Centered AI) and HEAL, emphasizing interdisciplinary collaboration. Research interests include developing advanced algorithms for dynamic optimization, prescriptive analytics, and federated learning in industrial contexts. He has contributed to projects like LOISI (Logistics Optimization in Steel Industries) and SimGenOpt2, addressing challenges in production planning and workforce optimization. Key collaborations involve institutions in Austria and beyond, focusing on smart manufacturing, logistics, and AI integration. His work bridges theoretical advancements with real-world applications, driving innovation in energy systems, crane scheduling, and predictive maintenance. Grants and projects include funding from FWF (doc.funds.connect) and Upper Austrian initiatives, emphasizing doctoral training and industry partnerships. He actively participates in conferences such as EUROCAST and PPSN, contributing to algorithmic advancements and computational theory.

Reinhard Bernsteinerمشاهده پروفایل

استاد مدعو

• Internet of Things
• Augmented Reality
• Knowledge Management
• +۵ مورد دیگر

Reinhard Bernsteiner is an Adjunct Professor at the University of Nebraska at Omaha (Department of Information Systems & Quantitative Analysis) and a long-standing lecturer at Management Center Innsbruck, where he teaches in programs including Industrial Engineering & Management (Master), Management, Communication & IT (Bachelor/Master), and Mechatronics (Bachelor). His academic career spans over two decades, with additional roles such as Lecturer at the Higher Technical Vocational School for Industrial Engineering since 1995. He holds a Dr. from the University for Health and Life Sciences (2004–2008) and a Mag. from Johannes Kepler University (1985–1989). Bernsteiner's research centers on emerging technologies and their societal impacts. Primary interests include: Internet of Things (IoT) : Applications in education and industry Augmented Reality (AR) : Industrial training and educational tools Knowledge Management : Frameworks for open innovation AI & Digital Transformation : Ethical implications and business integration Educational Technology : Enhancing learning through VR, gamification, and data analytics His 15 most recent publications (2024–2025) reveal a strong focus on IoT/AR in vocational education, AI-driven project management, blockchain in healthcare, and digital transformation challenges. Common themes include empirical studies on technology adoption, systematic literature reviews, and interdisciplinary approaches bridging engineering, business, and pedagogy. Awards & Recognition: Best Paper Award at EDULEARN for Motivating Students to Acquire Digital Skills (2021) Bernsteiner has supervised 100+ bachelor, diploma, and master theses, primarily exploring IoT, AR, data science, and business process optimization. Students investigated topics ranging from AI ethics to sustainable supply chains, reflecting his interdisciplinary mentorship. No grant or lab affiliations were documented.

• Medical Informatics
• Healthcare Information Systems
• Database Systems
• +۳ مورد دیگر

Ao.Univ.Prof. Dipl.-Ing. Dr.techn. Ernst Schuster is an Associate Professor in the Department of Databases and Artificial Intelligence at Technische Universität Wien. His research focuses on healthcare information systems, medical informatics, and telemedicine infrastructure. He has supervised numerous theses on topics ranging from cancer documentation systems (e.g., HNOOncoNet) to mobile health applications and medical data security. His work emphasizes interdisciplinary collaboration between informatics and healthcare domains. Key research interests include: Database systems for medical applications Telemedicine and remote patient monitoring Software engineering for healthcare IT Decision support systems in clinical settings Recent publications highlight innovations in: Medical data version control systems Usability engineering for healthcare interfaces Telecommunication security frameworks AI-driven diagnostic tools Supervised over 30 graduate students since 2002, contributing to advancements in medical informatics and health technology. Active in developing web-based medical documentation systems and e-learning platforms for medical education.

• Computer Architecture
• Compilers
• Programming Languages
• +۴ مورد دیگر

Andreas Krall is an Associate Professor in the Department of Software Technology at TU Wien's Faculty of Informatics. He holds roles as Curriculum Coordinator for the Bachelor Informatics and Bachelor Software and Information Engineering programs, and serves as a Substitute Member of the Curriculum Commission for Informatics. His research focuses on compiler design, architecture description languages (e.g., VADL), and formal methods for ensuring correctness in compiler-processor co-design. Key research areas include computer architecture, compiler verification, embedded systems, and the development of tools for processor simulation and optimization. Krall has led projects such as 'Correct Compilers for Correct Processors' (2010–2015) and contributed to the CACAO JVM project. He has published extensively on topics like instruction selection, abstract state machines (CASM), and SSA-based optimizations. Notable awards include the Heinz Zemanek Preis (1987). His work spans over 30 years, with contributions to both academic research and industry-relevant tools like the VADL architecture description framework. Krall has advised numerous students in topics ranging from compiler backends to garbage collection algorithms.

• Visual Analytics
• Human-Computer Interaction (HCI)
• Information Visualization
• +۴ مورد دیگر

Wolfgang Aigner is a Professor at TU Wien's Faculty of Informatics, affiliated with the Institute of Visual Computing and Human-Centered Technology. His work focuses on Visual Analytics, Human-Computer Interaction (HCI), and Information Visualization. He leads projects like KAVA-Time and HypoVis, emphasizing time-oriented data analysis and user-centered design. Education: Holds a Dr.techn. (PhD) and Privatdoz. (Privatdozent) in Computer Science. Research Interests: Includes visualization onboarding methods, temporal data analysis, knowledge-assisted VA, and interactive systems for medical and enterprise data. Notable contributions include TimeBench and Radial Sets frameworks. Awards: Honored with IEEE VAST 2012 Mention, Karl Ritter von Ghega Awards (2010, 2008), and multiple Sparkling Science grants. Courses Taught: Bachelor Thesis, Information Visualization, Project courses in Computer Science, Visual Computing, and Medical Informatics. Projects: Active in EU-funded initiatives like ArtVis, DoRIAH, and VIENA (Visual Enterprise Network Analytics). Supervises PhD students in onboarding methods and VA applications. Labs: Involved in the Visual Computing lab, focusing on HCI and interactive visual systems.

Cynthia Kenia Arcanjo Marcelinoمشاهده پروفایل

پژوهشگر

• Serverless Computing
• Edge-Cloud-Space Continuum
• Internet of Things
• +۳ مورد دیگر

Cynthia Kenia Arcanjo Marcelino is a PhD student and Research Scientist at the Distributed Systems Group (DSG) within the Faculty of Informatics at TU Wien. She holds a Bachelor's and Master's degree in Software Engineering & Internet Computing from TU Wien. Her research focuses on serverless computing, edge-cloud-space continuum architectures, and IoT applications. She has industry experience in large-scale distributed systems and cloud solutions. Education: Bachelor of Science in Software Engineering & Internet Computing, TU Wien Master of Science in Software Engineering & Internet Computing, TU Wien Research Interests: Serverless Computing Edge-Cloud-Space Continuum IoT Edge Intelligence Distributed Systems Her work emphasizes scalable serverless architectures and efficient scheduling strategies for distributed environments. Awards & Grants: 2024 IoT Conference Best Paper Award Netidee Project Grant (2024) Advising & Projects: Supervising master's and bachelor's theses on topics like WebAssembly runtime optimization and stateful serverless functions. Active in projects RapidREC and TEADAL focusing on edge-cloud continuum challenges. Labs & Teams: Core member of TU Wien's Distributed Systems Group, collaborating on edge-cloud infrastructure research and open-source tools like CWASI and HyperDrive.

• Machine Learning
• Enterprise Architecture
• Conceptual Modeling
• +۳ مورد دیگر

Philipp-Lorenz Glaser is a PreDoc Researcher at the Department of Business Informatics, Technische Universität Wien. His research focuses on conceptual modeling, enterprise architecture, machine learning applications, and knowledge graph construction. Role: PreDoc Researcher (E194-03) Contact: philipp-lorenz.glaser@tuwien.ac.at His work explores methods for encoding semantic information in conceptual models to improve machine learning applications, with a focus on FAIR datasets and hybrid modeling approaches. Key themes include: Enterprise architecture modeling practices Graph-based data representation Integration of textual and graphical modeling Development of modeling tools (e.g., Sprotty-based solutions)

• Software Engineering
• Requirements Engineering
• Variability Modeling
• +۴ مورد دیگر

Paul Grünbacher is a Lecturer at the Technische Universität Wien , affiliated with the Department of Information Systems Engineering . His research focuses on Software Engineering , Requirements Engineering , and Variability Modeling , with a particular emphasis on value-based approaches and stakeholder management. Grünbacher’s research interests are centered around improving software quality and traceability through value-based decision-making. He explores Variability Modeling to address software complexity, Traceability for requirement alignment, and Stakeholder Management in global development contexts. His publications highlight advancements in Value-Based Software Engineering , Variability Modeling , and Requirements Traceability . Key trends include cost-benefit analysis, automated traceability tools, and stakeholder-oriented methodologies in software development. Grünbacher has supervised several students, including D. Winkler , C. Pichler , and F. Schnitzhofer , guiding their work in areas like heterogeneous environments and business document modeling. Contact: paul.gruenbacher@tuwien.ac.at

Antonio Vallecilloمشاهده پروفایل

استاد

• Software Quality
• Model-Driven Software Engineering
• Enterprise Modeling
• +۷ مورد دیگر

Antonio Vallecillo is a Full Professor at the University of Málaga, leading the ATENEA research group focused on Software Modeling and Analysis. He has held key academic and administrative roles, including Vice-President of the Spanish Society on Informatics (SCIE), President of SISTEDES (Spanish Society on Software Engineering), and coordinator of the Computer Science and Information Technologies area at the Spanish Research Agency (AEI). His work spans standardization activities in AENOR, ISO, and ITU-T, where he edited three international standards on Open Distributed Processing. Research interests include Model-Driven Engineering, Software Quality, Enterprise Architectures, and Model Transformations. He has over 120 publications in top venues, secured €2M+ in research funding, and pioneered conferences like STAF and ICMT. His contributions to open-source tools for model transformation validation and international standards underscore his impact. Awards include Best Paper distinctions and the 10-Year Most Influential Paper Award. Academic leadership roles include Vice-President of Postgraduate Studies at the University of Málaga and Director of University IT systems. He actively participates in editorial boards (SoSym, JOT) and international conferences as PC Chair and keynote speaker.