جست‌وجوی استاد و پژوهشگر

• Computer Science
• Health Informatics
• Software Engineering
• +۷ مورد دیگر

Ao.Univ.Prof. Dipl.-Ing. Dr.techn. Thomas Grechenig is an Associate Professor at the Department of Business Informatics (E194-03), Technische Universität Wien (TU Wien). His work focuses on computer engineering, information systems, and human-centered technology, with a strong emphasis on serious games for healthcare and rehabilitation, mobile systems security, and software engineering methodologies. He leads projects like 'Blurred Boundaries,' an app-based intervention for employee recovery, and collaborates on gamified solutions such as MoodBooster and Rehafox. His research integrates technology with societal challenges, including privacy compliance via blockchain and user-centric design for health systems. Grechenig's educational contributions include teaching 'Advanced Software Engineering' (183.243) and supervising projects like 'Software Engineering Project' (194.149). His publications span conferences like IEEE HealthCom, SeGAH, and journals like Applied Sciences , reflecting expertise in gamified health applications, mobile security, and legacy system migration. Despite prolific output, no formal student names or awards are explicitly listed in the provided texts. He actively engages in industry collaborations, such as analyzing software migration in automotive and aviation sectors, and explores ethical issues in refugee management systems. Grechenig is affiliated with the Institute of Information Systems and Computer Media (INSO) and contributes to platforms like TISS and orcid.org.

Richard Yuمشاهده پروفایل

استاد

• Machine learning and artificial intelligence
• Connected and autonomous vehicles
• Blockchain and distributed ledger technology
• +۲ مورد دیگر

Dr. Richard Yu is a Professor at the School of Information Technology, Carleton University, Canada, with academic roles spanning since 2006. His research bridges machine learning, blockchain, and wireless networks, focusing on emerging technologies like vehicular systems and edge computing. Ph.D. in Electrical Engineering (UBC, Canada) M.A.Sc. in Computer Engineering (Beijing University of Posts & Telecomm.) B.A.Sc. in Electrical Engineering (Dalian University of Technology) His research explores machine learning and blockchain integration in connected vehicles , mobile networks , and IoT , emphasizing security and resource optimization . His work often employs deep reinforcement learning to address challenges in distributed systems. Recent publications focus on blockchain-enabled edge computing , vehicular networks , and IoT optimization , with methodologies centered on reinforcement learning , interference alignment , and secure transmission . 2023: Electronics and Electrical Engineering Leader, Research.com 2022: IEEE ICC Best Paper Award 2021: Fellow, Canadian Academy of Engineering 2020: IEEE GLOBECOM Best Paper Award 2019: IEEE TCGCC Distinguished Service Award 2017: IEEE VTC Best Paper Award 2017: IEEE Fellow 2016: IET Fellow 2011: Ontario Early Researcher Award His grants include the Canada Foundation for Innovation’s Leadership Opportunity Fund Award (2009). Collaborative work with students and colleagues underpins his contributions to wireless systems and blockchain.

René Röpkeمشاهده پروفایل

استادیار

• Learning Technologies
• Learning Analytics
• AI in Education
• +۷ مورد دیگر

René Röpke is an Assistant Professor at TU Wien since August 2024. Previously, he conducted his PhD and postdoctoral research within the Learning Technologies Research Group at RWTH Aachen University, focusing on personalized game-based learning for cybersecurity education. His academic journey includes a Bachelor's and Master's from Technical University of Darmstadt and a study semester at Simon Fraser University in Canada. His research interests span Learning Technologies, AI-driven Education, Game-based Learning, and Open Educational Resources (OER). Notable projects include the AIStudyBuddy initiative for AI-powered study planning and the development of serious games for phishing education. He has contributed to tools like WebWriter for interactive content creation and BuddyAnalytics for educational data visualization. Röpke’s recent publications emphasize leveraging AI and process mining for personalized learning solutions, study path optimization, and collaborative learning analytics. His work bridges theoretical educational frameworks with practical digital tool development, aiming to enhance individualized and equitable access to education. He has actively participated in conferences like LAK (Learning Analytics & Knowledge) and DELFI, advocating for open science practices and transparency in educational technology. His contributions highlight a strong focus on human-centered design principles in educational technologies.

• Business Process Analysis
• Anomaly Detection
• Process Monitoring
• +۳ مورد دیگر

Kristof Böhmer is affiliated with the Faculty of Computer Science, contributing to the Research Group Software Architecture. His expertise focuses on business process analysis, anomaly detection, and predictive modeling. He has been actively involved in peer review for journals like EMISA-Forum and conferences such as SIMPDA, and delivered talks on cybersecurity topics at events like IKT-Sicherheitskonferenz 2017. Research Interests: Business Process Optimization Machine Learning for Anomaly Detection Predictive Analytics in Transaction Monitoring Cryptocurrency Market Dynamics Notable Contributions: Developed AIS metric linking social media activity to cryptocurrency pricing Created BAnDIT framework for transaction-based anomaly detection Advanced LoGo methodology combining local/global techniques for process monitoring Recognition: 2018 Best Paper Award at CAiSE Conference for predictive business process monitoring work Professional Activities: Served as journal editor for EMISA-Forum Peer reviewer for multiple international conferences

Arndt von Haeselerمشاهده پروفایل

استاد

• Phylogenetic inference
• Phylogenomics
• Neural Networks
• +۴ مورد دیگر

Arndt von Haeseler is a Full Professor for Bioinformatics at the Center for Molecular Biology and Department for Computer Sciences at the University of Vienna, as well as at the Department for Medical Biochemistry at the Medical University of Vienna. He serves as the Scientific Director of the Center for Integrative Bioinformatics Vienna (CIBIV) and was previously Dean of the Center of Molecular Biology at the University of Vienna and Head of the Center for Medical Biochemistry at the Medical University of Vienna from 2017-2020. His research focuses on phylogenetic inference, phylogenomics, neural networks, sequence evolution, and complex patterns of evolution. With expertise spanning mathematics, biology, and computer science, he has made significant contributions to computational biology through the development of algorithms and software tools for phylogenetic analysis. His work bridges theoretical approaches with biological applications, particularly in evolutionary biology and genomics. Dr. von Haeseler's recent publications demonstrate a strong trend toward integrating machine learning approaches with traditional phylogenetic methods, while expanding into single-cell RNA sequencing analysis and organoid modeling. His research spans computational methodology development, evolutionary analysis, and biomedical applications, with a consistent focus on improving analytical frameworks for biological sequence data. Visiting Professor at Division of theoretical Genetics, National Institute of Genetics, Mishima, Japan (since 2012) WWTF Science Chair Award, Vienna, Austria (2005) Honorary Professor for Theoretical Biology, University of Leipzig, Germany (since 1999) PhD scholarship, Studienstiftung des Deutschen Volkes, Germany (1985-1988) He mentors numerous PhD students and researchers, including Heiko A. Schmidt, Alina Leuchtenberger, and Cassius Manuel. His laboratory develops computational methods that have found widespread application in evolutionary biology and genomics research. The Center for Integrative Bioinformatics Vienna (CIBIV), which he directs, serves as a hub for interdisciplinary research bridging computational approaches with biological questions.

• Emerging Technologies
• Gamification
• Serious Games
• +۵ مورد دیگر

Dr. Alexander Pfeiffer holds dual roles as Head of the Emerging Technologies Experiences Lab and Research Associate at the Center for Applied Game Studies, University for Continuing Education Krems. His work focuses on emerging technologies like blockchain, AI, and gamification in education, cybersecurity, and sustainability. Active in both academic research and applied projects, he leads initiatives such as the ZKPG+ project exploring zero-knowledge proofs in corporate sustainability and the ESPORTS EU-funded study on competitive gaming's societal impact. His research bridges disciplines including digital identity management, cybercrime prevention, and innovative educational paradigms. Key projects include: ZKPG+ (2025–2026): Gamifying sustainable corporate goals via zero-knowledge proofs ESPORTS (2025): Analyzing esports' cultural and economic dimensions FROG (2024–2025): Investigating gaming's future societal roles Publications highlight transformative technologies like AI-driven assessments, blockchain in credentialing systems, and climate-conscious e-commerce solutions. As a principle investigator, he drives grant-funded projects totaling over €5M across EU, FFG, and federal grants. His lab develops practical tools such as the Green e-Commerce size-sensing technology and blockchain-based gamification platforms for education. Current research emphasizes: Ethical AI integration in learning environments Metaverse's educational and sociological implications Cybersecurity challenges in digital gaming ecosystems Labs/Teams: Leads the Emerging Technologies Experiences Lab and collaborates with industry partners on applied tech solutions. Serves as academic advisor to interdisciplinary teams developing gamified assessment tools and digital identity frameworks.

• Software Engineering
• Machine Learning
• Static Code Analysis
• +۳ مورد دیگر

Markus Böck is a PreDoc Researcher at the Software Engineering department of Technische Universität Wien (TU Wien), Austria. His academic work focuses on the intersection of software engineering and machine learning , particularly in performance prediction and probabilistic program analysis . He contributes to automated code analysis and intelligent software systems research. Role: PreDoc Researcher Department: Software Engineering, TU Wien Contact: markus.h.boeck@tuwien.ac.at His research explores: Language-agnostic static analysis of probabilistic programs Context-dependent performance prediction from source code Interactive machine learning systems for software engineering Distributional reinforcement learning applications Code-based performance modeling Program analysis for probabilistic systems Key publication trends include: Advancing probabilistic program analysis (2024-2025) Performance prediction techniques (2022-2023) Reinforcement learning innovations (2020-2022) Application of machine learning to software engineering challenges Game theory algorithm optimization (2025)

• Blockchain
• Smart Contracts
• Ethereum
• +۷ مورد دیگر

Monika di Angelo is an Assistant Professor at Vienna University of Technology's Faculty of Informatics, Department of Automation and Control Systems. Working at 50% capacity, she focuses on Information Systems Engineering and Visual Computing and Human-Centered Technology. Her research spans blockchain technology, smart contracts, Ethereum security, vulnerability detection, cultural heritage applications, and educational informatics. Dr. di Angelo's research interests center around blockchain technology and smart contract security, with particular expertise in Ethereum. Her work explores vulnerability detection in smart contracts, compiler analysis, token standards, and wallet implementations. She also maintains research interests in cultural heritage applications through digital visualization and simulation, extending from earlier work on architectural heritage and pedestrian behavior modeling. Her educational research focuses on didactics in computer science education, particularly for secondary schools and vocational training. Her publication record shows a clear evolution from early work in educational technology and architectural visualization toward blockchain and smart contract research starting around 2018. Recent publications demonstrate deep expertise in Ethereum security analysis, vulnerability detection frameworks, and comparative analysis of smart contract platforms. Her work combines theoretical analysis with practical tool development for blockchain security. Mobilitätsstipendium der TU Wien für hervorragende Dissertation Lions-Förderpreis (1989) Dr. di Angelo has supervised over 50 diploma and master's theses since 2008, with recent supervision focusing primarily on blockchain security, smart contract analysis, and Ethereum vulnerability detection. Her students' work reflects her research trajectory, moving from educational technology topics toward blockchain security in recent years. She has secured research funding from the Austrian Research Promotion Agency (FFG) for projects evaluating educational concepts for MINT promotion. Her DIVS project (2010-2020) represented a long-term research commitment to visualization and simulation of pedestrian behavior at train stations and architectural heritage applications. Her research extends across multiple domains including the SmartBugs framework for smart contract analysis, Ethereum security research, and applications of blockchain technology in various domains. She maintains active collaborations with researchers in blockchain security and has contributed to the development of tools and methodologies for smart contract analysis.

Stefan Bifflمشاهده پروفایل

استاد

• Cyber-Physical Production Systems
• Software Engineering
• Industrie 4.0
• +۳ مورد دیگر

Ao.Univ.Prof. Stefan Biffl is a Professor at TU Wien's Forschungsbereich Information und Software Engineering. His work focuses on Cyber-Physical Production Systems (CPPS), Industrie 4.0, and software engineering, with an emphasis on security, quality, and interdisciplinary approaches to production systems. He leads projects like 'Security Improvement of Information Processing in the Production System Lifecycle.' Research interests span Complex Event Processing, data analytics in production, and self-adaptive systems. Recent work explores test-driven validation, risk management, and multi-domain modeling in CPPS. He collaborates on frameworks like MDM-CPPS and QualSec, addressing challenges in automation, security, and sustainability. No scientific awards listed, but extensive contributions to publications and industry-oriented research are evident. He advises on production systems engineering and contributes to open-access publications through TU Wien's platforms.

• Knowledge Graphs
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Sareh Aghaei serves as a Research Fellow at the Institute of Management Sciences within the Faculty of Mechanical Engineering and Industrial Management at Vienna University of Technology (TU Wien), focusing on knowledge-driven solutions for industrial maintenance and healthcare systems. Her academic credentials include: Ph.D. in Computer Science from the University of Innsbruck (2023) M.Sc. in Computer Science from the University of Isfahan Dr. Aghaei's research integrates knowledge graphs with natural language processing and machine learning to develop explainable AI systems. Her work spans industrial maintenance optimization, clinical decision support, and tourism information systems, emphasizing ontology engineering and question-answering frameworks that transform unstructured data into actionable knowledge. Analysis of her 2021-2025 publications reveals a strategic shift toward domain-specific knowledge graph applications, particularly in maintenance management (2022-2025) and health informatics (2023-2024). This evolution demonstrates increasing specialization in medical knowledge representation while maintaining foundational contributions to semantic web technologies established in earlier works like her 2011 Web services architecture research. Her scholarly recognition includes: netidee Grant Call 17: Austria's award for most innovative doctoral theses Dr. Aghaei's doctoral research was funded through the netidee scholarship. Current documentation indicates no active student supervision or major grant leadership beyond her postdoctoral position at TU Wien. Within TU Wien's Institute of Management Sciences, she contributes to research bridging production engineering and artificial intelligence, developing knowledge-based systems for predictive maintenance and industrial process optimization through interdisciplinary collaboration.

Peter Wetzمشاهده پروفایل

پژوهشگر

• Semantic Web
• Data Integration
• Environmental Data Systems
• +۳ مورد دیگر

Peter Wetz is a researcher affiliated with the Institute of Software Technology and Interactive Systems at TU Wien. His work focuses on semantic data processing, environmental data systems, and interactive data exploration. He has contributed to frameworks like YABench for RDF stream processing and StatSpace for statistical data integration. His research integrates Linked Data, real-time environmental monitoring, and user-friendly data visualization tools. Notable projects include Linked Widgets and Open Mashup Platform, aiming to lower barriers for data exploration. He has authored over 20 publications between 2013–2017, emphasizing interdisciplinary approaches to data management and semantic technologies. Key Areas: Semantic Web, Environmental Data, Stream Processing Tools Developed: YABench, StatSpace, Linked Widgets Platform

• Statistics
• Data Science
• Machine Learning
• +۴ مورد دیگر

Ursula Laa is an Assistant Professor at the Institute of Statistics , University of Natural Resources and Life Sciences, Vienna (BOKU) since 2020. Previously, she was a Postdoctoral Researcher at the Department of Econometrics & Business Statistics and School of Physics & Astronomy , Monash University (2017–2020), and earned her doctorate in particle physics at the University of Grenoble-Alpes , France (2014–2017). Her academic journey began with physics studies at the University of Vienna (2007–2014). Research Interests: She specializes in statistics, with a focus on data visualization, machine learning, computational statistics, and environmental statistics. Her work bridges high-dimensional data analysis with applications in particle physics and environmental studies, particularly in climate change and hydrology. Scientific Contributions: Ursula has actively contributed to projects involving climate change impacts on hydrological systems interactive visualization tools (lionfish, cubble, tourr) statistical modeling for environmental and particle physics data Her recent publications emphasize tour algorithms, projection pursuit, and spatiotemporal indexing, reflecting a blend of data science and domain-specific applications. Awards & Recognition: She has been a keynote speaker at DAGStat 2025 active participant in international conferences (EGU, useR!, Joint Statistical Meetings)

• Open Data
• Data Quality
• Knowledge Graphs
• +۳ مورد دیگر

Dr. Sebastian Neumaier is a Senior Researcher at the Institute of IT Security Research within the Department of Computer Science and Security at University of Applied Sciences St. Pölten . He focuses on open data ecosystems, knowledge graphs, and semantic web technologies. Research Interests : Open Data Quality and Governance Knowledge Graph Construction Data Security and Usage Control Semantic Web Standards Smart City Data Infrastructure Publication Trends (2015–2025) span open data quality assessment, knowledge graph applications, cybersecurity in data spaces, and semantic data labeling. Key subfields include license compliance, spatio-temporal data systems, and decentralized dataset exchange architectures. Education : PhD (2019) – Semantic Enrichment of Open Data Master's Thesis – Data Intelligence BSc – Computer Science Labs & Projects : Core contributor to ADEQUATe platform for open data quality Co-developer of DALICC as a service for license clearance Active in data space policy frameworks Participant in EU digital product passport initiatives

Stefan Resmeritaمشاهده پروفایل

دانشیار

• Embedded Systems
• Real-Time Systems
• Software Timing Analysis
• +۴ مورد دیگر

Stefan Resmerita is an Associate Professor and Deputy Head of the Department of Computer Science at the University of Salzburg, Faculty of Digital and Analytical Sciences. His office is located at Jakob-Haringer-Str. 2, Room 2.32, 5020 Salzburg, Austria, with contact number +43 662 8044-6406. His research focuses on embedded and real-time systems, particularly in the areas of software timing analysis, logical execution time paradigms, and model-based design for automotive applications. His work addresses challenges in migrating legacy embedded software to modern architectures while maintaining timing predictability and verification. He has extensively researched the Timing Definition Language (TDL) and developed the Validator Tool Suite for bridging the gap between software-in-the-loop and hardware-in-the-loop simulation environments. His publication record shows consistent contributions to real-time systems from 2022 back to 1997, with recent work focusing on fine-grained timing in Simulink models, data consistency in automotive multi-core applications, and efficient realization of logical execution times in legacy systems. His research demonstrates a clear trajectory from foundational work on hybrid systems and air traffic management toward contemporary challenges in automotive and embedded software systems. As Deputy Head of Department, he plays a significant administrative role within the Computer Science department while maintaining an active research profile in embedded systems engineering.

Monika Lanzenbergerمشاهده پروفایل

استادیار

• Semantic Web
• Ontology Alignment
• Information Visualization
• +۴ مورد دیگر

Monika Lanzenberger is an Assistant Professor at the Institute of Software Technology and Interactive Systems, Faculty of Informatics, Vienna University of Technology. Her research focuses on the intersection of Semantic Web technologies, ontology alignment, and information visualization. She has established herself as a notable researcher in visual ontology alignment through her development of the AlViz tool and related publications. Dr. Lanzenberger received her PhD from the Vienna University of Technology, Faculty of Informatics in 2003 and her MSc in Computer Science from the same institution in 2001. She completed a Post-Doc Fellowship (ERCIM) with the NTNU, Department of Computer and Information Science, Trondheim, Norway (February - October 2005) and with the Centre for IT Innovation (CITI) at the CRP Henri Tudor, Luxembourg (November 2005 - July 2006). Her primary research interests center around Semantic Web and Ontology-based Data, with specific focus on ontology alignment and visualization techniques. She has made significant contributions to the field through her work on visual ontology alignment tools, particularly the AlViz system. Her research also extends to Human Computer Interaction, Information Visualization techniques, feminist perspectives on computer science, and online learning and didactics. She has published extensively in top conferences and journals in these areas, with a particular emphasis on making ontology alignment more accessible through visualization. Dr. Lanzenberger has received recognition for her work, including an Outstanding Paper Award in 2002 for her research on the evaluation of navigation in hypertext learning systems. She is an active member of the scientific community, serving as a reviewer for international conferences and co-organizer of workshops in her field. As an educator, Dr. Lanzenberger has taught numerous courses including Information Visualization, Women in Science and Technology, Fundamentals of Methodical Working, and Semi-Automatic Information and Knowledge Systems. She has supervised multiple student projects, Bachelor's theses, and Master's theses, particularly in areas related to information visualization and semantic technologies. She is a member of several professional organizations including IEEE, ÖGAI, OCG, and GI, demonstrating her active engagement with the broader computer science community.