جست‌وجوی استاد و پژوهشگر

Bart De Moorمشاهده پروفایل

استاد

• Numerical Linear Algebra
• Optimization
• Algebraic Geometry
• +۱۱ مورد دیگر

Bart De Moor is a Full Professor at the Department of Electrical Engineering, KU Leuven, Belgium, and a guest professor at the University of Siena. He leads the STADIUS research group and has supervised 85 PhD students. His roles include chairman of Health House (2016–present), member of the Board of VIB (Biotech Institute), and former Vice-Rector for International Policy (2009–2013). Education: Master Degree in Electrical Engineering (1983), KU Leuven PhD in Engineering (1988), KU Leuven Research Interests: His work spans numerical linear algebra, optimization, algebraic geometry, systems and control theory, data-driven AI, machine learning, and applications in process industry and biomedical big data. He has contributed to subspace identification, tensor decomposition, bioinformatics, and quantum computing. Publications Trends: His publications highlight subspace identification methods, tensor decomposition, bioinformatics, and biomedical data analysis. These reflect interdisciplinary advancements in control theory, quantum physics, and mathematical engineering, with applications in industrial and healthcare domains. Scientific Awards and Honors: Leslie Fox Prize (1989) Laureate of the Belgian Royal Academy of Sciences (1992) Bi-annual Siemens Award (1994) Fellow of IEEE (since 2004) Member of the Royal Academy of Belgium for Science and Arts (since 2000) Fellow of IFAC (since 2022) Commander in the Order of King Leopold I (2020) Fellow of SIAM (since 2017) FWO Excellence Award (2010) Advising and Grants: He has led a research group of 20 PhD students and postdocs, co-founded 8 spinoff companies, and secured the ERC Advanced Grant ‘Back to the roots’ (2020–2025). He also co-holds the KU Leuven Chair on healthcare systems (2018–present). Labs and Organizations: Active in the STADIUS research group (KU Leuven), he has served on boards of the Flemish Interuniversity Institute for Biotechnology (VIB), the Alamire Foundation, and the Health Tech Experience Center Health House. His spinoffs include Trendminer, Cartagenia, and Ugentec.

• Database systems
• Large scale analytics
• Distributed systems

Beng Chin Ooi is a Lee Kong Chian Centennial Professor at the National University of Singapore (NUS), School of Computing. He has been with NUS since 1991, progressing through the ranks from Lecturer to his current distinguished position. He previously served as Dean of the School of Computing from 2007 to 2013 and as Director of the Smart Systems Institute from 2011 to 2021. His educational background includes: 1985: B.Sc. (1st Class Honors) from Monash University, Melbourne, Australia 1989: Ph.D. in Computer Science from Monash University, Melbourne, Australia Beng Chin Ooi's research focuses on database systems, large scale analytics, and distributed systems. His work has been instrumental in advancing the field of data management technology, particularly in the context of "big data" in large-scale parallel and distributed systems. He has made significant contributions to spatio-temporal and distributed data management, as well as pioneering research in distributed database management and peer-to-peer based enterprise quality management. His recent publications demonstrate a strong focus on blockchain technology, machine learning systems, and healthcare informatics. There's a clear progression from foundational database research to applications in emerging technologies like blockchain and AI. His work bridges theoretical advances with practical system implementations, as evidenced by multiple open-source projects associated with his publications. His notable awards include: 2021: NUS Research Recognition Award 2020: ACM SIGMOD E.F. Codd Innovations Award 2020: ACM SIGMOD Research Highlight Award 2019: VLDB Best Paper Award 2016: Fellow of Singapore National Academy of Science 2016: China Computer Federation Overseas Outstanding Contributions Award 2014: VLDB Best Paper Award 2014: IEEE TCDE CSEE Impact Award 2013: Singapore National Day's Public Administration Medal (Silver) 2013: NUS Outstanding Researcher Award 2012: IEEE Computer Society Kanai Award 2011: ACM Fellow 2011: Singapore President's Science Award 2009: IEEE Fellow 2009: ACM SIGMOD Contributions Award Throughout his career, Professor Ooi has demonstrated exceptional leadership in the database community, promoting high standards of database research at both international and regional levels. His BLOCKBENCH framework became the world's first benchmarking tool for private blockchains, and his work on data provenance on blockchain systems earned both the VLDB Best Paper Award and the ACM Research Highlight Award. He has led several major research initiatives, including the Smart Systems Institute at NUS. Professor Ooi has established multiple open-source projects including FabricSharp for blockchain data provenance and Cool for cohort online analytical processing. His research group has consistently produced high-impact work that bridges theoretical advances with practical system implementations.

Marko Tkalčičمشاهده پروفایل

استاد

• Recommender Systems
• Computational Psychology
• User Modeling
• +۷ مورد دیگر

Marko Tkalčič is a Full Professor at the Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT) at the University of Primorska in Koper, Slovenia. He is affiliated with the Department of Information Sciences and Technologies and leads research in psychologically-informed recommender systems through the HICUP lab. His academic journey includes prior roles as Associate Professor and Assistant Professor at the Free University of Bozen-Bolzano, and postdoctoral work at Johannes Kepler University and the University of Ljubljana. Research interests include computational psychology, user modeling, personality and emotion modeling, affective computing, and bias mitigation in AI. His work integrates machine learning, data mining, and user studies to enhance personalization systems by incorporating cognitive and emotional models. He focuses on music and film domains, with applications in social media, automotive interfaces, and multimedia. The recent publications demonstrate a strong trend toward human-centric AI , exploring eudaimonic and hedonic user experiences, cognitive load in driver assistance, music relistening behavior, privacy in group recommendations, and emotion-based video and music prediction. His research increasingly blends cognitive science theories (e.g., ACT-R) with practical recommender system design. University of Primorska Golden Plaque Award (2024) Stanford List of Top Scientists Cited Worldwide Best Reviewer Award at ISMIR 2020 Italian National Habilitation for Full Professor (2020) Italian National Habilitation for Associate Professor (2017) He actively supervises PhD students, including Elham Motamedi, and has secured teaching and research roles within his team. He is a member of the editorial board for UMUAI and Frontiers in Psychology, and has co-edited books and special issues on group recommender systems and human-centered AI. He leads the HICUP lab, fostering interdisciplinary research at the intersection of psychology and computer science.

• Software Architecture
• Microservices
• Cloud Applications
• +۳ مورد دیگر

Evangelos Ntentos is a researcher affiliated with the Faculty of Computer Science and the Software Architecture Research Group . He holds a Dr.techn. (PhD in Engineering) and degrees in BSc and MSc. His research focuses on software architecture, microservice systems, cloud applications, security practices in infrastructure, and reinforcement learning architectures. He actively contributes to conferences and peer-reviewed journals, with recent publications addressing MLOps quality assessment, security in infrastructure-as-code, and decision-making in reinforcement learning systems. He received the Best Paper Award in 2019 for work on data management and microservice architecture. Ntentos has presented at international conferences, including talks on cyber-physical system architectures and coupling-related architecture smells in 2023–2024. His research emphasizes practical applications of architectural design decisions, continuous delivery, and security best practices in modern software systems.

• Serious Games
• Game Design
• Virtual Reality
• +۳ مورد دیگر

Helmut Hlavacs is a Professor at the Faculty of Computer Science, leading the Research Group on Education, Didactics, and Entertainment Computing. His expertise spans serious games, game design, virtual reality, and health informatics. He has contributed to over 218 publications since 2005, focusing on topics like hedonic experiences in gaming, VR applications in therapy, and AI-driven behavior trees. His work intersects technology, education, and healthcare, with notable projects such as Conquer Catharsis (VR anxiety treatment) and PhyLab (VR physics experiments). Hlavacs has secured research funding for initiatives like Programmieren lernen durch Computerspielentwicklung and Dig-Equality FF , emphasizing digital equity and education. In 2019, he won the Best Poster Award at IFIP for his work on health data from serious games. Research Interests: Serious Games for health and education Virtual Reality applications in therapy and learning Game design methodologies and AI-driven NPC behavior Psychological impacts of gaming and digital consumption Procedural content generation for games Key Projects: Programmieren lernen durch Computerspielentwicklung (2008): Game-based learning for programming skills Dig-Equality FF (2020-2021): Digital competence promotion for equity TP1 PRECIOUS (2013-2016): VR conferencing and stress management Grants and Advising: Hlavacs has advised on projects involving AI in military command systems, VR therapy for anxiety disorders, and participatory design of social media literacy tools. He collaborates internationally on topics like gamification for behavior change and multicultural health interventions. Labs/Teams: His research group focuses on Serious Storytelling and Entertainment Computing , developing tools like the Prototypical game framework and InvisibleSound for blind musicians. Current work includes FiGHT (a web-based tool for eating disorder communication) and OutSmart! (a serious game for social media literacy).

• Cybersecurity
• Game Theory
• Quantum Cryptography
• +۵ مورد دیگر

Stefan Rass is a Professor at the Institute of Networks and Security within the Faculty of Engineering & Natural Sciences at Johannes Kepler University Linz (JKU), where he leads the LIT Secure and Correct Systems Lab. As Principal Investigator for FFG-funded projects including reSilienz (digital supply chain resilience, 2023–2025) and ITPUK (AI signature verification, 2022–2024), he bridges theoretical game theory with practical cybersecurity solutions for critical infrastructures and robotics systems. His research spans game-theoretic security models (patrolling games, defense-in-depth strategies), quantum cryptography (QKD network architectures), and cyber deception frameworks like Honeyquest for measuring honeypot effectiveness. Recent work addresses robotics security benchmarking (RobotPerf), cryptographic instruction chaining for control flow protection, and risk assessment methodologies for interdependent infrastructures. His mathematical decision-making approach integrates bounded rationality and stochastic modeling to solve real-world security challenges. Professor Rass actively shapes the field through program committee roles (ARES 2023), peer reviews, and invited talks on security transparency. His current projects focus on cost-benefit-aware monitoring for cyber-physical systems and quantum key distribution standardization, reflecting Austria’s strategic priorities in digital resilience. The LIT Secure and Correct Systems Lab under his direction develops foundational theories while deploying tools for industrial applications, particularly in critical infrastructure protection and secure robotics workflows.

Thomas Gärtnerمشاهده پروفایل

استاد

• Machine Learning
• Graph Neural Networks
• Geometric Deep Learning
• +۳ مورد دیگر

Thomas Gärtner is a Professor at the Institute of Logic and Computation within the Faculty of Informatics at Vienna University of Technology, leading the Machine Learning research group (E194-06). His work bridges theoretical machine learning with practical applications in chemistry, biology, and network analysis. His primary research focuses on graph neural networks (GNNs) and geometric deep learning, with significant contributions to GNN expressivity, graph transformations, and kernel methods for structured data. He explores fundamental questions about the limitations of message-passing architectures while developing practical enhancements like path-based extensions and expectation-complete representations. His chemical informatics work applies these techniques to binding affinity prediction, reaction classification, and solvent selection, demonstrating real-world impact in computational chemistry. Analysis of his 15 most recent publications (2023-2025) reveals three dominant research thrusts: theoretical GNN advancements (35% of articles), chemical informatics applications (40%), and novel learning frameworks (25%). The theoretical work increasingly addresses expressivity limitations through graph transformations and path-based approaches, while chemical applications show growing sophistication in molecular representation. Recent publications also indicate expanding interest in foundation models for graphs and robustness verification. He actively supervises master's students including Fabian Traxler (binding affinity prediction), Maximilian Plattner (SGD optimization), Fabian Jogl (graph transformations), and Thomas Schmied (reinforcement learning). His research is conducted through the Network Lab at TU Wien, where he serves as Principal Investigator for the Structured Data Learning with Generalized Similarities project.

• Research Data Management
• Semantic Web Technologies
• Machine Learning
• +۳ مورد دیگر

Tomasz Miksa is a researcher affiliated with TU Wien's Department of Research Data Management, focusing on machine-actionable data management plans (maDMPs), semantic web technologies, and data reproducibility. He collaborates extensively on projects involving automated assessment of data management workflows, FAIR data implementation, and privacy-preserving analysis platforms. Primary affiliation: TU Wien Department: Research Data Management Key projects: WellFort, FAIR Data Austria, openEO API His research integrates semantic technologies with data governance to enhance reproducibility in scientific workflows, particularly in domains like environmental monitoring and legal informatics. Recent publications emphasize ontological frameworks (DCSO), API harmonization, and auditable machine learning systems. Notable collaborative works include: Reproducibility standards for soil moisture data Knowledge graph applications in cyber-physical energy systems Dynamic data citation mechanisms He supervises students in theses related to maDMP integration, data citation frameworks, and institutional research data planning architectures.

• Artificial Intelligence
• Machine Learning
• Cybersecurity
• +۳ مورد دیگر

Marlies Temper is a Professor at St. Pölten University of Applied Sciences, serving as Academic Director for the Data Intelligence (MA) and Data Science and Artificial Intelligence (BA) programs. She is Deputy Head of the Department of Computer Science and Security and a member of the UAS Board from 2023 to 2026. Her roles include leading educational initiatives, conducting research, and managing continuing education programs. Academic Director, Data Intelligence (MA) Academic Director, Data Science and Artificial Intelligence (BA) Deputy Head, Department of Computer Science and Security Continuing Education Officer Marlies Temper's research focuses on Artificial Intelligence , Cybersecurity , and Big Data Analytics . She explores the ethical implications of AI, develops gamified models for security training, and investigates continuous biometric authentication methods. Her work bridges the gap between theoretical advancements and practical applications in AI-driven security solutions. Her recent publications highlight trends in AI Security (e.g., risk frameworks), Biometric Authentication (e.g., touch dynamics), and Cybersecurity Education (e.g., gamified simulations). She emphasizes the responsible use of AI and Big Data while addressing technical and ethical challenges.

Franz Wotawaمشاهده پروفایل

استاد

• Model-Based Reasoning
• Qualitative Reasoning
• Theorem Proving
• +۶ مورد دیگر

Franz Wotawa is a Professor of Software Engineering at Graz University of Technology. He holds a M.Sc. (1994) and PhD (1996) from Vienna University of Technology. He has served as head of the Institute for Software Technology from 2003–2009 and since 2020. His research focuses on model-based reasoning, software testing, autonomous systems, and diagnosis, with over 390 peer-reviewed publications. He founded Softnet Austria (2006) to bridge research and industry. He leads the Christian Doppler Laboratory for Quality Assurance Methodologies for Autonomous Cyber-Physical Systems since 2017 and has supervised 90+ master and 36+ PhD students. His awards include the 2016 Lifetime Achievement Award from the International Diagnosis Community. He is a member of Academia Europaea, IEEE, and AAAI. **Education**: M.Sc. in Computer Science, Vienna University of Technology, 1994 PhD, Vienna University of Technology, 1996 **Research Interests**: Model-based reasoning, qualitative reasoning, theorem proving, mobile robotics, verification/validation, software testing/debugging, AI, and autonomous systems. **Notable Projects**: A-IQ Ready (2022–2026): Quantum sensing for autonomous systems. ALFA (2024–2027): AI for smart diagnosis in building automation. Bilateral AI (2024–2029): Combining symbolic and sub-symbolic AI. VARCOS (2025–2028): Vehicle-road cooperative systems for autonomous driving. **Awards & Memberships**: Lifetime Achievement Award (2016, International Diagnosis Community) Senior Member, AAAI Member of Academia Europaea, IEEE, ACM, and Austrian Computer Society **Labs/Teams**: Christian Doppler Laboratory for Quality Assurance Methodologies (since 2017). Active in Cluster of Excellence “Bilateral AI” at TU Graz.

• Software Engineering
• Probabilistic Programming
• Security and Penetration Testing
• +۵ مورد دیگر

Jürgen Cito is an Associate Professor in the Department of Software Engineering at the Faculty of Informatics, TU Wien, where he leads research in probabilistic programming, security, and configuration management. His work is supported by major grants from the Austrian Science Fund (FWF), European Commission, and Meta Platforms, Inc., with active projects spanning 2022-2027. His research focuses on the intersection of software engineering and machine learning, particularly in static analysis of probabilistic programs, AI-driven penetration testing, and infrastructure security. Key contributions include identifying secret exposure in configuration files, grammar inference for ad hoc parsers, and performance prediction from source code, often combining empirical studies with tool development. Analysis of his 15 most recent publications (2020-2024) reveals three dominant trends: (1) Security vulnerabilities in configuration management systems, especially secret leakage in dotfiles; (2) Application of large language models to offensive security testing; and (3) Machine learning techniques for performance prediction and AutoML optimization in software contexts. Cito has supervised 22 Master's students on cutting-edge topics including AI security, infrastructure as code, and program analysis. His current research portfolio includes: Types4Strings (FWF, 2024-2027): Type systems for string processing Cloud Open Source Research Mobility Network (EU, 2023-2026): Open-source cloud infrastructure Software Assistants for Probabilistic Programming (Meta, 2022-2026): AI tools for probabilistic code He is embedded in TU Wien's Institute of Software Technology and Interactive Systems (E194), collaborating on cross-institutional projects focused on software security and developer tooling, with particular emphasis on empirical validation of security practices and configuration management systems.

• 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.

Stefan Häusslerمشاهده پروفایل

پژوهشگر

• Operations Management
• Production Planning
• Supply Chain Management
• +۴ مورد دیگر

Stefan Häussler is a researcher affiliated with the Department of Information Systems, Production and Logistics Management at the University of Innsbruck , and coordinates the Innsbruck Decision Sciences research center. His work focuses on Operations Management , Production Planning , and Supply Chain Management , employing methods like discrete event simulation , optimization techniques , econmic experiments , and machine learning . He collaborates with researchers such as Hubert Missbauer, Gregor Blossey, Julian Fodor, and Florian Merkle. His research emphasizes practical applications in supply chain dynamics, including behavioral analyses and predictive lead time modeling. Häussler seeks to address societal challenges like food security and social inequality through his work. He values interdisciplinary collaboration and enjoys engaging in discussions and projects through the IDS network. Key themes in his publications include optimizing order release mechanisms, analyzing human decision-making in supply chains, and integrating machine learning for production planning. While no specific awards are listed, his active research output reflects ongoing contributions to the field.

Theresa Rienmüllerمشاهده پروفایل

استادیار

• Biomechanics
• Biomedical Engineering
• Bioelectronics
• +۳ مورد دیگر

Theresa Rienmüller serves as Assistant Professor at the Institute of Biomechanics, Graz University of Technology (TU Graz), Austria since March 2025, following prior appointments at TU Graz's Institute of Health Care Engineering (2019-2025) and research roles at UMIT and TU Graz dating back to 2008. Her academic foundation includes a Ph.D. in Technical Sciences from UMIT (2013) and an M.Sc. in Telematics from TU Graz (2008). Her research integrates computational modeling with experimental biology to address complex physiological challenges, focusing on bioelectronic neural stimulation , cardiovascular dynamics , and tissue engineering . She pioneers the application of organic semiconductors for light-controlled neuromodulation and cardiac excitation, developing innovative solutions for traumatic brain injury recovery and regenerative medicine. Her methodology uniquely combines in vitro cell experiments with in silico system theory models to simulate physiological processes. Recent publications (2021-2025) reveal a dominant trend toward organic bioelectronics for neural/cardiac applications, with significant contributions in microfluidic diagnostics , cancer bioelectricity modeling , and AI-driven medical imaging . Her work consistently bridges fundamental biophysics with translational medical device development, emphasizing precision control of biological systems through engineered interfaces. As Co-PI of the Austrian Science Fund (FWF) project “LOGOS-TBI” (2019-2024), she advanced light-controlled implants for brain injury regeneration, and currently leads the “Microfluidic Platform” project (2024-2026) for point-of-care diagnostics. These grants reflect her leadership in securing competitive funding for interdisciplinary biomedical engineering research, with ongoing collaborations spanning Harvard University, European medical device centers, and clinical partners. Dr. Rienmüller maintains active research partnerships through TU Graz's Institute of Biomechanics, leveraging shared facilities for organic semiconductor fabrication , electrophysiology , and computational modeling . Her international network includes the Beth Israel Deaconess Medical Center (Harvard) and LAAS-CNRS in France, facilitating cross-border innovation in bioelectronic medicine and diagnostic technologies.

• Cybersecurity
• IT Security
• Artificial Intelligence
• +۷ مورد دیگر

Sebastian Eresheim serves as a Researcher at the Institute of IT Security Research within the Department of Computer Science and Security at St. Pölten University of Applied Sciences. His work focuses on developing innovative approaches to cybersecurity education and defense mechanisms through gamification, machine learning, and reinforcement learning techniques. He contributes to academic programs including Data Intelligence (MA) and Data Science and Artificial Intelligence (BA). Eresheim's research interests span across cybersecurity, artificial intelligence, and machine learning applications in security contexts. His work particularly emphasizes practical security solutions through gamification of security concepts, reinforcement learning for malware containment, and threat intelligence systems. He has developed cyber defense games like PenQuest that provide hands-on security training experiences. His research bridges theoretical security concepts with practical implementations, especially in the areas of process classification for anomaly detection and modeling real-world threat scenarios. Analysis of Eresheim's recent publications reveals a strong focus on applying artificial intelligence to cybersecurity challenges. His work demonstrates a progression from theoretical security modeling toward practical implementations, with increasing emphasis on gamification techniques for security education and reinforcement learning environments for cyber defense training. His research spans multiple domains including IT/OT infrastructure security, threat modeling, and security awareness training, showing interdisciplinary connections between computer science, game theory, and security engineering. Eresheim actively participates in various research projects including KliWaSim, the Webinar Series "Secure Home Office," and the Josef Ressel Center for Unified Threat Intelligence on Targeted Attacks (TARGET). He regularly presents at conferences and delivers workshops on AI and security topics, including events like the ACTA TECH DAY 2024 where he presented "Artificial Intelligence 101." His outreach extends to media appearances on ORF NÖ heute discussing practical AI applications.