جست‌وجوی استاد و پژوهشگر

Yunjie Yangمشاهده پروفایل

دانشیار

• AI-powered sensing and imaging
• Machine learning
• Soft sensors & electronics for robotics
• +۵ مورد دیگر

Dr. Yunjie Yang is an Associate Professor at the University of Edinburgh's School of Engineering, with affiliations at the Edinburgh Futures Institute (EFI), the Edinburgh Generative AI Laboratory (GAIL), and the Edinburgh Centre for Robotics. He previously held the Chancellor's Fellow in Data Driven Innovation (2018-2023) and Bayes Innovation Fellow (2023-2024) positions. His research focuses on AI-powered sensing and imaging, machine learning, and soft sensors & electronics for robotics. Yang received his PhD in Engineering Electronics from the University of Edinburgh, MSc in Control Science & Engineering from Tsinghua University, and BEng in Measurement & Control Engineering from Anhui University. After his PhD, he worked as a Postdoctoral Research Associate in Chemical Species Tomography before securing his lectureship. His research interests center on developing intelligent sensing systems that replicate human perception capabilities for robotics and intelligent systems. He pioneers flexible sensing and imaging technologies across various scales through innovative multi-modal sensors, soft electronics, and their modeling using machine learning approaches. His work aims to enable autonomous physical artificial intelligence by bridging the gap between robotic systems and human-like perception. Analysis of his recent publications reveals a strong focus on soft robotics perception, particularly through electrical impedance tomography (EIT) and transformer-based architectures. His research spans medical imaging applications, digital twin modeling for industrial processes, and machine learning approaches for sensor data interpretation. The trend shows increasing integration of physics-informed deep learning with traditional tomographic techniques to achieve higher accuracy and efficiency. European Research Council (ERC) Starting Grant (2024) IEEE J. Barry Oakes Advancement Award (2024) IEEE I&M Society Graduate Fellowship Award (2015) Multiple Best Paper Awards Senior Member of IEEE Fellow of the International Society for Industrial Process Tomography Fellow of the Higher Education Academy ESI highly cited papers Dr. Yang serves as Associate Editor for IEEE Transactions on Instrumentation and Measurement and holds editorial positions with Scientific Reports and IEEE Sensors Journal. His research has been licensed to overseas research institutes and industry partners and received wide media coverage including BBC, EFE, USA Today, and STV. He has secured significant grant funding including the prestigious ERC Starting Grant. He leads the Edinburgh SMART Lab (Sensing/imaging + Machine Learning + Robotics), which aims to replicate human perception capabilities for robotics and advance flexible sensing technologies through innovative multi-modal sensors and machine learning approaches. The lab focuses on enabling autonomous physical artificial intelligence with applications spanning medical diagnostics, industrial monitoring, and advanced robotics systems.

• Model Engineering
• Web Engineering
• Process Engineering
• +۹ مورد دیگر

Gerti Kappel is a full professor at the Institute of Information Systems Engineering at TU Wien, affiliated with the Business Informatics Group (BIG). Since 2020, she has served as Dean of the Faculty of Informatics at TU Wien, previously holding the role of Dean’s team member responsible for research, diversity, and financial affairs (2016–2019). She previously held a full professorship in computer science (database systems) and led the Department of Information Systems at Johannes Kepler University Linz (1993–2001). Her research focuses on Model Engineering, Web Engineering, and Process Engineering, particularly in cyber-physical production systems. She has co-authored influential works such as UML@Work (2005), UML@Classroom (2015), and Web Engineering (2006). Key projects include leadership roles in Vienna Informatics Living Lab (2018–2019), MPM4CPS (2014–2019), and ARTIST (2012–2015), addressing topics like model versioning, cloud architecture modeling, and inter-organizational systems. Her recent articles explore circular systems engineering, IoT-based simulation environments, and model-driven approaches for time-series analytics and cloud applications. She actively contributes to academic governance, including managing the Office of the Dean (E199-01) and overseeing faculty services. Her work emphasizes bridging theory and practice through collaborative frameworks like ERPEL and TROPIC . Grants: Projects funded by Austrian Research Promotion Agency, European Cooperation in Science and Technology, Vienna Business Agency, and others. Advising: Supervised over 15 graduate theses, including recent works on model-driven techniques for railway planning, debugging frameworks for modeling tools, and cloud-based IDEs. Labs/Teams: Leads research within the Business Informatics Group (BIG) and collaborates with the Vienna Informatics Living Lab for applied systems engineering.

Peter Mohr-Ziakمشاهده پروفایل

پژوهشگر

• Augmented Reality
• Mixed Reality
• Human-Computer Interaction
• +۷ مورد دیگر

Peter Mohr-Ziak is a researcher affiliated with both the Institute of Computer Graphics and Vision at the University of Technology Graz (TU Graz) and VRVis Forschungs GmbH. His primary focus areas include Augmented Reality (AR) and Mixed Reality (MR) systems, specifically in the domains of AR visualization, content generation for AR, and head-mounted display (HMD) technologies. He is actively involved in projects with AVL List GmbH in addition to his academic research. Academic Rank: Researcher at TU Graz Education: Telematics, TU Graz Peter's research interests center on creating interactive AR systems with applications in industrial assembly, remote assistance, and education. His work spans technical aspects of AR visualization and practical implementations for skill training (e.g., guitar tutorials) and complex tasks like maxillofacial surgery. He investigates spatial rendering techniques, adaptive perspective models, and light field applications in mixed reality environments. Recent research trends include: 2024: Expanding into human-robot interaction and AR affordance templates 2023: Developing interactive guitar tutorials and state-aware configuration detection systems 2022: Advancing focus cues in video see-through MR and assembly instruction authoring 2019-2020: Improving HMD interaction with TrackCap and light field remote assistance 2017: Creating adaptive perspective rendering and video tutorial retargeting systems Scientific recognition includes: 2021: ISMAR Best Conference Paper 2017: CHI Best Paper Honorable Mention He contributes to projects at TU Graz's Institute of Computer Graphics and Vision, including collaborations with VRVis Forschungs GmbH and AVL List GmbH, while maintaining personal interests in photography and drone flying.

Thomas Eiterمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Computational Logic
• +۷ مورد دیگر

Thomas Eiter is a Full Professor at the Institute of Logic and Computation, Technical University of Vienna (TU Wien), where he serves as Head of Research Unit. He is a Full Member of the Division of Mathematics and Natural Sciences since 2022 and holds leadership roles within the university. His research focuses on knowledge representation and reasoning, computational logic, algorithms and complexity in AI, declarative problem solving, nonmonotonic logic programming and databases, and reasoning about actions and change. His work bridges theoretical foundations with practical applications in artificial intelligence, particularly in logic programming and knowledge-based systems. He has made significant contributions to Answer Set Programming (ASP), developing frameworks like DLV and HEX programs that enable sophisticated reasoning capabilities. His recent publications demonstrate a strong focus on stream reasoning (LARS framework), knowledge forgetting, modular reasoning systems, and the integration of logic programming with ontologies. His research shows consistent contributions to both theoretical foundations and practical implementations of AI systems over several decades. ACM Fellow (2020) Fellow of the European Association for AI (2006) Distinguished Paper Award of the 17th International Joint Conference on Artificial Intelligence (IJCAI, 2001) Prominent Paper Award of the Artificial Intelligence Journal (2013) Test of Time Award (10 years) of the International Conference on Logic Programming (2013) Eiter has led and participated in numerous research projects, both internationally funded (such as LogiCS@TUWien, Humane AI, AI4EU) and nationally funded (including projects like BILAI, TAIGER, and several FWF-funded initiatives). His research unit has received substantial support from European Commission programs (H2020) and Austrian funding agencies (FWF, FFG, WWTF). He is actively involved in the academic community as a member of the Austrian Academy of Sciences (ÖAW), Academia Europaea, and has served on the Executive Council of AAAI. His research unit maintains strong connections with international collaborators and has developed influential systems like the DLV answer set programming system.

• Pediatrics
• Obesity Management
• Metabolic Disorders
• +۲ مورد دیگر

Daniel Weghuber is Professor and Department Chair at Paracelsus Medical University's Department of Pediatrics. His research focuses on pediatric obesity management, metabolic disorders, and pharmacotherapy. Research areas include: Anti-obesity medications for youth Neonatal laboratory diagnostics Clinical guideline development Metabolic function in inflammatory bowel disease Publications emphasize evidence-based obesity management, novel therapeutic approaches, and optimization of pediatric care protocols. Recent works address medication efficacy in adolescents and minimally invasive diagnostics. He leads projects on mitochondrial function in IBD and EURAS (epilepsy research). Current research examines climate impacts on migration through machine learning models.

• IT Security
• Cybersecurity
• Open-Source Software Analysis
• +۳ مورد دیگر

Tobias Dam serves as an Academic Professional 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 practical cybersecurity challenges with emphasis on open-source software ecosystems, data space security, and web-based threats. Based in the B-Campus-Platz 1 location, he actively contributes to both research and educational initiatives in IT Security. His educational background includes completing HTL St. Pölten's Department of IT/Computer Science program from 2008-2013, followed by a Bachelor's degree in IT Security at St. Pölten University of Applied Sciences from 2013-2016. He gained practical experience in 2015 working on software development, security, and configuration management in the "upribox" project. Since 2016, he has been pursuing a Master's degree in Information Security at the same institution. Dr. Dam's research spans multiple critical areas in modern cybersecurity, with particular expertise in analyzing vulnerabilities in open-source software ecosystems. His work on critical open-source software databases represents significant contributions to understanding the "health status" of important open-source projects. He has also made notable advances in data space security, developing policy patterns for usage control, and conducting extensive analyses of web-based threats including typosquatting, pop-up scams, and cryptojacking. His research uniquely bridges theoretical frameworks with empirical analysis of real-world security issues, often examining how privacy techniques like k-anonymity impact machine learning classifiers and how data deletion affects model integrity. His publication record demonstrates consistent contributions to major cybersecurity conferences and journals, with recent work focusing on dataspace connector implementations, critical open-source software metrics, and vulnerability assessment in open-source packages. His research trajectory shows increasing specialization in the security challenges of modern data ecosystems while maintaining strong connections to practical implementation concerns. Through his video presentations on cloud services versus self-operated programs and secure remote corporate IT access, Dr. Dam actively engages in knowledge transfer to broader technical audiences beyond traditional academic publication channels.

Markus Tatzgernمشاهده پروفایل

استاد

• Augmented Reality
• Virtual Reality
• Mixed Reality
• +۳ مورد دیگر

Dr. Markus Tatzgern serves as Professor for Mixed Reality and Game Development and Head of Research at the Department for Creative Technologies, Salzburg University of Applied Sciences. He leads the Digital Realities Lab, a multi-disciplinary research group focused on human-centered solutions at the intersection of software, design, and creative engineering for technology interaction. His academic foundation includes a Master of Science and Doctorate with highest distinction from Graz University of Technology. He furthered his expertise through post-doctoral research at the Christian Doppler Laboratory for Handheld Augmented Reality, recognized as a world-leading facility in mobile AR. Tatzgern's research spans Augmented Reality, Virtual Reality, Mixed Reality, and Human-Computer Interaction with emphasis on practical applications. His work addresses critical challenges in view management, haptic feedback systems, industrial procedure visualization, medical imaging interfaces, and game development. Key contributions include novel techniques for eye-perspective rendering, breathing-based VR interaction, and latency compensation in medical robotics. His publication trajectory reveals evolving focus from foundational AR visualization (2010-2016) toward applied XR solutions in healthcare, industrial training, and user experience optimization (2017-2024). Recent work demonstrates increasing integration of physiological inputs, real-world safety applications, and enterprise-grade XR prototyping. Scientific recognition includes: Honorable Mention for Best Paper at CHI 2022 for 'AirRes Mask' breathing interface Honorable Mention for Best Paper at IEEE 3DUI 2017 for adaptive rendering techniques As Head of Research, Tatzgern actively shapes the field through program committee roles and peer review for top venues including ACM CHI and IEEE VR. His four patents in AR visualization demonstrate translational impact from academic research to practical applications. The Digital Realities Lab operates as an innovation hub where software engineers, designers, and creative technologists collaborate on next-generation interaction paradigms. Current projects emphasize medical XR applications, industrial training systems, and accessibility-focused AR solutions for vulnerable populations.

• 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.

• Marketing
• Market Research
• Corporate Management
• +۸ مورد دیگر

Professor Ralf Terlutter is a faculty member at the University of Klagenfurt's Faculty of Economics and Law, leading the Department of Marketing and International Management. He holds multiple roles, including Head of the International Management program, Coordinator for International Relations, and Director of the Institute for Management. His research focuses on marketing, corporate social responsibility, health communication, consumer behavior, and media effects. Key areas include cross-cultural advertising, sustainable business ecosystems, and digital transformation. He has led numerous funded projects, such as the 'NoFakeFacts!' citizen science initiative promoting media literacy. His work bridges academic research with practical applications in business and healthcare. Notable contributions include studies on political microtargeting avoidance, robotic automation in logistics, and pandemic-era healthcare workforce challenges. Research Interests: Professor Terlutter’s interdisciplinary research spans health marketing, CSR communication, and media convergence. He explores how cultural dimensions influence advertising effectiveness and investigates technological advancements like AI in healthcare and robotics. Recent projects emphasize sustainability in entrepreneurial ecosystems and the ethical implications of digital advertising. Grants & Projects: NoFakeFacts! (2025–2028): Promotes media literacy among youth through citizen science. Heterogeneous multi-agent localization (2025–2028): FFG-funded robotics research for GPS-disturbed environments. Wind Turbine Blade Inspection (2025–2028): FFG project using drones for maintenance optimization. Teams & Labs: Leads the Institute’s Marketing and International Management Unit, fostering collaborative research initiatives with industry partners like Infineon Technologies and NOI AG. Engages in international networks through Erasmus+ programs and OeAD-funded projects.

• Nature-Based Solutions
• Green Infrastructure
• Vegetation Technology
• +۴ مورد دیگر

Anna Katharina Briefer (Dipl.-Ing.) is a researcher at the Institute of Soil Bioengineering and Landscape Construction , University of Natural Resources and Life Sciences, Vienna (BOKU). She specializes in nature-based urban solutions, focusing on integrating vegetation into architectural and infrastructural systems for climate adaptation. Her work bridges technical soil bioengineering with participatory landscape planning. Education: PhD studies in landscape planning (2022), Master's thesis (2021) Research spans green infrastructure , vertical greening , and climate-resilient urban design , with notable projects on thermal regulation of glazed buildings and community-led green space management. Her publications emphasize ecosystem services and sustainable resource use . Key projects include Klimaquartier Melk (2024-2027), Meidlinger "L" Demo (2024-2027), and MossDule (2023-2026), all funded by the Austrian Research Promotion Agency (FFG) and institutional partners. Active in knowledge transfer, she contributes to public workshops, the BOKU Research Information System (FIS) , and urban climate initiatives in Vienna. Her work combines bioengineering techniques with social ecology to create scalable climate adaptation models.

• Intercultural Communication
• Media Representations of Migrants
• Racial and Cultural Identity
• +۳ مورد دیگر

Jolanta Drzewiecka is an Associate Professor at the University of Lugano (Università della Svizzera italiana), serving as Vice Dean of the Faculty of Communication, Culture and Society. Her academic journey includes roles as Senior Assistant Professor (2016–2019) and Guest Professor at the University of Zürich (2015). Previously, she held professorial positions at Washington State University (USA) from 1997 to 2015. She specializes in intercultural communication, migrant integration, and discursive constructions of identity and memory. Her research focuses on media representations of migration, racial and cultural identity negotiation, and collective memory. Notable projects include a Swiss National Science Foundation-funded study on migrant belonging (2017) and current work on affective dimensions of place-based integration. She has received awards such as the 2010 Ralph Cooley Outstanding Scholarship Award. Drzewiecka’s work bridges theory and practice, addressing topics like EU enlargement discourses, immigrant racial incorporation, and the interplay between affect and power in everyday social practices. Her current projects explore relational integration in smaller Swiss cities, emphasizing ethnographic methods and interdisciplinary approaches. Grants: SNSF-funded projects on migrant belonging (2017), relational integration in place (current), and inclusion of refugees (Agora project). Labs/Teams: Institute of Communication and Public Policies (ICPP) at USI.

• Artificial Intelligence
• Knowledge Engineering
• Machine Learning
• +۳ مورد دیگر

Konstantin Schekotihin is an Associate Professor at the Institute of Artificial Intelligence and Cybersecurity , part of the Faculty of Technical Sciences at Alpen-Adria-Universität Klagenfurt. His research focuses on AI-driven solutions for semiconductor manufacturing, failure analysis, and multi-agent systems. He specializes in reinforcement learning, scheduling optimization, and neuro-symbolic AI applications. His work bridges theoretical advancements with industrial challenges such as semiconductor fab automation and real-time process monitoring. He has collaborated with organizations like the Austrian Research Promotion Agency (FFG) and Infineon Technologies. Key research areas include: AI for semiconductor failure analysis workflows Reinforcement learning in manufacturing scheduling Multi-agent systems in immersive VR environments Neuro-symbolic AI for defect routing Predictive modeling for equipment maintenance Recent projects involve optimizing ion implantation processes, developing FA ChatBots, and improving social presence in VR simulations. His work emphasizes scalability, explainability, and real-world applicability of AI systems.

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.

• Blockchain Technology
• Cyber-Physical Systems
• Building Information Modeling (BIM)
• +۳ مورد دیگر

Thomas Preindl is a Researcher at the Automation Systems department of TU Wien's Faculty of Mechanical and Automotive Engineering and Transportation. His work focuses on blockchain technology, BIM integration, and cyber-physical systems, with applications in construction, energy systems, and Industry 4.0. He holds a BSc and a diploma in engineering from TU Wien. Education : BSc in Engineering, TU Wien (year not specified); Diploma in Automation Engineering, TU Wien (2019). Research : Preindl’s research explores blockchain applications in process automation, decentralized systems, and circular economy. Notable projects include DiCYCLE (2022–2026), exploring blockchain for sustainable construction, and FORA (2017–2021) on facility management frameworks. His work often bridges BIM with smart contracts to enhance transparency and efficiency in construction workflows. Articles : His recent publications address confidential process execution on blockchain, storage optimization for containerized systems, and BIM-integrated blockchain tools. Key themes include decentralized frameworks, fault detection, and energy system dependability. Grants & Projects : Funded by the Austrian Research Promotion Agency (FFG), his projects span 2015–2027, focusing on circular economy, energy data spaces, and IoT integration in industrial systems. Advising : Supervised 6 diploma theses on topics like zero-knowledge proofs in BPM, decentralized storage systems, and BIM data management via smart contracts. Labs/Teams : Active in TU Wien’s Automation Systems group, contributing to interdisciplinary projects in industrial automation and digital transformation.

• Production and Maintenance Management
• Knowledge-Based Maintenance
• Industry 4.0
• +۴ مورد دیگر

Prof. Fazel Ansari is a University Professor of Data-Driven Maintenance Management at Vienna University of Technology's Faculty of Mechanical Engineering and Industrial Management. He leads the Production and Maintenance Management Research Department and holds adjunct roles at multiple institutions including Fraunhofer Austria. His research focuses on knowledge-based maintenance strategies, Industry 4.0 transformation, and human-centered cyber-physical systems. Ansari serves on editorial boards for journals like AI and Intelligent Manufacturing, and holds leadership roles in professional organizations such as CIRP and IFAC. Education: Habilitation (venia docendi) in Industrial Engineering, TU Wien (2021) PhD in Computer Science (summa cum laude), Universität Siegen (2014) MSc Mechatronics, Universität Siegen (2008) BSc Mechanical Engineering, Universität Teheran (2005) Research interests emphasize applying AI and data science to optimize maintenance systems, enhance manufacturing sustainability, and develop reciprocal learning frameworks for human-machine collaboration. His work bridges technical systems with workforce development through digital twin applications and competence management solutions. Awards include the 2023 Best Paper Award from the University of Technology Sydney, Theta Award (2015), and multiple best paper recognitions at international conferences. Teaching responsibilities span master's and executive programs in maintenance management, production systems, and data science applications across TU Wien's Mechanical Engineering and Management Sciences faculties.