جست‌وجوی استاد و پژوهشگر

Susanne Buiterمشاهده پروفایل

استاد

• Geodynamics
• Tectonics
• Structural Geology
• +۷ مورد دیگر

Prof. Dr. Susanne Buiter is Scientific Executive Director and Spokesperson of the GFZ German Research Centre for Geosciences in Potsdam, Germany, and Professor of Tectonics and Geodynamics at RWTH Aachen University since 2020. Her career spans roles in Norway, Canada, and Switzerland, including leadership at the Geological Survey of Norway (2006-2020) and adjunct professorship at Oslo University. PhD in Tectonophysics from Utrecht University Specialist in numerical modeling of crustal deformation Developer of 2D/3D software SULEC Research Focus Buiter's work centers on geodynamic processes across scales, including: Quantitative deformation analysis in crust and lithosphere Subduction zone dynamics and continental collision Wilson Cycle modeling (subduction, collision, rifting) Rifted continental margin evolution Benchmarking numerical and analogue tectonic models Her research integrates computational methods with geological observations to study processes from sedimentary basin inversion to mantle plume effects on continental breakup. Scientific Leadership Vice-President, Helmholtz Research Field 'Earth and Environment' (2024-2025) Union Service Award, European Geosciences Union (2022) Marie Skłodowska-Curie Doctoral Network 'Talents' Co-PI (2023) Editorial leadership at Solid Earth (2019-present) Young Outstanding Scientist Award, Norwegian Research Council (2007) As Executive Editor of Solid Earth and organizer of 8 international workshops, she actively shapes geodynamic research and open science initiatives.

• Decision support systems
• Computational intelligence
• Recommender systems
• +۴ مورد دیگر

Distinguished Professor Jie Lu is Associate Dean (Research Excellence) in the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS), where she also serves as Director of the Australian Artificial Intelligence Institute (AAII). With over two decades of academic service at UTS, she has held progressively senior roles including Professor since 2007, Head of School of Software (2011-2014), and Director of the Centre for Artificial Intelligence (2017-2020) before assuming her current leadership positions. Professor Lu earned her PhD from Curtin University in 2000 and joined UTS the same year. Her academic journey progressed from Lecturer (2000-2001) to Senior Lecturer (2002-2004), Associate Professor (2005-2007), and ultimately Professor (2017-present). Professor Lu's research spans computational intelligence with particular expertise in decision support systems, fuzzy transfer learning, concept drift, and recommender systems. Her work bridges theoretical innovation with practical applications across transportation, telecommunications, healthcare, and education sectors. She has pioneered approaches in data-driven decision making that deliver tangible economic benefits and risk management solutions for industry partners. Her recent publications demonstrate continued leadership in AI research, with a focus on addressing challenges in non-stationary environments, out-of-distribution detection, cross-domain recommendation, and healthcare applications. Her work increasingly integrates large language models with specialized domain knowledge for enhanced decision support. Officer of the Order of Australia (2022) 2023 NSW Premier's Prize for Excellence in Engineering or Information & Communication Technology Australian Laureate Fellow (2019) IEEE Fellow for contributions to fuzzy machine learning and decision making (2018) Fellow of International Fuzzy Systems Association (2017) Australia's Most Innovative Engineer Award (2019) Multiple IEEE Transactions Outstanding Paper awards Professor Lu has supervised over 50 PhD students to completion, with half pursuing academic careers and half working in industry. She has secured over A$10 million in research funding as lead Chief Investigator, including 10 highly competitive ARC Discovery Projects. Her industry collaborations include significant projects with Optus, Sydney Trains, Domain Holdings, and healthcare organizations. As Director of the Australian AI Institute, Professor Lu leads Australia's largest AI research hub with over 250 researchers and PhD students. Under her leadership, AAII has secured 47 ARC grants and over 110 industry projects since 2017. She also serves as Editor-in-Chief of Knowledge-Based Systems, a leading journal in the field.

Anita Onayمشاهده پروفایل

استاد

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

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

• Conceptual Modeling
• Machine Learning
• Software Engineering
• +۲ مورد دیگر

Aleksandar Gavric is a PreDoc Researcher at the Business Informatics Group of TU Wien. His research focuses on conceptual modeling and machine learning integration, as evidenced by his 2023 publication on systematic reviews of model encoding for ML applications. He holds degrees in Engineering (MEng and B.Eng) and is affiliated with the university's Department of Business Informatics. His work bridges theoretical modeling frameworks with practical ML implementations in enterprise systems. As part of the Business Informatics Group, he collaborates with senior faculty like Prof. Henderik Proper and contributes to projects in enterprise engineering and digital transformation. His current research emphasizes understanding how conceptual models are encoded to enhance ML-driven solutions in software and information systems.

• Software Architecture
• Domain-Specific Languages
• Model-Driven Software Development
• +۳ مورد دیگر

Dr. Michael Szvetits is a Lecturer and Researcher at the Institute of Computer Sciences at the University of Applied Sciences Wiener Neustadt. He holds a PhD in Computer Science from the University of Vienna (2019), an MSc in Computer Science (2012), and a BSc in Information Technology (2010), all from the University of Applied Sciences Wiener Neustadt. His research focuses on software architecture, domain-specific languages, model-driven software development, functional programming, logic programming, and compiler construction. He has contributed to projects such as 'Care about Care' (C^C), which aims to enhance home care through ICT solutions, and 'CARU cares,' which integrates emergency call systems with care documentation tools. His publications span topics like runtime event analysis, model-driven engineering, and software architecture decisions. He collaborates on initiatives funded by the FFG and Active Assisted Living Programme. Dr. Szvetits is actively involved in research projects targeting healthcare technology, software systems optimization, and innovation in assistive living solutions.

• Conceptual Modeling
• Model-Driven Engineering
• Enterprise Architecture
• +۳ مورد دیگر

**Dominik Bork** is an Assistant Professor at the Department of Business Informatics within the Faculty of Informatics at TU Wien. His core research focuses on conceptual modeling, model-driven engineering, and the integration of artificial intelligence into enterprise systems. He leads projects such as the Network Lab and has coordinated initiatives like the Automatisiertes End-to-End-Testen von Cloud-basierten Modellierungswerkzeugen and MFP 4.2 Advanced Analytics for Smart Manufacturing . His work emphasizes GLSP-based web modeling tools , including the development of open-source platforms like BIGUML for UML modeling. He has published extensively on topics like knowledge graph transformation, accessibility in modeling tools, and AI-enhanced decision management. Bork actively contributes to academic communities through conference organizing roles and guest editorial work for journals like Enterprise, Business-Process and Information Systems Modeling . His research bridges theoretical advancements with practical applications in enterprise architecture and sustainable systems engineering. Education & Background : Holds titles including Dipl.-Wirtsch.Inf.Univ. and Dr.rer.pol., reflecting his interdisciplinary expertise in business informatics and economics. Key Contributions : - Developed CM2KGcloud , a web-based platform for conceptual model-to-knowledge graph transformation. - Pioneered EA ModelSet , a FAIR dataset advancing machine learning in enterprise modeling. - Authored influential papers on inclusive conceptual modeling for disability-aware tools. - Led efforts in model-based construction of enterprise architecture knowledge graphs . Grants/Projects : Automatisiertes End-to-End-Testen von Cloud-basierten Modellierungswerkzeugen (Principal Investigator) Digital Platform Enterprise (Principal Investigator) MFP 4.2 Advanced Analytics for Smart Manufacturing (Principal Investigator) Labs/Teams : Active in the Network Lab at TU Wien, focusing on cutting-edge research in modeling technologies and AI integration.

• Computer Vision
• Autonomous Driving
• 3D Reconstruction
• +۵ مورد دیگر

Ao.Univ.Prof. Margrit Gelautz is an Associate Professor at TU Wien's Computer Vision research department (E193-01), affiliated with the Institute for Software Technology and Interactive Systems (E188). Her work focuses on computer vision applications in autonomous driving, robotics, and 3D reconstruction. She leads projects on driver monitoring systems, vulnerable road user detection, and human-robot interaction. Recent research includes 3D bounding box prediction, synthetic data-driven pose estimation, and real-time sensor systems. She advises over 20 graduate students and collaborates on automotive platforms integrating vision-based safety systems. Her contributions span sensor fusion, stereo matching algorithms, and interactive video tools. Key projects include multimodal sensor-lighting systems for traffic safety, 3D scene completion, and intelligent workflow design for low-cost 3D film production. Her work emphasizes practical applications like in-cabin monitoring systems and adaptive lighting control. She develops semi-automatic annotation tools for traffic datasets and explores nonverbal communication in human-robot interaction using platforms like Pepper humanoid robots.

• Software Engineering
• Model-Driven Engineering
• Cloud Computing
• +۳ مورد دیگر

Dr. Philip Langer is a researcher at TU Wien's Institut für Information Systems Engineering, part of the Faculty of Informatics. His work focuses on model-driven engineering, semantic model differencing, and cloud-based software modernization. He contributed to frameworks like GLSP, ARTIST, and xMOF, emphasizing tool integration and collaboration in modeling environments. Research Areas: Model transformation, UML semantics, cloud migration, and search-based optimization Key Projects: ARTIST (cloud migration), GLSP (web modeling tools), xMOF (formal semantics) Publications highlight advancements in model differencing using execution traces, multi-objective model merging (MOMM), and semantic visualization techniques for web-based IDEs. His work bridges theoretical foundations with practical tool development, addressing challenges in collaborative modeling and legacy system modernization. Awards: No specific prizes mentioned, but recognized through prolific conference contributions and framework development. Grants/Advising: He collaborates extensively with peers like Tanja Mayerhofer and Manuel Wimmer, though specific grants or student advisement details are not explicitly stated. His research impacts both academic and industrial software engineering practices.

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

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

• Formal Methods
• Model-Driven Engineering
• SAT/QBF Solving
• +۴ مورد دیگر

Martina Seidl is a researcher and principle investigator at TU Wien's Institut für Softwaretechnik und Interaktive Systeme (E188). Her main affiliation is within the Faculty of Informatics. She leads the FAME Project (Formalizing and Managing Evolution in Model-Driven Engineering), focusing on advancing formal methods in software engineering. Her research interests include formal verification techniques, SAT/QBF solving algorithms, model-driven engineering, and automated reasoning. She has contributed to advancements in quantified Boolean formula (QBF) solving, parallel computing methodologies for logical problems, and formal methods in software model analysis. Her work spans theoretical computer science and practical applications in automated theorem proving and model checking. Notable contributions include expansion-based QBF solving approaches, parallel solving frameworks, and feature-based classifications of formal verification techniques. Seidl co-organized the QBF Gallery initiative, which curates benchmark suites for quantified Boolean formula competitions. She has also published extensively on clause redundancy optimization, blocked clause analysis, and the integration of formal methods in educational contexts like UML@Classroom.

• Artificial Intelligence
• Recommender Systems
• Configuration Systems
• +۷ مورد دیگر

Alexander Felfernig is a full Professor at Graz University of Technology, Austria, where he leads the Applied Software Engineering & AI (ASE) research group. He earned his PhD in Computer Science from the University of Klagenfurt and has been a key contributor to AI and software engineering research since 2009. His research focuses on intelligent systems, particularly in the domains of recommender systems, knowledge-based configuration, model-based diagnosis, and software requirements engineering. He investigates the intersection of human decision-making and AI, with growing interest in sustainability within computing systems. His work emphasizes practical applications of AI in software engineering and user-centered systems. Felfernig has published extensively in top-tier international journals and conferences such as IJCAI, AAAI, ECAI, ACM Recommender Systems, IEEE Transactions on Engineering Management, and Artificial Intelligence. His publications reflect a strong trend in AI-driven software systems, personalized recommendation technologies, and formal modeling of user preferences and constraints. Co-author of Recommender Systems (Cambridge University Press) Co-author of Knowledge-based Configuration (Elsevier/Morgan Kaufmann) Co-author of Group Recommender Systems and Feature Models – AI-Driven Design, Analysis and Applications (Springer) Felfernig has been actively involved in organizing major international events including the ACM Conference on Recommender Systems, International Symposium on Methodologies for Intelligent Systems, International Workshop on Configuration, and ACM Systems and Software Product Line Conference. These efforts highlight his leadership in the research community and his role in advancing collaborative and applied AI research. He is affiliated with the Applied Software Engineering & AI research group, which focuses on developing intelligent, scalable, and user-aware software systems.

Egon Lüfteneggerمشاهده پروفایل

مدرس ارشد

• Business Process Management
• Sentiment Analysis
• Process Mining
• +۳ مورد دیگر

Egon Lüftenegger is a Senior Lecturer at Fachhochschule Salzburg's Department of Information Technologies and Digitalisation. His work bridges academia and industry through innovative process mining and sentiment analysis applications. PhD in Information Systems (TU Eindhoven) Focus on Service-Dominant Logic and Business Process Management Active in Industry 4.0 and Digital Transformation research His research explores sentiment-driven process redesign, technology-enabled social inclusion, and smart production analytics. Publications highlight process mining frameworks , LLM applications in BPM, and service-dominant business models . Current projects involve creating tools like SentiProMoWeb and Cost-Benefit Tracker, with applications in manufacturing, airline services, and education sectors.

• Structural Engineering
• Computational Mechanics
• Isogeometric Analysis
• +۵ مورد دیگر

Aleksandar Borković is a Researcher at the Institute of Structural Mechanics , Graz University of Technology. His work focuses on advanced computational methods in structural engineering, particularly isogeometric analysis, finite strip modeling, and van der Waals interactions in slender structures. Department: Institute of Structural Mechanics Email: aborkovic@tugraz.at His research bridges theoretical mechanics and practical engineering applications, addressing nonlinear dynamics, contact mechanics, and geometrically exact formulations. Recent publications highlight innovative approaches to modeling molecular interactions in fiber systems and optimizing computational efficiency for structural simulations. The 15 most recent articles demonstrate expertise in: Van der Waals attraction in curved beams Geometrically exact isogeometric formulations Finite strip method for stiffened plates Contact dynamics in beam-to-beam interactions Nonlinear stability analysis of thin-walled structures Moving load simulations in spatial beams He has also contributed to educational software development for structural analysis, emphasizing real-time visualization and numerical accuracy.

• Single-cell Biology
• Bioinformatics
• Machine Learning
• +۷ مورد دیگر

Christoph Bock is a Principal Investigator at CeMM Research Center for Molecular Medicine and Professor/Head of the Institute of Artificial Intelligence at Medical University of Vienna. He leads the Biomedical Sequencing Facility and contributes to the Human Cell Atlas and ELLIS initiatives. Key research areas: Single-cell biology , Epigenetics , CRISPR screening , Machine learning , Cell therapy , Multi-omics Major contributions: CellWhisperer (natural language single-cell analysis), JAK-STAT signaling in immune homeostasis, LIQUORICE for liquid biopsies, and RnBeads software Scientific Awards include: ERC Starting Grant (2016) ERC Consolidator Grant (2021) Overton Prize (2017) Erwin Schrödinger Prize (2022) Clarivate Highly Cited Researcher (2019-2024) His lab develops bioinformatics tools (e.g., RnBeads, LIQUORICE) and applies systems immunology to understand disease mechanisms. Startup leadership : Co-founder of Myllia Biotechnology. Collaborations include clinical translations and tech development with the Biomedical Sequencing Facility.

Sarah Riedmannمشاهده پروفایل

پژوهشگر

• Industry 4.0
• Systems Engineering
• Reference Architectures
• +۳ مورد دیگر

Sarah Riedmann is a Junior Researcher at the Information Technologies and Digitalisation Centre for Dependable Systems Engineering, Salzburg University of Applied Sciences. She actively contributes to the Josef Ressel Centre for Dependable System-of-Systems Engineering (DeSoS) and Research Campus Schloss Urstein (RCSU), advancing Industry 4.0 implementation through reference architectures and simulation modeling. Education: Information Technology and Systems Management, Dipl.-Ing., Salzburg University of Applied Sciences GmbH (2021) Research Focus: Her work centers on RAMI 4.0 integration, resource capability modeling, and stakeholder-specific reference architectures. She investigates reinforcement learning applications in production systems and dependable system-of-systems engineering, addressing critical gaps in smart manufacturing resilience and design principle compliance. Publication Analysis: 2024 outputs reveal concentrated innovation in Industry 4.0 architecture frameworks, with dual emphasis on theoretical extensions (domain-specific languages for RAMI 4.0) and practical implementations (smart campervan retrofits). Her research consistently bridges reference architecture theory with production system validation, demonstrating cross-domain applicability from embedded systems to smart grids. Scientific Awards: No awards documented in source materials. Research Leadership: As Co-Investigator on major initiatives: RCSU: Research Campus Schloss Urstein (2023-2025) focusing on applied Industry 4.0 campus development DeSoS: Josef Ressel Centre for Dependable System-of-Systems Engineering (2020-2025) advancing methodology for complex industrial systems Collaborative Ecosystem: Operates within Salzburg University's digitalisation centre alongside interdisciplinary teams from engineering, computer science, and industrial partners, driving Austria's Josef Ressel Centre research agenda in dependable systems engineering.