جستجوی استاد راهنمای دانشگاهی

Gernot Rottermanner is a Researcher at the Media Computing Research Group within the Department of Media and Digital Technologies at St. Pölten University of Applied Sciences' Institute of Creative\Media/Technologies. He has been working at the institution since September 1, 2013, focusing on Usability Evaluation and User Centered Design within various research projects. Rottermanner completed his studies in Media Technology and Digital Media Technologies at St. Pölten University of Applied Sciences from 2008 to 2013, following which he worked as a Student Assistant at the same university from 2011 to 2013 before transitioning to his current research role. His research spans multiple domains including Human-Computer Interaction, Usability Evaluation, Accessibility Technologies, and AI/Machine Learning applications. Rottermanner has made significant contributions to air traffic control systems, accessibility solutions for elderly users, and industrial applications of digital technologies. His work often involves developing and evaluating prototypes for real-world applications, particularly in safety-critical environments and media technology contexts. Analysis of Rottermanner's recent publications (2019-2024) reveals a strong focus on practical applications of HCI principles across diverse domains. His work demonstrates consistent collaboration with industry partners and academic colleagues, with particular emphasis on user-centered solutions for media technology, air traffic control systems, and industrial automation. The publications show an evolution from foundational usability studies toward more complex AI-integrated systems, reflecting broader trends in the field. As a member of the Media Computing Research Group, Rottermanner contributes to numerous research projects including TrustAI, FairMedia, ERIKA, comfort:zone, QUAKE-iP, CLUE, and several iterations of CargoRider platforms. His work often bridges theoretical research with practical implementation, particularly in developing user interfaces for specialized contexts such as aviation and industrial manufacturing.

• Human-Computer Interaction
• Usability Evaluation
• User Centered Design
• +۵ مورد دیگر

Herr Marc Masana Castrillo is a Researcher at the Institute of Computer Graphics and Vision within Graz University of Technology (College of Engineering). Holding a PhD in Computer Vision (cum laude) from Universitat Autònoma de Barcelona (2020), he specializes in Deep Learning , Continual Learning , and Neural Network Compression . His work addresses catastrophic forgetting in sequential tasks, out-of-distribution detection, and domain adaptation. PhD Thesis: "Lifelong Learning of Neural Networks: Detecting Novelty and Adapting to New Domains without Forgetting" MSc in Computer Vision (with Honours, 2015) BSc in Mathematics and Computer Science (2014) His research spans continual learning frameworks , feature disentanglement , and multimodal translation . Publications in top-tier venues like TPAMI , BMVC , and ICCV highlight his contributions. He co-developed Avalanche , an open-source PyTorch-based library for reproducible continual learning research. Scientific recognition includes the Best Master Thesis Project at UAB (2015) and the Business Track Award at Accenture Datathon (2016). His email addresses are mmasana@tugraz.at and marc.masana@icg.tugraz.at . He has reviewed for journals like TPAMI and conferences including CVPR and ICCV .

• Deep Learning
• Continual Learning
• Computer Vision
• +۳ مورد دیگر

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

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

Davide Ceneda is a Postdoctoral Researcher at the Vienna University of Technology (TU Wien), affiliated with the Institute of Visual Computing & Human-Centered Technology under the Faculty of Informatics. His research focuses on guidance systems in visual analytics and information visualization, particularly in time-oriented data analysis and user interaction. Education highlights include his Dr.-techn. (PhD) in Guidance-Enriched Visual Analytics completed in 2020 at TU Wien. He has collaborated extensively with institutions like the Institute of Visual Computing and researchers such as Silvia Miksch, Theresia Gschwandtner, and Alessio Arleo. Key research areas include: Guidance frameworks for mixed-initiative systems Temporal network visualization (e.g., TimeLighting) User confidence measurement under uncertainty Automated timing for guidance interventions Recent work emphasizes task-driven methodologies and practical frameworks like Lotse. His publications span top venues including IEEE TVCG, EuroVis workshops, and Computer Graphics Forum. No awards were explicitly listed in the provided materials. Active collaborations involve developing guidance systems for real-world applications like pandemic data journalism (COVIs project).

• Information Visualization
• Visual Analytics
• Time-Oriented Data Analysis
• +۳ مورد دیگر

Heinz Dobler serves as a Professor at the University of Applied Sciences Upper Austria, Hagenberg Campus, affiliated with the Research Center Hagenberg. With an h-index of 28 and 43 research outputs spanning 1986-2024, his career demonstrates sustained contributions to software engineering and programming languages. His research focuses on software development methodologies, compiler construction (particularly parsing techniques and semantic evaluation), static program analysis, and genetic programming. Significant work includes innovations in software testing for class libraries and educational approaches for programming novices, reflecting both theoretical depth and practical application. Recent publications (2010-2024) reveal consistent advancement in compiler technologies and software engineering. Key trends include hybrid parsing techniques (BoB), framework-independent genetic programming (GPDL), and testable task design for programming education. His work bridges formal language theory with real-world software development challenges. Scientific awards: No major awards are documented in available records, though his h-index of 28 indicates substantial scholarly impact. Dobler has supervised at least two students, as noted in institutional records. While specific grant details are absent, his leadership in organizing the annual DACHS symposium series (2020-2024) demonstrates active involvement in collaborative research initiatives and academic community building. As a core member of the Research Center Hagenberg, he contributes to software engineering research teams and drives the DACHS symposium series, which fosters interdisciplinary collaboration in compiler design, genetic programming, and software testing. His ongoing 2024 activities confirm active research leadership within the institution.

• Software Development
• Compiler Design
• Static Program Analysis
• +۳ مورد دیگر

Univ.-Prof. Dr. Günther Specht is a faculty member in the Department of Computer Science at Universität Innsbruck. His research focuses on machine learning, data mining, and their applications in recommendation systems, music information retrieval, and authorship attribution. He has contributed to projects such as HPT4Rec (a hyperparameter optimization framework for recommenders) and Cloudgene (a cloud computing tool for biomedical pipelines). His work spans database systems, text analysis, and social media analytics. Notable tools include HaploGrep 2 (for mitochondrial DNA analysis) and StyleExplorer (for textual style visualization). Key research areas include: (1) Developing algorithms for music popularity prediction and playlist analysis; (2) Enhancing authorship attribution techniques using grammar profiling and syntax tree analysis; (3) Designing efficient database index structures like Height Optimized Tries; and (4) Investigating ethical aspects of recommendation systems and plagiarism detection. Publications from 2020-2024 highlight advancements in cross-domain text classification, social media behavior analysis, and automated music genre recognition. His work bridges traditional statistical methods with modern machine learning, emphasizing practical applications in both academic and industry contexts.

• Machine Learning
• Data Mining
• Recommendation Systems
• +۵ مورد دیگر

Thomas Fahringer is a full Professor and Head of the Distributed and Parallel Systems Group at the University of Innsbruck's Institute of Computer Science. His research focuses on parallel computing, distributed systems, and high-performance computing (HPC), with particular emphasis on GPU acceleration, cloud/edge computing, and serverless architectures. He leads interdisciplinary projects involving scientific workflows, resource management systems, and exascale computing solutions. Key research areas include: Design of high-level APIs for accelerator clusters (e.g., Celerity-RSim) Optimization of IoT and LoRa networks using machine learning Scalable key-value stores for geo-distributed systems Workflow scheduling in edge-cloud continuum environments Recent work emphasizes automation of deployments, energy-efficient transmission policies, and fault-tolerant orchestration of serverless functions. He actively participates in community initiatives like the Workflows Community Summit, driving advancements in scientific workflows and HPC ecosystems. His lab develops frameworks such as Apollo and AllScale, targeting exascale computing and distributed runtime systems.

• Parallel Computing
• Distributed Systems
• High-Performance Computing (HPC)
• +۴ مورد دیگر

Josef Altmann serves as a Professor at the University of Applied Sciences Upper Austria, specifically within the School of Informatics, Communications and Media at the Hagenberg Campus. He leads research activities at the Research Center Hagenberg Knowledge Media and Engineering and contributes to the AIST Digital Transformation Strength area focused on ICT - Information & Communication Technology. His academic credentials include Mag. Dr. qualifications, reflecting advanced academic achievements in his field. Professor Altmann's research spans multiple interconnected domains of Human-Computer Interaction, with particular emphasis on user interaction , personalization , and digital platform development . His work consistently addresses practical applications across diverse sectors including volunteering systems, construction technology, and intralogistics. The research fingerprint analysis reveals strong concentrations in Human-Computer Interaction (77%), User Interaction (100%), Personalization (64%), and Input Devices (64%), with notable contributions to Tabletop interfaces (59%) and Neurorehabilitation (47%). His approach integrates theoretical HCI principles with real-world problem-solving, particularly evident in his development of goal-oriented volunteering platforms and industry 4.0 applications. Analysis of his recent publication trends shows a clear trajectory toward applied research with societal impact. His 2024 works focus on leveraging Large Language Models for volunteering platforms, demonstrating adaptation to emerging AI technologies. Earlier publications (2021-2022) established foundations in mixed reality applications for intralogistics and digital transformation of construction sites. The consistent thread across his work involves creating user-centered digital solutions that address specific domain challenges while advancing HCI methodologies. His publications appear primarily in computer science venues with strong industry relevance. Best Paper Award HUCAPP 2018 - International Conference on Human-Computer Interaction Theory and Applications Professor Altmann actively contributes to the research ecosystem through numerous funded projects. Current major initiatives include iReduce (2025-2026) focusing on alarm flood reduction in critical infrastructure, AI-supported knowledge database development for industrial plastics production (2024-2027), and CIvolunteer (2023-2025) for digital volunteer engagement. He serves as a key researcher in these collaborative efforts, often working with Schönböck, Augstein, and Bodenhofer. His grant portfolio demonstrates strong industry-academia collaboration, particularly with COMET Competence Centers and KIRAS research programs. He also maintains an active role in the scientific community through conference participation, peer review activities, and organizational contributions. As part of the Research Center Hagenberg Knowledge Media and Engineering, Professor Altmann contributes to a vibrant research environment focused on digital transformation. His work intersects with several research teams focusing on human-centered computing, with particular connections to groups working on interaction design, digital platforms, and industry 4.0 applications. The collaborative nature of his projects indicates strong integration within both the university's research structure and external industry partnerships, particularly in the Austrian technology sector.

• Human-Computer Interaction
• User Interaction
• Personalization
• +۹ مورد دیگر

Prof. Maria Christakis is a Full Professor in the Faculty of Informatics at TU Wien, leading the Rigorous Software Engineering Group and the Software Engineering Research Unit (E194-01). Her research focuses on developing reliable software tools, emphasizing formal methods, program analysis, and automated testing. She holds leadership roles including Curriculum Coordinator for Software Engineering programs and Faculty Council membership. Her research interests span automatic test generation, program verification, and improving developer productivity through novel techniques. Notable projects include the 'Sherlock' framework for testing program analyzers and 'Olympia' for Solidity fuzzer benchmarking. Awards include Amazon and Google Research Awards, and she actively contributes to conferences like CAV, ASE, and IJCAI. Prof. Christakis advises over 15 students (PhD, Master's, and project students) and has supervised numerous alumni. She teaches core courses like Advanced Software Engineering and oversees Bachelor/Master curricula. Her work bridges formal verification and systematic testing, with tools like 'queryFuzz' and 'LIBRA' addressing neural network fairness and SMT solver reliability. Current projects include the 'Nomos' specification language for machine learning safety and the 'LaZ' framework for lazy testing. She co-leads the Automated Reasoning doctoral school and collaborates with institutions like MPI-SWS and Microsoft Research.

• Software Engineering
• Formal Methods
• Program Analysis
• +۷ مورد دیگر

Florian Mischek is a researcher affiliated with TU Wien's Forschungsbereich Databases and Artificial Intelligence department. His work focuses on optimization problems in industrial scheduling, particularly in test laboratories and healthcare environments. He holds a BSc, Dipl.-Ing (engineer's diploma), and a Dr.techn (doctorate) in technical sciences. Research interests include scheduling algorithms, hyper-heuristics, constraint programming, reinforcement learning, and their applications to real-world challenges like test laboratory operations and pandemic-era healthcare staffing. His contributions span both theoretical advancements in optimization frameworks and practical system implementations for automated scheduling. Notable publications explore problem-independent hyper-heuristics, reinforcement learning for cross-domain optimization, and local search frameworks for industrial scheduling. He has collaborated extensively with Prof. Nysret Musliu on projects involving test laboratories and nurse rostering problems. His work often bridges mathematical programming and heuristic approaches, emphasizing practical applicability.

• Operations Research
• Scheduling Algorithms
• Artificial Intelligence
• +۳ مورد دیگر

Jean D. Hallewell Haslwanter serves as Professor at the University of Applied Sciences Upper Austria, Campus Wels, where she leads research in the Research Center Wels with affiliations to the Center of Excellence Automotive/Mobility and Center of Excellence for Smart Production. Her work integrates thermography, non-destructive testing, and smart automation with human-centered design principles. Education PhD in Informatics, Thesis: User-Centered Development of sensor-based Systems for Older People, TU Wien (2017) Master in Computing Sciences, Thesis: Participatory Design Methods in the Context of Human-Computer Interaction, University of Technology Sydney (1996) Bachelor in Mathematics, Stanford University (1987) Research Interests Dr. Haslwanter pioneers assistive technologies for aging populations , investigating ambient assisted living systems, aging-in-place solutions, and ageism in user experience design. Her non-destructive evaluation research applies AI to thermography and robotics for industrial inspection, while her educational technology work develops programming pedagogy for novices. These interconnected fields address critical gaps in technology accessibility for elderly users and workforce training. Publication Trends Recent publications (2022-2024) reveal dual research tracks: assistive technology studies examining computer literacy barriers among seniors and ageism in design processes, alongside programming education innovations using test-first methodologies. This demonstrates consistent focus on human-technology interaction across demographic spectrums. Scientific Awards No specific awards were documented in the source material. Advising and Grants She has supervised at least one graduate student. Major funded projects include: FLARE (2025-2027): Developing human-centered AI for high-rate non-destructive evaluation in industrial settings COIN Cooperation & Innovation (2016-2021): Creating automatic assistance systems for production workplaces Palmaster Usability Reviews (2014-2015): Designing interface solutions for storage systems Labs and Teams As core faculty in Research Center Wels, she directs the Smart Automation and Robotics group and Thermography research cluster. Her interdisciplinary teams collaborate with automotive manufacturers and healthcare technology firms on EU-funded initiatives, maintaining strong industry partnerships through the Center of Excellence Automotive/Mobility.

• Assistive Technology
• Ambient Assisted Living
• Aging in Place
• +۵ مورد دیگر

Horst Possegger is a Computer Vision researcher at the Institute of Computer Graphics and Vision at Graz University of Technology, Austria. He holds a BSc and MSc in Software Development and Business Management (2011, 2013) and a PhD in Computer Science (2018), all from Graz University of Technology. His research focuses on multiple object tracking/detection, human behavior analysis, and video analysis with applications in autonomous systems, LiDAR data processing, and robotics. Key projects include trajectory prediction, 3D object detection, and domain adaptation techniques for real-world scenarios. Recent work emphasizes cross-modal learning (e.g., vision-language models for LiDAR data), robust localization in challenging environments, and lightweight motion prediction models. He contributes to the Learning, Recognition & Surveillance (LRS) group and has published extensively in top-tier venues like IEEE/CVF CVPR and IROS. Publications span autonomous driving benchmarks, UWB-based localization, and warehouse automation. His work often bridges theoretical advancements with practical implementations in robotics and surveillance systems.

• Computer Vision
• Autonomous Systems
• Multiple Object Tracking
• +۳ مورد دیگر

Dr. Peter Schüller is a Professor affiliated with the Department of Knowledge-Based Systems at TU Wien (Vienna University of Technology). He holds the academic title of Privatdozent (Priv.-Doz.) and has a background in Technical Engineering (Dipl.-Ing. Dr.techn. / Bakk.techn.). His roles include academic research, consulting services for intelligent automation, and partnership with Potassco Solutions. He is based at Favoritenstrasse 11, Room HG0312, and can be contacted via peter.schueller@tuwien.ac.at or contact@peterschueller.com. Education : Master's Thesis: 'Reconstructing borders of manually torn paper sheets using integer linear programming' (2008) PhD (Dr.techn.) in Informatics Habilitation (Privatdozent) qualification Research Interests : Schüller specializes in declarative problem solving through Answer Set Programming (ASP), with focus areas including hybrid knowledge integration systems, inconsistency management, and applications in robotics, traffic optimization, and industrial automation. His work bridges theoretical advances in computational logic with practical implementations in enterprise software architecture and database systems. Projects & Grants : He has led projects funded by the Austrian Research Promotion Agency (FFG), Austrian Science Fund (FWF), and Vienna Science and Technology Fund (WWTF). Key projects include: 'Dynamic knowledge-based (re)configuration of cyber-physical systems' (2017–2020) 'Integrated Evaluation of Answer Set Programs' (2015–2018) 'Inconsistency Management for Knowledge-Integration Systems' (2009–2012) Consulting & Partnerships : Provides services in enterprise software design, database optimization, GDPR compliance, and hybrid knowledge systems. Official partner of Potassco Solutions. Collaborates on initiatives like AI4EU and HumanE-AI-Net. Labs & Teams : Active in TU Wien's Knowledge-Based Systems Group. Involved in developing the DLVHEX and Hexlite solvers.

• Answer Set Programming
• Knowledge Representation and Reasoning
• Cyber-Physical Systems
• +۳ مورد دیگر

Manuel Wimmer is a Lecturer in Business Informatics at TU Wien's Faculty of Informatics, specializing in model-driven engineering methodologies. His research develops foundations for model transformation, metamodeling, and interdisciplinary engineering. Research interests include model-driven software engineering, cyber-physical systems, web engineering, and industrial automation, with applications in smart production systems. Current work focuses on bridging IT/OT domains through standardized modeling approaches. Recent publications address quantum-edge cloud architectures, AI-enhanced modeling, and industrial security challenges. Article trends demonstrate strong focus on modeling language engineering, interoperability solutions, and quality assurance in complex systems. Leads the Christian Doppler Laboratory for Model-Integrated Smart Production and coordinates EU projects on low-code engineering platforms. Supervises doctoral research in model-driven technologies and software quality.

• Model-Driven Engineering
• Model Transformation
• Web Engineering
• +۳ مورد دیگر

Ivona Brandic is a Full Professor of High Performance Computing Systems at TU Wien's Institute of Information Systems Engineering, leading the HPC Research Group. She specializes in Computational Sustainability, Cloud/Edge Computing, and Quantum-Classical Systems. Her roles include Head of the Computational Sustainability Research Unit and membership in TU Wien's Faculty Council. She teaches courses such as AI/ML in Climate Change and Hybrid Quantum-Classical Systems. Her research focuses on sustainable IT, energy-efficient systems, and hybrid quantum-classical workflows. Projects include computational sustainability initiatives funded by the Austrian Science Fund (FWF) and industry partnerships like the Virtual Shepherd project. She has contributed to over 50 publications, emphasizing edge computing, quantum algorithms, and HPC optimization. Notable contributions include developing frameworks like RIGOLETTO for hybrid scientific workflows and FRESCO for edge offloading. Her work bridges theoretical advancements with practical applications in environmental monitoring and energy efficiency.

• Computational Sustainability
• Cloud Computing
• Edge Computing
• +۳ مورد دیگر