جست‌وجوی استاد و پژوهشگر

Anna Christina Nobreمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Neuroimaging (MEG, EEG, fMRI)
• Attention and Expectation
• +۳ مورد دیگر

Anna Christina Nobre is the Wu Tsai Professor of Psychology at Yale University and Associate Director of the Wu Tsai Institute. She also holds roles as Director of the Center for Neurocognition and Behavior at Yale and retains affiliations at the University of Oxford, including Head of the Department of Experimental Psychology (2016–2023) and Director of the Oxford Centre for Human Brain Activity (OHBA). Her academic journey includes a PhD in Psychology from Yale (1993) and a BA from Williams College (1985). Her research focuses on cognitive neuroscience, particularly attention, temporal processing, memory, and large-scale neural networks, utilizing techniques like MEG, EEG, and fMRI. She leads the OHBA, equipped with advanced neuroimaging facilities, and has secured over £8M in research funding as principal or co-investigator. Professor Nobre has supervised numerous students and fellows, contributing to over 140 journal articles and receiving prestigious awards such as the Broadbent Prize and election to the Academia Europaea. Her work bridges fundamental cognitive research with translational applications in brain health.

• Geoinformatics
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Omid Reza Abbasi is a Research Fellow in Geoinformatics at the University of Salzburg , specializing in the integration of Artificial Intelligence, Machine Learning, and Geographic Information Systems (GIS) to address complex spatial challenges. His work spans diverse domains including spatio-temporal modeling, human mobility prediction, and semantic similarity measures in geospatial contexts. Projects : Collaborated on 'RegioWoodTrain,' a project focusing on sustainable regional wood transport through cooperative supply chain management using simulation and AI technologies. Research Interests : Omid's research emphasizes the application of AI and GIS in urban planning, transportation systems, and social media analysis. Key areas include: Large Language Models (LLMs) for geographical representation Semantic similarity assessment in geospatial data Human mobility pattern prediction using social networks Accessibility in WebGIS via audio interfaces Recommender systems for tourism and retail Spatio-temporal analysis of public services and environmental impacts Publications : His recent work explores the use of LLMs in GIS, novel semantic similarity metrics, and spatio-temporal modeling for urban governance. Articles from 2018-2025 highlight trends in AI-driven spatial analysis, collective mobility prediction, and georeferencing of semi-structured data. Contact : Email: omidreza.abbasi@plus.ac.at

Matthijs Cluitmansمشاهده پروفایل

استادیار

• Arrhythmia Mechanisms
• Sudden Cardiac Arrest
• Cardiac Research
• +۷ مورد دیگر

Matthijs Cluitmans is an Assistant Professor at Maastricht University and Senior Scientist at Philips Research , bridging academic science, clinical medicine, and medical technology. His work focuses on arrhythmia mechanisms in idiopathic ventricular fibrillation and healthcare innovation through AI and digital systems.

Josef Altmannمشاهده پروفایل

استاد

• Human-Computer Interaction
• User Interaction
• Personalization
• +۹ 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.

• Educational Technology
• Artificial Intelligence in Education
• Massive Open Online Courses
• +۳ مورد دیگر

Martin Ebner is an Associate Professor at Graz University of Technology, specializing in educational technology, artificial intelligence in education, and learning analytics. As Dean of Studies for Technical and Textile Design, Computer Science, and Descriptive Geometry, he oversees academic programs focused on modern pedagogical approaches. His research explores the integration of AI in educational contexts, including generative AI for content creation, chatbot-assisted learning, and multilingual resource development. Research interests center on educational technologies supporting self-regulated learning, with significant work on MOOC platforms, learning analytics dashboards, and digital transformation in higher education. Publications demonstrate consistent focus on AI-driven educational tools, teacher training for digital literacy, and international education infrastructure. Awards include recognition for innovative research methodologies and educational technology implementations. Advising activities emphasize doctoral training and research community development, particularly through European university alliances like Unite!.

Clemens Sauerweinمشاهده پروفایل

استادیار

• Information Security
• Cyber Threat Intelligence Sharing
• Information Security Risk Management
• +۱۴ مورد دیگر

Clemens Sauerwein is an Assistant Professor in the Department of Computer Science at the University of Innsbruck , Austria. His academic work spans information security, cyber threat intelligence, and innovative approaches in software engineering education. Position: Assistant Professor Institution: University of Innsbruck Department: Department of Computer Science Office: ICT Building, Room 3S03 Contact: clemens.sauerwein@uibk.ac.at His research is centered on Information Security , particularly cyber threat intelligence sharing , risk management , and organizational security culture . He also investigates Information Systems topics like crowdsourcing and socio-technical systems , and contributes to Security & Software Engineering Education through e-learning , AI integration , and security awareness training . The recent publications reflect a strong trend in empirical studies on threat intelligence platforms, automated programming assessment systems , and AI applications in education . His work combines technical and organizational aspects, often involving global or regional surveys and framework development. Scientific Contributions: Active research in cybersecurity and software engineering education Published in top venues like HICSS, ARES, ICEIS, and CSEE&T Focus on actionable intelligence and educational innovation He actively supervises bachelor’s and master’s theses in computer science and information systems, and leads projects like CySeReS-KMU to support SMEs in cybersecurity. He is involved in developing scalable educational tools and frameworks for learning analytics and AI tutoring. Labs and Teams: While no specific lab name is mentioned, his work is closely tied to empirical research in security and software engineering education, likely within collaborative research groups at the University of Innsbruck.

Mher Safaryanمشاهده پروفایل

پژوهشگر

• Optimization theory and algorithms
• Machine learning
• Federated learning
• +۷ مورد دیگر

Dr. Mher Safaryan is a postdoctoral researcher at the Institute of Science and Technology Austria (ISTA), affiliated with Prof. Dan Alistarh's research group since 2022. Previously, he held postdoctoral positions at King Abdullah University of Science and Technology (KAUST) from 2019-2022 and served as a research technician there from 2016-2019. He earned his Ph.D. in Mathematics from Yerevan State University in 2018 under Prof. Grigori Karagulyan's supervision. Education: Ph.D. in Mathematics (2018, YSU) Past Affiliations: KAUST (2016-2022), Neural Magic/Red Hat (industrial secondment) His research focuses on optimization theory and algorithms for machine learning , particularly in developing communication/computation/memory-efficient methods for large-scale training and federated learning. Key contributions include LDAdam (low-dimensional gradient statistics optimization), GradSkip (accelerated local gradient methods), and Unified Scaling Laws for compressed representations. He has published in top venues like NeurIPS, ICML, ICLR, TMLR, and The Journal of Geometric Analysis. Scientific Awards: Marie Skłodowska-Curie Fellowship (MSCA COFUND IST-BRIDGE) His work bridges machine learning optimization with mathematical foundations from his earlier research in real harmonic analysis. Current collaborations include Prof. Dan Alistarh (ISTA), Dr. Alexandre Marques (Neural Magic), and Prof. Peter Richtárik (KAUST).

Klaus Muellerمشاهده پروفایل

استاد

• Visual Analytics
• Explainable Machine Learning and AI
• Algorithmic Fairness and Transparency
• +۷ مورد دیگر

Klaus Mueller is a Professor in the Computer Science Department at Stony Brook University , with additional appointments in Biomedical Engineering and Radiology. He serves as Director of the Visual Analytics and Imaging (VAI) Lab, Liaison for the SUNY Korea CS Program, and Interim Chair of the Department of Technology and Society . His career spans roles at Brookhaven National Lab and leadership positions at SUNY Korea. Dr. Mueller earned his PhD in Computer and Information Science (1998), MS in Computer and Information Science (1996), and MS in Biomedical Engineering (1990) from The Ohio State University , alongside a BS in Electrical Engineering (1987) from the Polytechnic University of Ulm, Germany. His research focuses on visual analytics , explainable AI , algorithmic fairness , computational imaging , and medical imaging . He has pioneered GPU-accelerated CT reconstruction techniques, bias mitigation frameworks (e.g., D-BIAS), and tools like DOMINO for causal reasoning. His work bridges data science , human-computer interaction , and medical applications , often integrating large language models for visualization tasks. Recent publications highlight advances in multivariate volume rendering , LLM-driven bias detection , and mDDPM-based medical image synthesis . His articles span IEEE Transactions , Nature Machine Intelligence , and conferences like IEEE VIS and ACM CHI . Award highlights include NSF CAREER (2000), SUNY Chancellor Award (2011), IEEE Golden Core Award (2016, 2022), induction into the National Academy of Inventors (2018), and elevation to IEEE Fellow (2024). He has chaired major conferences and served as Editor-in-Chief of IEEE Transactions on Visualization and Computer Graphics (2019-2022). He teaches graduate and undergraduate courses in visualization , medical imaging , and GPGPU programming , and leads the Visual Analytics Seminar (CSE 648). His lab ( VAI Lab ) fosters interdisciplinary research in GPU-accelerated analytics and ethical AI.

• Natural Language Processing
• Machine Learning
• Data Mining
• +۷ مورد دیگر

Pedro Henrique Luz de Araujo is a member of the Faculty of Computer Science affiliated with the Research Group Data Mining and Machine Learning . His work focuses on Natural Language Processing , Language Modeling , and Behavioral Learning , particularly in Brazilian legal text domains. He has contributed to advancements in named entity recognition , hate speech detection , and specification-driven AI systems . Active in 2022-2025 with publications in PLoS ONE and top NLP conferences Organized the KONVENS 2024 conference Research emphasizes LLM calibration , multimodal classification , and domain-specific datasets His recent publications show expertise in large language models (2025: persona effects; 2024: specification overfitting, text-guided image clustering), NER techniques (2024), and legal document processing (2023: multimodal classification; 2020: VICTOR dataset, LeNER-Br).

• Machine Learning
• System Architecture
• MLOps
• +۶ مورد دیگر

Stephen John Warnett is a researcher affiliated with the Faculty of Computer Science, specializing in Software Architecture. His work focuses on architectural design decisions for machine learning systems, particularly MLOps and RLOps frameworks. Research Interests: Primary areas include Machine Learning, System Architecture, and Reinforcement Learning. Key subtopics involve architectural design decisions, quality assessment, understandability, data integration, and deployment practices in cyber-physical systems. Publications Trends: Recent work emphasizes model-driven metrics for MLOps architectures, understandability in machine learning systems, and decision-making support for training strategies in reinforcement learning. Scientific Awards: Best Paper Award (2022)

• Natural language semantics
• Formal diachronic semantics
• Crosslinguistic variation
• +۲ مورد دیگر

Sigrid Beck serves as Professor of Theoretical and Descriptive English Linguistics at the University of Tübingen's Faculty of Philosophy since 2005, with prior appointments including Associate Professor at University of Connecticut and Junior Professor at Universität Potsdam. Her international engagements include Visiting Professorships at MIT and University of Canterbury. Educational background: PhD in Linguistics, Universität Tübingen (1997), "summa cum laude" (Dissertation: "Wh-constructions and transparent Logical Form") Habilitation, Johann-Wolfgang-Goethe-Universität Frankfurt (2003) (Thesis: "Pluralities and Comparisons") Masters in Linguistics with distinction, Eberhard-Karls-Universität Tübingen (1993) Beck's research pioneers formal approaches to meaning construction across languages, with signature contributions to: Theoretical frameworks for semantics-pragmatics interactions Diachronic evolution of semantic structures Crosslinguistic analysis of focus and presupposition Syntactic constraints on semantic interpretation Her methodology integrates formal theory with empirical cross-linguistic data to resolve foundational questions in meaning representation. Major recognitions: Academy of Europe membership (2022) Heinz-Maier-Leibnitz-Preis for doctoral work (1997) Oxford Visiting Fellowship at Magdalen College (2022) As principal investigator, Beck secured substantial DFG funding including the 12-year Collaborative Research Center SFB 833 'Construction of Meaning' (2009-2021) where she directed projects on crosslinguistic semantics and context reconstruction, plus XPRAG network leadership for experimental pragmatics research (2014-2020). Her grant portfolio demonstrates sustained leadership in coordinating large-scale interdisciplinary teams. She directs the 'Construction of Meaning' research consortium within the English Linguistics section, fostering collaboration between theoretical linguists, experimental researchers, and computational modelers to advance semantic theory through empirical validation.

Chen Chang-Wenمشاهده پروفایل

استاد

• Multimedia Signal Processing
• Multimedia Systems
• Image/Video Processing
• +۱ مورد دیگر

Chen Chang-Wen is a Chair Professor of Visual Computing at The Hong Kong Polytechnic University (2021–present). Previously, he was Empire Innovation Professor at the University at Buffalo (2008–2021) and held leadership roles including Dean of the School of Science and Engineering at CUHK Shenzhen (2017–2020). His research focuses on multimedia systems, signal processing, and communication. He is a Fellow of IEEE and SPIE, and has received numerous awards including the Alexander von Humboldt Research Award (2010) and the SUNY Chancellor's Award (2016). Chen has authored over 420 publications and holds three US patents. His work emphasizes interdisciplinary applications in visual computing, including contributions to autonomous systems, edge networks, and video quality assessment. He currently serves as Editor-in-Chief of IEEE Transactions on Systems, Man, and Cybernetics: Systems and leads initiatives in global university rankings and accreditation for engineering programs.

• Business Processes
• Blockchain Technology
• Semantic Technologies
• +۵ مورد دیگر

Assoc. Prof. Julius Köpke is an Associate Professor at the University of Klagenfurt's Department of Informatics Systems. His research focuses on business processes, blockchain technology, and semantic interoperability, with particular emphasis on smart contracts, artifact-centric processes, and interorganizational systems. He is affiliated with the Information and Communication Systems research group and contributes to the Institute for Computer Science Systems. Research Interests: - Interorganizational business processes with a focus on blockchain and smart contracts - Application of semantic technologies for data interoperability - Artifact-centric process modeling and data provenance Key Contributions: - Developed SecBPMN2BC framework for secure blockchain-based process modeling - Authored methods for aligning global and local processes, optimizing data-flow implementations - Pioneered lightweight XML-Schema annotation techniques for data translation Recent Work: - Explored LLM-based conversational process modeling tools - Investigated blockchain channel storage for business process data - Published extensively on time-aware processes and temporal constraints Labs/Teams: - Member of the Information and Communication Systems team - Active contributor to the Department of Informatics Systems' research initiatives

• Artificial Intelligence
• Data Scraping
• Textile Engineering
• +۳ مورد دیگر

Samuel Dieter Zühlke is a researcher affiliated with the Digital Media Lab at Hagenberg University of Applied Sciences. His work focuses on AI-based systems, textile engineering, and interactive technologies, particularly in sustainable fashion and sensor layout optimization. Key Collaborations: Projects involve partnerships with institutions in Austria, Germany, and beyond. Research Themes: Includes self-repairing web scraping architectures, textile-integrated sensors, and digital traceability frameworks for sustainable fashion. Methodologies: Leverages Large Language Models (LLMs), sensor design, and data pipeline maintenance techniques.

Matthias Janetschekمشاهده پروفایل

دانشیار

• Computer Science
• Cybersecurity
• Distributed Systems
• +۵ مورد دیگر

Matthias Janetschek holds the position of Associate Professor at the Management Center Innsbruck (MCI), Austria, since September 2020. Previously, he served as a Lecturer at MCI (2018–2020) and was a Co-Founder/Senior Developer at Felix Solution UG (2013–2015). He earned a PhD in Computer Science from the University of Innsbruck (2011–2019), alongside earlier degrees in Computer Science (BSc 2002–2007, MSc 2007–2011). His research focuses on distributed systems, workflow management, cybersecurity, and IoT , with notable contributions to scientific workflow execution on cloud/manycore architectures and AR/VR applications in education. He has supervised over 18 bachelor/master theses addressing topics like IoT security, reinforcement learning, and edge computing. Teaching responsibilities include courses such as Distributed Systems , Virtual Reality , and Computer Architecture at MCI. He has also completed further training in online education tools (e.g., Sakai, Adobe Connect) and corporate communication. His publications span journals like Multimodal Technologies and Interaction and conference proceedings on workflow systems, cloud computing, and AR usability. Current work emphasizes large-scale IoT security assessments and edge computing optimizations.