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Markus SchedlView profile

Professor

• Recommender Systems
• Information Retrieval
• Algorithmic Fairness
• +6 more

Markus Schedl is a Full Professor at Johannes Kepler University Linz , Austria, where he leads the Multimedia Mining and Search (MMS) group within the Institute of Computational Perception . He also heads the Human-centered Artificial Intelligence (HCAI) group at the Linz Institute of Technology (LIT) AI Lab . Education: Computer Science (TU Wien), PhD (JKU Linz), Master's in International Business Administration (WU Wien, University of Gothenburg) Research Interests span recommender systems , information retrieval , algorithmic fairness , user modeling , and machine learning . His recent publications focus on: Multimodal and hybrid AI for human-centric personalization Context-aware music recommendation and emotion recognition Graph neural networks for session-based recommendation Technical and regulatory compliance in fair, transparent, and privacy-preserving systems Projects are funded by the Austrian Science Fund (FWF) , Austrian Research Promotion Agency (FFG) , and European Commission (EC) . He maintains industry collaborations with Siemens, Spotify, and Deezer. Teaching includes courses like Introduction to Machine Learning and Social Media Mining and Analysis at JKU, with guest lecturing experiences at Pompeu Fabra, Queen Mary London, and KTH Stockholm. Labs & Teams: MMS group at JKU's Institute of Computational Perception and HCAI group at LIT AI Lab.

• Machine Learning
• Computer Vision
• Data Analytics
• +12 more

Michael Dittenbach is a researcher at TU Wien's Institute of Software Technology and Interactive Systems (E188). He contributes to interdisciplinary work combining machine learning, computer vision, and tourism informatics. His career spans over 15 years of publications in semantic web technologies, data analytics, and 3D virtual environments. Current research focuses on computer vision applications for cultural heritage, tourism recommender systems, and self-organizing map visualization Key projects include Media Square, SOIRE, and Web 3D environments Collaborates extensively with Helmut Berger, Andreas Rauber, and Robert Sablatnig His recent work (2022) explores computer vision techniques for digital library preservation, while earlier studies (2005-2015) focused on tourism informatics, data analytics frameworks, and semantic web applications. Publications demonstrate a consistent trajectory toward integrating machine learning with user-centric digital systems. As part of TU Wien's research infrastructure, he contributes to technical reports, conference proceedings, and multimedia system development without explicit mentions of scientific awards in available records.

• Human-Centered Computing
• Digital Thinking Pedagogy
• Crowdsourcing Mechanics
• +4 more

Lisa Posch, a Research Fellow at the Institute of Human-Centred Computing at Graz University of Technology, focuses on digital thinking pedagogy, crowdsourcing mechanics, and social media analytics. Her work bridges computational methods with sociotechnical systems. Education: Dipl.-Ing. (Master of Science), Dr.techn. (Doctorate in Technical Sciences), BSc Her research spans Human-Centered Computing , Natural Language Processing , and Digital Humanities , with publications on crowdworker motivation, social media monitoring, and metadata modeling. She has contributed to advancements in probabilistic ontology mapping and multilingual topic modeling. Her recent publications (2013-2023) demonstrate expertise in social media analytics , digital labor dynamics , and semantic data systems . She actively engages in educational initiatives through the Teaching Digital Thinking Project (TDT).

Milosh JovanovikjView profile

Associate Professor

• Knowledge Graphs
• Data Engineering
• Semantic Web
• +8 more

Dr. Milosh Jovanovikj holds the role of Associate Professor at the Faculty of Computer Science and Engineering in Skopje, North Macedonia, and concurrently serves as a PostDoc Researcher at TU Wien in Vienna, Austria. He is also a Senior R&D Knowledge Graphs Engineer at OpenLink Software in London. His primary research focuses on Knowledge Graphs (KGs), including their lifecycle processes such as modeling, enrichment, and analytics-driven AI applications. He has contributed to over 10 international and 25 national research projects, authored 60+ publications, and co-authored 3 books. His expertise spans Data Engineering, Semantic Web technologies, Linked Data, and Applied AI. Significant contributions include developing frameworks like RDFGraphGen for RDF graph generation and PharmKE for pharmaceutical text analysis. He has led initiatives in geospatial semantic web standards (GeoSPARQL) and healthcare informatics, including predictive analytics for nephrology data. Education: PhD in Computer Science and Engineering His work bridges academia and industry, with projects like the 3DFed federation engine and Semantic Sky (a Gmail plugin). He has extensive experience in ontology development (e.g., SEOntology, VEO for CO2 emissions) and open data initiatives, including LinkedDrugs for global drug data consolidation. Active in dissemination, his articles span knowledge graph applications in music recommendation, finance sentiment analysis, and drug-disease relation discovery. He has collaborated on benchmarks like the GeoSPARQL Compliance Benchmark and Mighty Storage Challenge (MOCHA). Grants/Projects: HOBBIT, SAGE, 3DFed, LinkedDrugs He leads teams in advancing semantic web integration, cloud service platforms (Semantic Sky), and educational materials like Web Programming Basics . His labs and teams focus on AI-driven solutions for healthcare, geospatial analytics, and enterprise systems.

Jürgen DornView profile

Associate Professor

• Business Process Management
• Knowledge & Competence Management
• Service Science
• +6 more

Jürgen Dorn is a retired Associate Professor at the Technische Universität Wien (TU Wien), affiliated with the Faculty of Informatics and the Institute of Information Systems. His career includes roles at the Christian Doppler Laboratory for Expert Systems and leadership of the Virtual Enterprises group at the E-Commerce Competence Center. He holds a PhD in knowledge-based real-time planning from TU Berlin (1989). Research focuses on Business Process Management, Knowledge & Competence Management, Service Science, E-Commerce, and Artificial Intelligence. Notable projects include the JIRA Process Mapper (2017-2018), ISIS Papyrus Process Mining System evaluation (2008), and development of the MOVE service composition framework. His work addresses trust in digital services, service classification, and tourism planning. Publications span trust models for e-markets, semantic web technologies, and scheduling systems. He advises numerous students on topics like case-based reasoning, digital badges, and service-oriented architectures. Awards section is currently empty. Grants and collaborations include projects with Catworkx GmbH and ISIS Information Systems GmbH. Active in teaching, including a 2025S Research Seminar for Ph.D. Students.

• Artificial Intelligence
• Machine Learning
• Healthcare Informatics
• +6 more

Oliver Krauss serves as an Assistant Professor at FH Upper Austria (University of Applied Sciences Upper Austria) at the Hagenberg Campus. He is affiliated with multiple research centers including the Research Center Hagenberg, Web Intelligence and Innovation Laboratory, AIST Assistive Technology Lab, Center of Excellence Medical Technology/TIMed Center, Center of Excellence for Smart Production, and Digital Media Lab. His work falls under the Strength area ICT - Information & Communication Technology with additional connections to HEAL initiatives. Dr. Krauss's research spans several interconnected domains with a strong focus on practical applications of artificial intelligence. His primary research interests include Healthcare Informatics (particularly HL7 FHIR standards), Language Models and Natural Language Processing, Web Intelligence for user behavior analysis, Assistive Technology applications, and Process Mining for business optimization. His work demonstrates consistent interdisciplinary connections between computer science fundamentals and real-world healthcare and business applications. Analysis of Krauss's recent publications (2023-2025) reveals a clear trajectory toward increasingly sophisticated AI applications. His research has evolved from foundational IoT and sensor data processing toward advanced language model applications in healthcare informatics, e-commerce personalization, and fact-checking systems. A notable pattern is his ability to bridge theoretical AI concepts with practical implementations in medical technology and business intelligence, often incorporating emerging technologies like GPT-3 and other large language models into domain-specific solutions. Dr. Krauss has received significant recognition for his work, including: FH Upper Austria Young Researcher Award (2019 and 2022) HL7 Austria Student Award for Master's Thesis (2015) Best Paper Award at Intelligent Systems and Applications 2022 His research activities include substantial project leadership and collaboration, with notable projects including MARIE (Mobile Robotic Assistance for Office Environments), CRISAM® Loop (AI-based risk management), and EDEN (Emergency Detection for Elevator Networks). He has maintained consistent publication output with 74 publications to date and has been active in scientific communities through conference participation, invited lectures (including on HL7 FHIR topics), and committee work. His h-index of 6 reflects a solid research impact with 110 citations. Dr. Krauss leads research within multiple specialized laboratories including the Web Intelligence and Innovation Laboratory where he applies language models to website visitor segmentation, the AIST Assistive Technology Lab focusing on healthcare applications, and contributes to the Center of Excellence Medical Technology/TIMed Center where his work on patient medical records analysis has significant clinical implications.

• Information Retrieval
• Knowledge Graphs
• Natural Language Processing
• +5 more

Florina Piroi is a Senior Scientist (Research Fellow) at the Center for Research Data Management (E058-06) within the Faculty of Informatics at TU Wien. Her research integrates information retrieval, knowledge graphs, and semantic technologies to advance exploratory search systems and research data infrastructure. Her core research interests include: Information Retrieval evaluation and validation methodologies Knowledge graph applications for domain-specific search Patent text mining and semantic technologies Medical concept normalization and entity linking Argumentative zoning in scientific documents Table extraction and classification systems Analysis of her recent publications reveals strong trends in applying machine learning to specialized IR tasks, particularly in patent analysis and medical text processing. Her work emphasizes robust evaluation frameworks and cross-lingual capabilities, with consistent contributions to the CLEF campaign and PatentSemTech workshops. Dr. Piroi actively collaborates with international researchers through the Network Lab at TU Wien and contributes to the university's Center for Research Data Management, focusing on semantic technologies for research data infrastructure and scholarly communication systems.

• Information Retrieval
• Data Mining
• Text Classification
• +5 more

Allan Hanbury is a Full Professor for Data Intelligence and Head of the Data Science Research Unit at the Faculty of Informatics, TU Wien, Austria. He serves as Faculty Representative responsible for financial affairs and internationalization within the faculty. He is also a faculty member at the Complexity Science Hub Vienna. Roles: Faculty Representative (financial/internationalization), Data Science Research Unit Head Key Projects: Coordinator of EU-funded Khresmoi (medical search), DoSSIER (Marie Curie ITN training network), VISCERAL (big data evaluation), KConnect (medical text analysis) Spin-off: Co-founder of contextflow (radiology image search) Research focuses on information systems engineering and visual computing, with emphasis on: Information retrieval, data mining, text classification Medical data intelligence, health informatics Domain-specific systems for information extraction/retrieval Publications span over 180 refereed works, with recent contributions on LLMs in query generation, clinical trial matching, and systematic review automation. His work bridges academic research with industry applications in healthcare, legal text analysis, and patent mining. Grants include EU Horizon projects (e.g., DoSSIER, BRISE-Vienna), FFG-funded innovation initiatives, and collaborations with organizations like Siemens, Deutsche Telekom, and the Austrian Ministry of Finance.

• Selective Sampling
• Text Classification and Web Mining
• Data Mining in the Social Sciences
• +6 more

Johannes Fürnkranz serves as a Professor at the Faculty of Informatics, TU Wien, affiliated with the Distributed Systems research group (Institute E194-02). His institutional presence is evidenced by current contact details and recent scholarly output. His research spans critical machine learning domains including Selective Sampling, Text Classification and Web Mining, Data Mining in the Social Sciences, Inductive Logic Programming, and Noise Handling. Specialized interests cover Machine Learning in Game Playing, Pairwise Classification and Preference Learning, alongside Meta-Learning and Ensemble Classifiers, reflecting both theoretical depth and applied versatility in artificial intelligence. Current publication trends indicate active work in change point detection for heterogeneous data systems, combining predictive modeling with anomaly detection in time series. This aligns with broader themes in statistical learning and non-parametric methods for complex data structures. No scientific awards were documented in the source material. Advising activities and research funding details remain unspecified in available information. Laboratory affiliations center on the Distributed Systems group within TU Wien's Faculty of Informatics infrastructure.

Elia AnnibaleView profile

Professor

• Computational Linguistics
• Theoretical Linguistics
• Applied Linguistics
• +4 more

Elia Annibale is a Full Professor of Computational Linguistics at the University of Salerno, Italy, holding positions since 1987. He leads the Department of Political, Social and Communication Sciences and previously directed the Department of Communication Sciences. His academic journey includes a PhD in Computational Linguistics from Paris 7 University (1979) and earlier roles at the University of Paris and the University of Southern California. Research focuses on computational linguistics, machine translation, and semantic web technologies. Notable projects include the ESPRIT MULTILEX and GENELEX EU initiatives, developing multilingual linguistic resources. Awards include Academia Europaea membership (1989) and leadership in PRIN research units. Education: PhD in Computational Linguistics, University of Paris VII (1979) Laurea in Modern Literature, University of Naples (1972) Publications span theoretical linguistics, applied computational linguistics, and semantic analysis. Current projects include a semantic web search engine and lexical resource development for e-government.