جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Natural Language Processing
• Education Technology
• +۳ مورد دیگر

Jieun Han is a researcher with a focus on interdisciplinary research spanning natural language processing, education technology, healthcare informatics, and wireless communications. Her work often integrates AI tools like ChatGPT into educational settings and explores applications of robotics and UAV systems in healthcare and communication. Co-authored publications indicate collaboration with institutions in South Korea and international partners. Research interests include AI-driven education systems (e.g., EFL writing support), multimodal safety testing for vision-language models, and task planning with large language models. Technical contributions include UAV-based localization systems, VR environments for cognitive assessment, and provenance compression for large datasets. Recent publications (2023-2025) highlight innovations in automated essay scoring, chatbot integration in language learning, and beamforming algorithms for 3D sidelobe suppression. Collaborations span computer science, electrical engineering, and health informatics domains.

Doulkeridis Christosمشاهده پروفایل

استاد

• Big Data
• Data Management in Cloud Computing
• Query Processing
• +۵ مورد دیگر

Christos Doulkeridis is a Professor at the Department of Digital Systems, University of Piraeus. Specializing in big data management, distributed systems, and mobility analytics, he has led projects such as CHOROLOGOS (ELIDEK-funded) and contributed to EU initiatives like datAcron and Track&Know. He holds Marie-Curie and ERCIM fellowships, and his work emphasizes energy-efficient data architectures and semantic trajectory analysis. Education: PhD in Informatics, Athens University of Economics and Business (2007) MSc in Informatics, Athens University of Economics and Business (2003) Diploma in Electrical & Computer Engineering, National Technical University of Athens (2001) Research Interests: Big data analytics, cloud computing, spatiotemporal query processing, mobility forecasting (e.g., traffic patterns, maritime monitoring), and semantic trajectory modeling. His work bridges theory with practical applications in smart cities and environmental sustainability. Awards: Winner of SemEval’17 Task4 (sentiment analysis) Best Paper Award at EuroVA’19 Michalis Dertouzos Award (2004) for Human Face of Computing Grants & Projects: Principal Investigator for CHOROLOGOS (semantic spatiotemporal data) Core contributor to datAcron (maritime data ontology) European projects: BigDataStack, RoadRunner (ARISTEIA II) Labs & Teams: Leads research teams developing frameworks like SPARTAN (semantic integration) and ARGO (trajectory prediction). Collaborates on open-source tools like ST_VISIONS (spatiotemporal visualization) and NoDA (unified NoSQL access).

Tamer Özsuمشاهده پروفایل

استاد

• Distributed Data Management
• Graph Databases
• RDF Systems
• +۲ مورد دیگر

Tamer Özsu is a University Professor at the David R. Cheriton School of Computer Science, University of Waterloo, where he previously served as Director (2007-2010) and currently holds the role of Associate Dean of Research. He is also a Distinguished Visiting Professor at Tsinghua University. Professor Özsu's research spans distributed data management, graph/RDF systems, and database fundamentals. His current work focuses on: Distributed graph processing algorithms SPARQL query optimization for RDF systems Streaming graph analytics Indexing techniques for modern hardware Distributed database architectures He has authored the seminal textbook Principles of Distributed Database Systems and co-edited the Encyclopedia of Database Systems . As founding Editor-in-Chief of ACM Books, he has shaped computing literature. His recent publications demonstrate continued innovation in graph partitioning, streaming graph algorithms, and scalable RDF processing. Özsu maintains active research leadership in database systems with over 30 years of influential contributions.

• Graph Data Management
• RDF and Semantic Web
• Database Theory
• +۳ مورد دیگر

Maxime Jakubowski is a PostDoc Researcher at TU Wien's Faculty of Informatics, affiliated with the Databases and Artificial Intelligence research group. Based in Room HA0320 at Favoritenstrasse 9, he can be contacted at maxime.jakubowski@tuwien.ac.at and maintains an ORCID profile (0000-0002-7420-1337). His research centers on graph data management within the Semantic Web ecosystem, specializing in RDF validation through shape constraint languages like SHACL and ShEx. He investigates formal foundations, expressiveness boundaries, and practical implementations including SQL compilation and neighborhood-based graph description. Current projects include FRESH (2021–2026), KtoAPP (2018–2025), and TARGET (2024–2028), focusing on graph data theory and implementation. Recent publications (2021–2025) demonstrate consistent contributions to RDF validation standards, with 14 articles addressing shape language formalization, compilation techniques, and provenance tracking. His work bridges theoretical database concepts with industrial applications in knowledge graph validation. Dr. Jakubowski supervises bachelor theses and teaches courses including Management of Graph Data (192.161) and Project in Computer Science. His research collaborations span international projects and the Dagstuhl Seminar 24102 on Shapes in Graph Data. He is an active member of the Databases and Artificial Intelligence research group, contributing to TU Wien's leadership in graph data management and Semantic Web technologies through both theoretical research and practical tool development.

• Statistical Machine Learning
• Exploratory Data Analysis
• Data Science
• +۴ مورد دیگر

Jaakko Peltonen is a Professor of Statistics and Data Analysis at Tampere University, Faculty of Information Technology and Communication Sciences, Department of Computing Sciences. He leads the Statistical Machine Learning and Exploratory Data Analysis (SMiLE) research group and is affiliated with the Tampere Research Center in Information and Systems and the Academy of Finland Center of Excellence in Game Culture Studies. His research focuses on statistical machine learning, exploratory data analysis, and their applications in diverse domains including healthcare, social media analytics, gaming, and political discourse analysis. Notable projects include developing algorithms for transparent AI systems (e.g., TraQuLA, Flow of Trust framework) and analyzing online communities through platforms like Twitch and Steam. Recent work emphasizes ethical AI integration in education and healthcare, predictive modeling for emergency department management, and game studies involving player behavior analysis. Peltonen collaborates across disciplines, leveraging text mining, graph theory, and visualization techniques to address complex societal challenges. Key contributions span methodological advancements (e.g., constrained non-negative matrix factorization) and interdisciplinary applications in policy analysis, digital humanities, and health informatics. His work bridges technical innovation with real-world societal impact through collaborative research initiatives.

Raúl García-Castroمشاهده پروفایل

دانشیار

• Semantic Technologies
• Ontological Engineering
• Knowledge Graphs
• +۳ مورد دیگر

Raúl García-Castro is an Associate Professor at the Computer Science School of Universidad Politécnica de Madrid (UPM) , Spain. He works in the Ontology Engineering Group , focusing on semantic technologies, ontological engineering, and interoperability. His roles include Principal Investigator in EU projects like AURORAL , COGITO , and OntoCommons , and contributor to ETSI and W3C standards. Education : Ph.D. in Computer Science and Artificial Intelligence (UPM, 2008), M.Sc. in Computer Science (UPM, 2003). Research Interests center on benchmarking semantic technologies, ontological modeling, knowledge graph lifecycle, and semantic interoperability in IoT and blockchain. Recent work includes frameworks like LOT for industrial ontologies and WoTHive for Web of Things discovery. He has contributed to the SSN Ontology (W3C/OGC standard) and SAREF family of ontologies (ETSI standards). Scientific Awards include the UPM Extraordinary PhD Award (2008-2009) 3rd Best Paper Award at SEKE 2012 Grants include an FPI grant (BES-2005-8024) from Spain’s Ministry of Education. He has led projects like VICINITY (H2020-688467) and DELTA (H2020-773960), and participated in NeOn (FP6-027595) and Knowledge Web (FP6-507482). Leadership includes organizing conferences like SEKE 2021 (Chair), ESWC 2016 (Track Chair), and SEKE 2012 (Publicity Chair).

Oscar Corchoمشاهده پروفایل

استاد

• Semantic Web
• Linked Data
• Ontological Engineering
• +۳ مورد دیگر

Oscar Corcho is a Full Professor at Universidad Politécnica de Madrid (UPM) and co-leads the Ontology Engineering Group (OEG). He holds a BSc, MSc, and PhD in Computer Science from UPM. His research focuses on Semantic Web technologies, Linked Data, and Ontological Engineering, with applied work in e-Science and Open Science. He has coordinated major EU projects like STARS4ALL, MobileAge, and CLARITY, and led national initiatives such as Ciudad2020 and myBigData. Corcho’s academic background includes over 100 publications, including the textbook Ontological Engineering , and an h-index of 40+. He has supervised 16 PhD theses and serves on editorial boards of journals like Semantic Web and Journal of Web Semantics . His awards include the 2016 Juan López de Peñalver Award and the Semantic Web Challenge 2015. Research leadership roles include co-directing OEG and coordinating Marie Curie actions (SemData, KOPAR). His projects span innovation in public transport (TransformingTransport), elderly digital inclusion (MobileAge), and open government data (LocaliData). He actively promotes citizen science through projects like STARS4ALL to combat light pollution. Education: BSc in Computer Science (UPM, 2000) MSc in Software Engineering (UPM, 2001) PhD in Computer Science and AI (UPM, 2004) Awards: Highlighted awards including Royal Academy of Engineering recognition and EU innovation prizes Labs/Teams: Ontology Engineering Group (OEG), STARS4ALL consortium, SlideWiki collaborative learning platform

Víctor Rodríguez Doncelمشاهده پروفایل

دانشیار

• Semantic Web
• Digital Rights Management
• Ontology Engineering
• +۳ مورد دیگر

Víctor Rodríguez Doncel is an Associate Professor at the Universidad Politécnica de Madrid (UPM) , affiliated with the Ontology Engineering Group (OEG) within the Department of Artificial Intelligence at the Faculty of Computer Science. His research focuses on semantic representation of intellectual property, licenses, and contracts, contributing to standards like ISO/IEC 21000-19 and W3C ODRL. He holds a PhD (2010) and has industry experience at GMV Sistemas and academic collaborations in Europe. Education : PhD in 2010 from UPM His research interests include ontology engineering for media value chains, semantic web technologies, and conditional access systems for linked data. He maintains an RDF license dataset and services for rights-based data access. Publications span 8 journal papers and over 20 conference contributions, focusing on semantic web applications, DRM systems, and multimedia standards. European Projects : SUPERHUB (FP7), AXMEDIS (FP6), VISNET II (FP6) Spanish Projects : INNPRONTA, AVANZA2, CENIT Segura He has taught for 6 years, authored two books, and holds a patent. His work bridges academia-industry through standards development and practical implementations.

Long Chengمشاهده پروفایل

پژوهشگر

• Cloud Computing
• Big Data Analytics
• Parallel and Distributed Systems
• +۳ مورد دیگر

Dr. Long Cheng was a former Researcher at the International Center for Computational Logic (ICCL) within the Faculty of Computer Science at TU Dresden. His research focused on cloud computing, big data analytics, and distributed systems, particularly in optimizing large-scale data processing, outer join operations, and semantic web technologies. He contributed to projects involving parallel programming models like X10, MapReduce frameworks, and efficient data compression techniques for RDF datasets. Cheng collaborated with the Knowledge-Based Systems research group, addressing challenges in scalable systems, high-throughput indexing, and parallel reasoning under non-monotonic logics. His work emphasized performance optimization in distributed environments, including skew handling, data redistribution strategies, and algorithm scalability for large datasets. Publications span topics such as outer join evaluation in cloud environments, efficient compression of semantic web data, and high-performance query execution over distributed systems. His research bridges theoretical computational logic with practical applications in big data and cloud infrastructure.

Konstantinos Stefanidisمشاهده پروفایل

استاد

• Data Science
• Big Data Management
• Recommender Systems
• +۵ مورد دیگر

Professor Konstantinos Stefanidis holds a full professorship in Data Science at Tampere University's Faculty of Information Technology and Communication Sciences (ITC). He leads the Data Science Research Centre and Recommender Systems Research Group, focusing on advancing fairness and transparency in AI-driven systems. His work bridges computational techniques with societal impact, emphasizing ethical considerations in big data analytics. Education: PhD in Computer Science (2009) from University of Ioannina, Greece Postdoctoral research at institutions including Hong Kong, Norway, and Greece Research Interests: His primary areas include: Recommender Systems with fairness guarantees Entity Resolution in big data Algorithmic transparency and ethical AI Sequential group recommendations Health informatics applications He has published over 100 papers in top-tier venues like ICDE, EDBT, and VLDB. Recent Contributions: Recent work emphasizes: Counterfactual explanations for group recommendations Fairness-aware entity resolution Health domain recommendations Explainable AI frameworks Awards & Recognition: Best Paper Awards at ACM SAC (2022), PIC (2021), and QAUCA (2019) Recipient of Academy Research Fellowships General co-chair for major conferences (EDBT/ICDT 2026, ADBIS 2025) Advising & Collaboration: Mentors over 10 PhD/MSc students. Active in international collaborations including EU-funded projects. Leads research teams addressing global challenges like sustainable AI and healthcare innovation. Labs & Teams: Coordinates the Recommender Systems Group and Data Science Subunit at Tampere. Collaborates with industry partners and academic institutions globally to advance socially responsible technologies.

Pablo Martinez Rodriguezمشاهده پروفایل

استادیار

• Industrialized Construction
• Robotics and Automation
• Computer-aided Process Planning
• +۴ مورد دیگر

Dr. Pablo Martinez Rodriguez is an Assistant Professor at Northumbria University's Architecture and Built Environment Department. He specializes in multi-disciplinary engineering, focusing on Industry 4.0 integration in low-digitalized sectors like construction and agriculture. His research emphasizes industrialized construction, robotics automation, lean manufacturing, and precision farming. Education: BEng in Electromechanical Engineering (Comillas Pontifical University), MSc in Mechanical Engineering (University of Alberta), and PhD in Civil and Environmental Engineering (University of Alberta). Previously held roles include NSERC post-doctoral fellow and International Visiting Professor at Tecnologico de Monterrey. Research Interests: Industrialized Construction (Modern Methods of Construction), Robotics & Automation, Computer-aided Process Planning, Lean Manufacturing, Waste Management, and Precision Farming Automation. His work addresses challenges in smart safety systems, digital twins, and sustainable construction practices. Key Projects: Developed an IALF-certified learning factory, created ontology-based safety management tools, and advanced aquaponics 4.0 systems. Recent articles highlight digital twin applications, gamified safety training, and AI-driven generative design. Grants & Collaboration: Active in organizing international conferences like the Modular and Offsite Construction Summit. Supervises PhD students and collaborates on projects aligning with UN Sustainable Development Goals, particularly education and sustainable cities. Labs/Teams: Leads the AllFactory transdisciplinary educational facility focusing on aquaponics 4.0 and smart manufacturing systems. Engages in cyber-physical systems research for zero-defect production.

Go Sugimotoمشاهده پروفایل

پژوهشگر ارشد

• Linked Data
• Entity Linking
• Data Integration
• +۴ مورد دیگر

Go Sugimoto holds multiple Visiting Fellow positions at Vrije Universiteit Amsterdam across key research units: Faculty of Science Business Web and Media Network Institute Intelligent Information Systems His research bridges Computer Science and Digital Humanities with emphases on: Quality assessment of Linked Data infrastructure Entity Linking for cultural heritage applications Data Integration challenges in historical research NLP-driven RDF generation from biographical texts FAIR principles implementation barriers Publication analysis reveals consistent focus on empirical evaluation of semantic web tools for humanities contexts, particularly examining data connectivity gaps in cultural heritage systems. His work demonstrates methodical investigation of real-world tool limitations while advancing practical integration frameworks for heterogeneous historical datasets. No major scientific awards are documented in available records. Information regarding student advising or research grant management is not disclosed in current profiles. Sugimoto operates within VU Amsterdam's Network Institute and Intelligent Information Systems ecosystem, leveraging interdisciplinary collaboration between computer science and humanities scholars to address data infrastructure challenges in cultural heritage domains.

• Stream Reasoning
• Semantic Web
• Knowledge Graphs
• +۴ مورد دیگر

Pieter Bonte serves as an Assistant Professor (tenure track) in the Department of Computer Science at KU Leuven's Faculty of Engineering Science, based at the Kulak Kortrijk Campus. He holds dual institutional affiliations as a core member of Leuven.AI - KU Leuven Institute for Artificial Intelligence and participates in academic governance through the Council of the Faculty of Engineering Science, Computer Science Department Council, and Science, Engineering and Technology Group Council at Campus Kulak Kortrijk. His research program centers on Stream Reasoning and Semantic Web technologies, with specialized expertise in Knowledge Graph embeddings , neurosymbolic reasoning , and edge analytics for IoT data streams . Current investigations focus on resource-optimized stream processing, cross-context learning architectures, and ontological frameworks for heterogeneous streaming data. His work bridges theoretical foundations with healthcare and communications network applications, emphasizing practical deployment in distributed environments. Recent publications (2023-2025) reveal dominant themes in RDF stream processing systems, benchmarking methodologies for knowledge graph embeddings, and ontology engineering for streaming linked data. His output consistently targets high-impact venues including VLDB Journal, Semantic Web journal, and DEBS conference, demonstrating leadership in stream reasoning standardization through comprehensive surveys and vision papers. The research trajectory shows increasing integration of symbolic AI with neural approaches for edge-constrained environments. As principal investigator, Bonte leads three major funded projects through 2028: Stream Reasoning for efficient Edge Processing , Neurosymbolic Stream Reasoning , and Edge analytics of heterogeneous IoT data streams . His teaching portfolio includes core computer science courses in Operating Systems (X0A48A), Declarative Languages (X0C99A), Computer Systems Organization (X0E31A), and Scientific Training (X0D49A), reflecting his commitment to foundational and emerging topics in data-intensive systems. Bonte's research group operates within KU Leuven's Leuven.AI ecosystem and Kulak campus infrastructure, maintaining extensive international collaborations evident in multi-institutional publications. The team specializes in developing semantic stream processing frameworks for real-world applications in healthcare monitoring and communications networks, with active partnerships across European research institutions.

Raymond Wongمشاهده پروفایل

دانشیار

• Database Systems
• Data Science/Analytics
• Information Extraction
• +۵ مورد دیگر

Associate Professor Raymond Wong is a faculty member in the School of Computer Science & Engineering at UNSW Sydney, where he also serves as Director of Online Education. He holds a PhD from Hong Kong University of Science & Technology, and has extensive expertise in database systems, data science, information extraction, and cloud computing. With over 220 conference papers, 56 journal articles, and two US patents, his research spans data mining, machine learning, and big data analytics. He has received 8 best paper awards and 4 industry/professional recognitions. His advisory roles include stints at Data61/CSIRO and Stats Central, and he has co-founded technology startups. Key projects include the Singapore NTU SPIRIT Smart Nation Research Centre's Intelligent Case Retrieval System (ICRS) and collaborations across Asia-Pacific regions. His research interests focus on database optimization, data analytics, NLP, and cloud infrastructure. He has supervised 25 PhD students and 65 honors students, six of whom earned University Medals. Notable grants include projects on ovarian cancer detection ($135k), cardiovascular disease analysis ($100k), and social media analytics ($250k). Awards include the 2016 ARC UNSW Supervisor Award and multiple IEEE best paper honors. His work bridges academia and industry, addressing challenges in healthcare, cybersecurity, and data-driven innovation.

• Dataspaces
• Semantic Web Technologies
• Ontologies
• +۶ مورد دیگر

Johannes Theissen-Lipp is a senior scientific researcher at the Fraunhofer FIT Office Aachen with significant academic affiliations at RWTH Aachen University. He operates within the Department of Computer Science (Informatik 5) under the Faculty of Mathematics, Computer Science and Natural Sciences, working from the Databases and Information Systems (DBIS) group led by Professor Stefan Decker. His research focuses on semantic foundations of dataspaces with practical applications in manufacturing and mobility sectors. He earned his Computer Science degree from RWTH Aachen University, where he later conducted research at the Institute for Information Management in Mechanical Engineering (IMA) for nearly two years before joining the "Knowledge Pipelines" research group in December 2019. He successfully defended his PhD thesis titled "Semantic Foundations of Dataspaces" on September 25, 2024, completing his doctoral studies at RWTH Aachen. Theissen-Lipp's research spans semantic web technologies, ontologies, and data interoperability with particular expertise in RDF validation (SHACL), semantic mappings (RML), and FAIR data implementation within dataspaces. His work bridges theoretical foundations with industrial applications, especially in manufacturing contexts where data integration across organizational boundaries presents significant challenges. He has pioneered approaches for enhancing dataspaces through large language models and developing scalable validation techniques for distributed data environments. His publication record demonstrates consistent contributions to major semantic web venues including ESWC, SEMANTiCS, and dedicated workshops on dataspaces. As both author and editor (notably for the Second International Workshop on Semantics in Dataspaces proceedings), he has helped shape research directions in this emerging field. His recent work increasingly explores the intersection of traditional semantic technologies with contemporary AI approaches. Theissen-Lipp actively supervises multiple thesis projects including "FAIRification of Data Models in Manufacturing," "Leveraging Solid Pods for Sovereign Data Sharing in the Cultural Sector," and "Identification Techniques for Data-driven Feedback Loops in Manufacturing." He has taught the "Dataspaces Proseminar" in the summer semester of 2025, demonstrating his commitment to academic education alongside his research activities. As part of the Cluster of Excellence Internet of Production, he contributes to advancing data interoperability in industrial contexts. His professional presence extends to GitHub (JohannesLipp), LinkedIn, and ResearchGate, with a personal website providing additional details about his research portfolio and professional activities.