Find Academic Supervisors

• Information Systems
• Artificial Intelligence
• Data Visualization
• +4 more

Peter McBrien is an Associate Professor in the Department of Computing at Imperial College London, affiliated with the Faculty of Engineering. He holds dual affiliations with the Distributed Software Engineering group. His research focuses on conceptual modeling, ontology engineering, database systems, and temporal data management. He has been active in advancing techniques for data visualization, semantic web technologies, and relational database integration. Key research areas include: Ontology extraction from relational databases Type inference in transactional systems Schema transformation between heterogeneous models Peer-to-peer data integration protocols Temporal database systems His publication trends emphasize integration of heterogeneous data sources through formal methods, with notable contributions to OWL ontology implementation, hypergraph data models, and benchmarking big data query languages. Recent work focuses on Spark-based semantic reasoning and distributed knowledge exchange systems. Peter McBrien's research has been supported through Imperial College's infrastructure, with ongoing contributions to the AutoMed data integration framework and RoDEx protocols for unreliable networks. His work bridges theoretical foundations of data management with practical implementations in distributed systems.

Jeff HeflinView profile

Associate Professor

• Semantic Web
• Ontology Development
• Artificial Intelligence
• +3 more

Jeff Heflin is an Associate Professor in the Department of Computer Science and Engineering at Lehigh University, and Director of the Cognitive Science Program. He holds a PhD from the University of Maryland, College Park, and a B.S. from The College of William and Mary. His research focuses on AI for Data Management, Scalable Reasoning, and Data Exploration, with significant contributions to Semantic Web technologies like SHOE, DAML+OIL, and OWL. Education: Ph.D. in Computer Science, University of Maryland, 2001 M.S. in Computer Science, University of Maryland, 1999 B.S. in Computer Science, The College of William and Mary, 1992 Research Interests: Heflin’s work advances Semantic Web infrastructure, including ontology development, scalable reasoning systems, and data integration. His contributions include foundational benchmarks like LUBM and innovations in entity matching (DAME), table search (StruBERT), and neural-augmented logical reasoning. Awards: Winner of the Billion Triple Challenge (ISWC 2012) Best Paper Award, ISWC 2004 Ruth and Joel Spira Award for Excellence in Teaching (2017) Service & Leadership: Served as Vice-President of the Semantic Web Science Association (SWSA), Editorial Board member of the Artificial Intelligence Journal , and General Chair of ISWC 2017. Active in conference organization (CIKM 2020, COLING 2022) and journal special issues on Semantic Web evaluation. Labs & Collaborations: Leads the Semantic Web and Agent Technologies (SWAT) Lab at Lehigh, focusing on AI-driven data management and scalable reasoning systems. Collaborates on NSF-funded projects like CRISPS (cell-centric image similarity search) and Domain-Agnostic Dataset Search.

• Conceptual Modeling
• Ontology
• Domain Modeling
• +7 more

Tiago Prince Sales is an Assistant Professor in the field of Semantics, Cybersecurity & Services, actively contributing to foundational research in conceptual modeling, ontology, and information systems. His work bridges formal methods with practical applications in digital platforms, cybersecurity, and knowledge representation. Assistant Professor, Semantics, Cybersecurity & Services Active in international research communities (FOIS, ER, BPMDS, RCIS) Key focus: Ontology, Domain Modeling, Interoperability, Digital Platforms Recognized with multiple best paper awards His research centers on the development and application of formal conceptual models using frameworks such as OntoUML and the Unified Foundational Ontology (UFO). He investigates how domain models can enhance system design, improve interoperability, and support risk analysis in complex information systems. His work often integrates empirical insights with theoretical rigor, aiming to address real-world challenges in modeling. The recent publications highlight a strong trend toward ontological engineering in cybersecurity (e.g., phishing attack modeling), digital platform taxonomy, and FAIR data planning. These works demonstrate a consistent focus on creating reusable, semantically rich models that support both human understanding and machine processing across domains. The integration of modeling with data science and security indicates a forward-looking research agenda. Best paper award at FOIS 2023 Best paper award at ER 2022 EMMSAD 2025 Best paper award Tiago Prince Sales actively mentors and collaborates with researchers, though no formal students are listed. He has secured recognition through competitive awards and leads significant research outputs, including datasets and open models. His involvement in organizing top-tier conferences such as FOIS 2024 reflects leadership in the academic community. While specific grants are not listed, his productivity suggests external funding support. He contributes to open science through Zenodo-hosted datasets like the OntoUML Vocabulary and GO-Plan method, and participates in collaborative teams focused on knowledge graphs, FAIRification, and model-driven engineering. His role in organizing the FOIS 2024 conference underscores his integration within leading research networks in formal ontology and conceptual modeling.

Juan F. SequedaView profile

Researcher

• Knowledge Graphs
• Semantic Web
• Databases
• +4 more

Juan F. Sequeda is the Principal Scientist and Head of the AI Lab at data.world, with a PhD in Computer Science from the University of Texas at Austin. He co-founded Capsenta, a spin-off from his research on semantic data virtualization. His work bridges academia and industry through roles in the Property Graph Schema Working Group, LDBC Graph Query Languages task force, and W3C standards editing. Education : PhD in Computer Science (2015) from University of Texas at Austin His research focuses on Knowledge Graphs, Semantic Web, and Ontology-Based Data Integration. He develops technologies for graph data management and semantic query processing, with applications in constitutional data analysis (Constitute.org) and enterprise data virtualization (Ultrawrap, Gra.fo, G-CORE). Recent publications analyze composable graph query languages (G-CORE, 2018) and optimize SPARQL execution on relational data (Ultrawrap, 2013). Awards include NSF Graduate Fellowship (2010-2013), ISWC2014 Best Student Paper, and 2015 Institute for Applied Informatics Best Transfer Project. Scientific Awards : NSF Graduate Research Fellowship (2010-2013) 2nd Place, 2013 Semantic Web Challenge Best Student Research Paper, ISWC2014 2015 Best Transfer and Innovation Project (Institute for Applied Informatics) UT Graduate Diversity Fellowship (2008-2009) National Instruments Scholarship (2007-2008) Intel Foundation Fellowship (2007) He actively contributes to program committees (ISWC, ESWC, WWW) and workshop organization (COLD, AMW2018 General Chair). Contact: juan@data.world (work), juanfederico@gmail.com (personal).

• Computational Logic
• Knowledge Representation
• Artificial Intelligence
• +5 more

Professor Kewen Wang is a faculty member in the School of Information and Communication Technology at Griffith University , where he has been actively working in computational logic, knowledge representation, and their applications in artificial intelligence for over 30 years. His research has led to the development of novel logics, computer languages, and systems for knowledge representation and reasoning. Broad research areas: Computational Logic, Knowledge Representation, Artificial Intelligence, Programming, Knowledge Graphs, Explainable AI, Ontology Reasoning, Rule Learning Key contributions: RLvLR (scalable rule learner for KGs), TyRuLe (typed rule learning), Drewer (Datalog+- query engine), ALBERT+CCR (CommonsenseQA model), auction design algorithms His research has been widely cited in top venues like Artificial Intelligence , JAIR , ACM Transactions on Computational Logic , and conferences AAAI (Area Chair 2022-2025), IJCAI , KR . He has secured six ARC Grants (five Discovery, one Linkage) and smaller grants from NICTA, CSIRO, and Griffith University. Editorial roles: Area Chair for AAAI (2022-2025), Associate Editor for Journal of Web Semantics , TGDK Supervision: Has supervised over 15 PhD students including Hong Wu, Peng Xiao, and Pouya Omran Teaching: Courses in Intelligent Systems, Data Structures, Discrete Mathematics, and Robotics

Sebastián FerradaView profile

Assistant Professor

• Knowledge Graphs
• Graph Databases
• Multimedia Databases
• +3 more

Sebastián Ferrada is an Assistant Professor at the Data & Artificial Intelligence Initiative of Universidad de Chile. He also serves as Young Researcher at the Institute for Foundational Research on Data (IMFD) and Collaborating Researcher at the National Center for Artificial Intelligence Research (CENIA). His research focuses on Knowledge Graphs, with special emphasis on extraction, management, and applications for querying, browsing, and AI systems. His academic background includes: PhD in Computer Science (2021), Universidad de Chile MSc in Computer Science (2017), Universidad de Chile BEng in Computer Science (2017), Universidad de Chile Sebastián's research explores several key areas: Multimedia Databases with applications to Wikimedia Commons images Graph Databases and Knowledge Graphs construction Federated Data Management across heterogeneous RDF sources SPARQL query extensions for similarity-based operations Graph data management and compression techniques His recent publications demonstrate strong trends in knowledge graph construction, similarity-based querying, and efficient graph data management. These works combine theoretical advancements with practical implementations in real-world systems like IMGpedia and MillenniumDB. Scientific achievements include: Best Paper Award at CoopIS 2023 Best Demonstration Award runner-up at SIGMOD/PODS 2024 Best Student Paper (Resources Track) and Best Poster at ISWC 2017 First prize in CLEI 2017 for his Master's thesis Sebastián currently leads the Fondecyt project on graph data management and contributes to the U-Inicia project on AI processes in graph databases. He serves on the editorial board of Transactions on Graph Data and Knowledge.

Stefano FerilliView profile

Professor

• Machine Learning
• Artificial Intelligence
• Data Mining
• +6 more

Stefano Ferilli is a Professor of Computer Science at the University of Bari, Italy, where he leads the ARA (Apprendimento e Ragionamento Automatico) research lab within the Department of Computer Science. His academic roles include former Director of the Interdepartmental Center for Logic and Applications (CILA) and current head of the Artificial Intelligence & Intelligent Systems node in the CINI national laboratory. He holds a PhD in Computer Science and has been a key figure in advancing machine learning, logic programming, and digital library technologies. Education: Laurea (MSc equivalent) in Information Sciences (1996), Specialist Laurea in Computer Science (2003), and PhD in Computer Science (2001). His research focuses on foundational aspects of machine learning, multi-strategy reasoning, process mining, and applications in cultural heritage, bioinformatics, and smart environments. Research Contributions: Developed frameworks like INTHELEX (incremental theory learner), WoMan (process mining), and DoMInUS (document management). Over 370 publications, including a Springer monograph and multiple award-winning papers. Active in organizing conferences like ECML-PKDD, ICDM, and IRCDL, and serves on editorial boards of journals like Information Sciences . Projects: Led or participated in over 30 national and European projects, including EU-funded initiatives on digital libraries (COLLATE, DELOS) and AI applications. Collaborates with industries like Samsung and institutions like the Italian Police for traffic analysis and cultural heritage preservation. Awards: Recognized for outstanding peer review (MDPI, ECMLPKDD), best paper awards, and contributions to AI education and cultural heritage. Member of prestigious associations like AI*IA (Italian AI Society) and AICA (Italian Computing Society).

Enrico FranconiView profile

Professor

• Knowledge Representation
• Artificial Intelligence
• Semantic Technologies
• +6 more

Enrico Franconi is a tenured full Professor in the Faculty of Engineering at the Free University of Bozen-Bolzano, Italy. He is the founder and director of the KRDB Research Centre for Knowledge-based Artificial Intelligence, established in 2002. His research focuses on applying database, AI, and semantic technologies to address challenges in information systems design, data integration, and big data analysis. He holds leadership roles including former Vice-Rector for Research (2005-2006) and director of the European Masters Program in Computational Logic (2004-2019). His academic contributions span Description Logics, knowledge representation, and ontology engineering, with a strong emphasis on theoretical foundations and practical applications. He has led numerous EU-funded projects, including ONTORULE and SeWAsIE, and contributed to international conferences as a program committee member and keynote speaker. His work bridges theory and practice, aiming to translate foundational results into real-world solutions. He is a prolific author with an h-index of 42 and has mentored researchers in areas like semantic web technologies and conceptual modeling. Key achievements include advancing ontology-driven data integration, developing tools like ICOM for conceptual modeling, and contributing to standards for semantic web languages. He is affiliated with the Computational Logic community and actively participates in international research networks such as CAIRNE. His research has been recognized through ANVUR evaluations ranking his department among Italy’s top computer science faculties.

Olaf HartigView profile

Associate Professor

• Database Systems
• Semantic Web
• Data Management
• +5 more

Olaf Hartig is a Senior Associate Professor at Linköping University's Department of Computer and Information Science (IDA), affiliated with the Database and Information Techniques (ADIT) division. He is also an Amazon Scholar collaborating with the Neptune graph database team. His research focuses on data management, semantic web technologies, graph databases, and distributed data systems. Hartig holds a PhD from Humboldt-Universität zu Berlin and is a Docent at Linköping University. He has received numerous awards, including the SWSA Distinguished Dissertation Award and eight best paper awards, and was selected as a Wallenberg Academy Fellow in 2024. Education: PhD in Computer Science (Humboldt-Universität zu Berlin), Docent (Linköping University). Research interests span query processing for Linked Data, federated systems, RDF and GraphQL semantics, and knowledge graph construction. He leads research groups in Database and Web Information Systems and Semantic Web Technologies at IDA. Key achievements include pioneering traversal-based query execution, developing Triple Pattern Fragments, and contributions to standards like RDF* and SPARQL*. His work has been recognized through grants, patents (e.g., on graph acceleration techniques), and leadership roles in conferences like ISWC and ESWC. Teaching: Course leader for database technology courses (TDDD12, TDDD37) and advanced topics like big data analytics and bioinformatics databases. Active in curriculum design and interdisciplinary education. Labs/Teams: Database and Web Information Systems Group, Semantic Web Research Group, Sports Analytics Group (IDA) Grants: Wallenberg Academy Fellowship, Swedish Research Council funding

Katja HoseView profile

Professor

• Query Processing
• Semantic Web
• Linked Data
• +7 more

Katja Hose is a Professor in the Department of Computer Science at Aalborg University's Technical Faculty of IT and Design. Her research focuses on Data, Knowledge and Web Engineering with specializations in AI for the People and Artificial Intelligence and Machine Learning. She maintains an active research profile with numerous publications and projects. Department of Computer Science Technical Faculty of IT and Design Aalborg University Research areas: Query Processing, Semantic Web, Linked Data, Knowledge Graphs Professor Hose's research interests center on knowledge representation, semantic web technologies, and AI applications. Her work spans from theoretical database systems to practical applications in healthcare, environmental assessment, and microbial data analysis. She has made significant contributions to knowledge graphs, large language models, and semantic search technologies, with particular emphasis on addressing hallucinations in AI systems and improving table search in semantic data lakes. Her recent publications demonstrate a strong trend toward integrating knowledge graphs with large language models, developing evaluation frameworks for AI hallucinations, and applying data science to diverse domains including healthcare and environmental sustainability. Her research bridges theoretical computer science with practical applications that address real-world challenges. NLP4KGC Best Paper Award (2023) ESWC 2023 Best Demo Award (2023) 2020 AMiner AI 2000 Most Influential Scholars AIME 2020 Best Paper Nomination (2020) ESWC 2019 Best Demo Award Nomination (2019) Professor Hose leads multiple significant research projects including ARISTOTLE (AI for clinical risk assessment), DarkScience (microbial data analysis), and the Poul Due Jensen Professorate in Big Data and AI. She has supervised numerous PhD students and collaborates extensively across disciplines, particularly in healthcare applications of AI and environmental assessment technologies. Her research has attracted substantial funding from sources like Villum Fonden and Danish E-infrastructure Cooperation. She is actively involved in several interdisciplinary research teams, including collaborations with microbiologists on microbial dark matter projects and with environmental scientists on digital environmental assessment systems. Her work on the ARISTOTLE project demonstrates strong connections between AI research and clinical applications, while her DarkScience project bridges computer science with microbiology.

• Schema discovery for Semantic Web data
• Data mining
• Recommendation systems
• +5 more

Kenza Kellou-Menouer is a researcher affiliated with the ETIS Laboratory at ENSEA, France, and part of the MIDI research group . Her work focuses on schema discovery for Semantic Web data, data mining, and big data optimization. Research: Semantic schema discovery, clustering/classification algorithms, and association rules. Teaching: Semantic Web technologies, database design, algorithms, and programming languages (Java, C++, C#, C). Research Interests center on Semantic Web data integration, RDF schema inference, and hybrid machine learning approaches. She has contributed to scalable schema discovery systems and real-time profiling techniques for large datasets. Publications include work on schema inference tools (SchemaDecrypt++, HInT) and methodological frameworks presented at top-tier venues like VLDB (A*), ICDE (A*), SSDBM (A), and ISWC . Her research bridges theoretical advancements with practical implementations for RDF datasets. Community Contributions include organizing tutorials at the International Semantic Web Conference (ISWC) 2022 and developing educational materials for database and programming courses.

Fei ChiangView profile

Associate Professor

• Data Management
• Data Quality
• Data Privacy
• +6 more

Dr. Fei Chiang is an Associate Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. Her research focuses on data management , with emphasis on data quality, data privacy, information extraction , and contextual data cleaning . She has collaborated with IBM Global Services and Microsoft Research on improving data quality in enterprise systems. Key research themes include graph databases , temporal data analysis , and privacy-aware data processing Recent publications explore federated learning , SQL understanding in LLMs , and temporal graph constraints Industry collaborations with IBM Toronto Lab and Microsoft Research have led to innovations in data cleaning automation and semantic analysis. Her work bridges database theory with machine learning applications in healthcare inventory optimization and flight reliability prediction.

Morteza ZihayatView profile

Associate Professor

• Data Analytics
• Human-centered AI
• Decentralized AI
• +6 more

Morteza Zihayat is an Associate Professor and Canada Research Chair (Tier 2) in Human-Centered Artificial Intelligence at Toronto Metropolitan University. He holds dual appointments in the Faculty of Engineering and Architectural Science (Department of Electrical, Computer, and Biomedical Engineering) and the Ted Rogers School of Management. Additionally, he serves as an Adjunct Professor at the University of Waterloo in Management Sciences and is a Faculty Fellow at IBM's Centre for Advanced Studies. Dr. Zihayat's educational background includes: PhD in Computer Science from York University (2016) MSc in Computer Engineering from University of Tehran (2011) Postdoctoral Research Fellowship at University of Toronto's Faculty of Information (2017) His research lies at the intersection of AI, security, and society with a focus on building fair and transparent AI systems. Dr. Zihayat's expertise spans human-centered AI, fair information retrieval systems, and blockchain-enabled AI infrastructures. His work emphasizes creating AI systems that are accountable and designed to serve the public good, with applications in healthcare, digital media, and social networks. Dr. Zihayat has received numerous accolades including the Canada Research Chair (Tier 2) in Human-Centered AI (2024), Dean's Outstanding Scholarly, Research, and Creative Activity Award (2023), Best Short Paper Award at ECIR (2023), and IBM CAS Faculty Fellowship (2021). His research has attracted over $1.7 million in external funding from agencies such as NSERC, Mitacs, and multiple industry partners including Toronto Transit Commission, The Globe and Mail, AT&T, and IBM. Dr. Zihayat serves as Associate Editor of the Computational Intelligence Journal and is an active reviewer for top-tier venues. He is also Co-director and Co-founder of the Digital Enterprise Analytics and Leadership (DEAL) Research Center.

• Logic
• Automated Reasoning
• Ontology Languages
• +5 more

Ulrike Sattler is a Professor in the Department of Computer Science at the University of Manchester, where she also serves as Deputy Head of Department and Senior Mentor. Her academic journey includes a PhD from RWTH Aachen University (1998) and a Habilitation from the University of Manchester (2003). She has held roles such as Reader and Senior Lecturer at Manchester, and previously worked as a Senior Researcher at TU Dresden and RWTH Aachen. Her research focuses on logic-based knowledge representation, automated reasoning, and Description Logics, with contributions to OWL ontology languages and standardization. Notable awards include the Friedrich Wilhelm Preis (1999) for her PhD thesis. She has co-supervised over 20 PhD students, including prominent figures like Birte Glimm and Matthew Horridge. Her service contributions include co-chairing conferences (KR 2010, IJCAR 2012), editorial roles in journals like JAR and JAIR, and leadership in the W3C OWL Working Group. She teaches courses on ontology engineering and semantic web technologies, emphasizing practical applications in molecular biology and knowledge graphs.

• Robotics
• Artificial Intelligence
• Autonomous Systems
• +4 more

Nikolaos Tsiogkas is an Assistant Professor in the Declarative Languages and Artificial Intelligence (DTAI) group at KU Leuven's Faculty of Engineering Technology, Department of Computer Science. His research focuses on robotics, artificial intelligence, and autonomous systems, with particular emphasis on cognitive reasoning, knowledge representation, and sensor fusion for robotic navigation. Projects: Promotor of initiatives like 'Harnessing Robotics for Safe Agriculture' (2024-2028) and 'ROSANA: Robust Semantic Navigation in Orchards' (2022-2027); co-promotor in demining robotics and multi-arm manipulation research. Research: Combines symbolic AI with robotics, exploring knowledge graphs for explainable navigation, reinforcement learning frameworks, and computationally efficient free-space detection algorithms.