جست‌وجوی استاد و پژوهشگر

Véronique Benzakenمشاهده پروفایل

استاد

• Data-Centric Programming Languages
• Formal Methods
• Type Systems
• +۳ مورد دیگر

Véronique Benzaken is a Full Professor at the University of Paris-Saclay , affiliated with the Computer Science Department and member of the VALS (Verification of Algorithms, Languages, and Systems) research group at LRI (CNRS) and the Toccata group at INRIA-Saclay. Her research focuses on Data-Centric Programming Languages and Deep Specification with Proof Assistants , particularly SQL/XML formalization and Coq-based verification systems. Her work includes the development of the ℂDuce XML-centric functional programming language and the Datacert project (2016-2021) for certifying data-intensive systems using Coq and Why(3). She collaborates with Oracle Labs on multi-lingual query interfaces (QIR) and formalizes languages like XQuery, Datalog, and SQL execution plans. She has received significant funding through the ANR grants for the Typex (2016) and Datacert (2016-2021) projects. Her publications in venues like CPP, ESOP, ITP, and SPLASH reflect her leadership in formal methods for data systems. Education : Habilitation (1996), PhD (1990), DEA in Theoretical Computer Science (1986), and degree in Singing/Opera (1983). Employment : Full Professor at Paris-Sud 11 since 1998; Assistant Professor at Paris 1 Panthéon-Sorbonne (1990-1998); INRIA researcher (1986-1990).

• Information Retrieval
• XML Search Engines
• Text Search Engines
• +۸ مورد دیگر

Shlomo Geva is an Adjunct Professor in the School of Computer Science at Queensland University of Technology's Faculty of Science. His research focuses on information retrieval systems, particularly in specialized areas including XML search engines, text search engines, link discovery, and document computing. His academic work spans multiple disciplines within computer science, with particular emphasis on information retrieval technologies and their applications. Professor Geva's research interests include clustering algorithms, cross language information retrieval, focused information retrieval, information retrieval systems, link discovery mechanisms, search engine technologies, text indexing and retrieval methods, and XML indexing and retrieval techniques. His work demonstrates a consistent focus on improving the efficiency and effectiveness of information access systems across various data formats and domains. His recent publications reveal a trend toward applications of information retrieval techniques in diverse fields including remote sensing, bioinformatics, and data stream processing. The research shows an evolution from traditional information retrieval problems toward more specialized applications requiring advanced clustering algorithms and efficient data processing techniques for large-scale datasets. Professor Geva has successfully supervised numerous doctoral students whose research topics include indoor environment mapping by robots, cross-language information retrieval, natural language query interfaces for XML, evolvable hardware, and autonomous robot behavior systems.

• Database Systems
• Semantic Web
• Graph Databases
• +۳ مورد دیگر

Jacques CHABIN serves as a Lecturer at the University of Orleans, affiliated with the LIFO (Laboratoire d'Informatique Fondamentale d'Orléans) research laboratory. His academic role centers on advancing database theory and semantic technologies within the institution's computer science research ecosystem. His research spans database systems with emphasis on semantic web architectures, graph database evolution, and formal language applications. Key investigations include RDF/S schema management, null value handling in incomplete databases, and context-driven querying systems for urban graph analysis. Recent work addresses privacy-preserving techniques in semantic networks and consistency maintenance during database evolution. Analysis of his 15 most recent publications reveals persistent focus on graph-based data management systems. The 2020-2024 output demonstrates progression from foundational XML schema evolution toward contemporary property graph challenges, with consistent attention to data consistency, constraint enforcement, and practical tool development like DataFix for database repair. As an active member of LIFO, Chabin contributes to the laboratory's mission in fundamental computer science research. His collaborative work with researchers including Mirian Halfeld-Ferrari and Nicolas Hiot reflects integration within the laboratory's database systems research group focused on theoretical and applied data management challenges.

• Machine Learning
• Big Data Management
• Data Integration
• +۵ مورد دیگر

Vassilios Vassalos is a Professor in the Department of Computer Science at Athens University of Economics and Business (AUEB), where he has been since 2004. He directs the graduate program in Data Science and leads the Data Science research group at the Information Processing Laboratory ( ipl.aueb.gr ). Prior to this, he served as Assistant Professor of Information Systems at the Stern School of Business, New York University, and held visiting positions at École Polytechnique Fédérale de Lausanne (2013) and the University of California, San Diego (2007-2008). Education : Diploma in Electrical and Computer Engineering from National Technical University of Athens (1994), MSc (1998) and PhD (2000) in Computer Science from Stanford University. His research focuses on machine learning techniques for large-scale business problems, next-generation big data management , data integration and cleansing , and query optimization for non-traditional data (XML, streams, text) in environments like sensors and text databases. His work has produced over 50 publications and two patents, with a notable ICDE 2009 Best Student Paper award for a reactive join optimization technique. Scientific Awards : Marie Curie Fellow, Bodossakis Foundation Fellow, Lilian Voudouris Foundation Fellow. As founder of Enosys Software (acquired by BEA Systems) and Principal Investigator in the Human Brain Project, he bridges academia and industry, advising organizations like Eurobank and the Special Secretariat for Digital Planning. His leadership in funded research programs and graduate education underscores his impact.

Katja Zeumeمشاهده پروفایل

استاد

• Databases
• Information Systems
• Semi-structured Data
• +۵ مورد دیگر

Prof. Dr. Katja Zeume serves as Professor and Dean of the Faculty of Computer Science and Communication at the Westphalian University of Applied Sciences in Gelsenkirchen, Germany. Her academic leadership spans theoretical and applied database systems research with emphasis on semi-structured data management. Her educational foundation includes a PhD from the University of Bayreuth (2015), where she completed her thesis "Foundations of Regular Languages for Processing RDF and XML" under the name Katja Losemann. Dr. Zeume's research centers on the theoretical underpinnings of database query languages, particularly investigating regular expressions in SPARQL for RDF and XML data models. Her work bridges formal language theory with practical database applications, addressing challenges in query complexity, data federation, and schema design for unstructured information. Key contributions include foundational analyses of deterministic regular expressions and their computational properties in semantic web contexts. Her publication trajectory reveals consistent focus on theoretical database foundations, evolving from XML schema research toward SPARQL complexity analysis. The body of work demonstrates deep integration of automata theory, complexity analysis, and practical query language design for modern data ecosystems. As Dean of the Faculty of Computer Science and Communication, she oversees academic strategy while maintaining active research engagement. Her teaching portfolio includes core database systems courses covering traditional SQL, NoSQL architectures, web-scale data management, and theoretical database principles.

Giorgio Ghelliمشاهده پروفایل

استاد

• Database Systems
• Data Management
• XML
• +۴ مورد دیگر

Giorgio Ghelli is a Full Professor at the Department of Computer Science, University of Pisa. His research focuses on database systems, XML/JSON schema validation, type systems, and formal methods. He has contributed to foundational work on programming languages and query systems, including the development of the Fibonacci database programming language and the TQL query language for semistructured data. His recent work emphasizes JSON schema formalization, validation techniques, and interactive schema inference for large datasets. Teaching includes advanced database courses and foundational database theory. Research interests span data management, formal semantics, and efficient query processing. Over 150 publications including seminal works on XML updates, JSON schema validation, and type systems for mobile ambients.

• XML Database Systems
• Cloud Computing Security
• Data Stream Mining
• +۵ مورد دیگر

Eric Pardede is a professor at the School of Computing and Mathematics of Western Sydney University . He has an extensive publication record in data management, cybersecurity, and technology-enhanced learning, often collaborating with researchers like Wenny Rahayu, David Taniar, and A. S. M. Kayes. Research Focus: XML database systems, cloud computing security, data stream mining, and educational technology Award-Winning Contributions: Notable work on IoT security frameworks, blockchain risk assessment, and adaptive learning systems Recent Publications: 15 articles from 2021-2025 address topics like concept drift adaptation, cybersecurity in multi-cloud environments, and smart education tools Key Collaborations: Frequent partnerships with researchers in Australia, Indonesia, and Austria

• Distributed Stream Processing
• Data Stream Analytics
• Database Optimization
• +۳ مورد دیگر

Dr. Boris Novikov is a prominent Russian computer scientist affiliated with St Petersburg University and the Higher School of Economics . His research focuses on distributed stream processing, temporal databases, and XML query optimization. Key collaborators include Artem Trofimov , Elena Mikhailova , and Anna Yarygina . Research Areas : Distributed Systems (stream processing, substream management) Database Optimization (vertical partitioning, XML caching) Temporal Data Management Machine Learning (concept drift detection) His recent work on distributed stream processing (2023-2022) explores substream bounding, deterministic models, and resource allocation strategies. Earlier contributions (2012-2008) focused on XML query performance, similarity indexing, and access control frameworks. Technical Trends : Event time alignment in distributed architectures Dynamic residual projection for cybersecurity Bi-objective optimization in database systems Speculative execution with conflict resolution Incremental Lagrangian dual solutions Matrix clustering for partitioning problems

Louiqa Raschidمشاهده پروفایل

استاد

• Database Systems
• Data Integration
• Data Mining
• +۸ مورد دیگر

Louiqa Raschid is a Professor at the University of Maryland, holding appointments in the Robert H. Smith School of Business, the Institute for Advanced Computer Studies (UMIACS), and the Department of Computer Science. Her research bridges computer science and business information systems, focusing on data integration, management, and mining in non-traditional domains. Education: B.Tech (IIT Madras, 1980), PhD (University of Florida, 1987) Research Interests include: Data integration and mining across life sciences, health sciences, and financial ecosystems Humanitarian IT solutions for disaster management Semantic query optimization and data delivery techniques Grid and wide-area data management Article Trends reflect interdisciplinary efforts combining bioinformatics, database systems, and social behavior modeling. Key themes include ontology-driven data analysis, network-aware query optimization, and disaster relief systems development. Scientific Awards include: ACM Distinguished Member (2016) ACM Fellow (2016) IEEE Fellow (2000) DILS 2008 Best Paper Award Grants from NSF and DARPA have funded her work on biological data integration and financial cyberinfrastructure. She co-directs the Computational Linguistics and Information Processing (CLIP) Lab and collaborates with institutions worldwide.

• Machine Learning
• Data Mining
• Recommendation Systems
• +۵ 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.

Jian Tangمشاهده پروفایل

استاد

• Database Systems
• Distributed Computing
• Data Mining
• +۳ مورد دیگر

Dr. Jian Tang is a Professor in the Department of Computer Science at Memorial University of Newfoundland. He holds a M.Sc. from the University of Iowa and a Ph.D. from Penn State University. His primary affiliation is within the Faculty of Science. His research focuses on database systems, distributed computing, data mining, and IoT security. Key projects include fault tolerance in distributed systems, workflow management, intrusion detection in IoT networks, and machine learning applications in healthcare and genomics. He has published extensively on topics like autonomous IoT security systems, feature selection methods for microarray data, and probabilistic resource scheduling in grid environments. Dr. Tang’s work bridges theoretical foundations with practical implementations, particularly in cybersecurity, bioinformatics workflows, and scalable distributed systems. His recent publications emphasize real-time autonomous IoT security solutions and machine learning-driven predictive models for healthcare outcomes.

Marc H. Schollمشاهده پروفایل

استاد

• Database systems architecture
• Query optimization
• Data stream processing
• +۳ مورد دیگر

Marc H. Scholl is Professor Emeritus of Computer Science at University of Konstanz, specializing in database systems and information management. He served as Vice President at University of Konstanz (1998-2004) and CIO at both Konstanz (2012-2023) and University of Freiburg (2022-2023). His research focuses on database architectures, query optimization, and emerging data management paradigms including XML databases and stream processing. He co-founded BaseX GmbH, an XML database company, and launched OpenProceedings.org for open-access conference publications. Scholl has chaired major conferences including EDBT'06 and serves on the executive board of the EDBT association. His work bridges academic research with industrial applications in data management systems.

Martin Wynneمشاهده پروفایل

پژوهشگر

• Corpus Linguistics
• Digital Humanities
• Computational Linguistics
• +۳ مورد دیگر

Martin Wynne is a Senior Researcher in Corpus Linguistics and National Coordinator for CLARIN-UK at the University of Oxford, affiliated with the Faculty of Linguistics, Philology and Phonetics. His roles include managing the Literary and Linguistic Data Service (successor to the Oxford Text Archive) and leading CLARIN-UK, a pan-European infrastructure for language resources. He previously held positions at OUCS (now IT Services), Bodleian Libraries, and universities in Germany and Poland. His research focuses on corpus linguistics, literary and non-literary text analysis, and digital humanities infrastructure. Education: Studied Linguistics at the University of Leeds and French at Queen Mary College, London. He has taught courses on corpus linguistics and digital research methods, including modules for MSc Digital Scholarship and Linguistics masters programs. Research interests include corpus design, digital humanities tools, language resource curation, and projects such as the British National Corpus (BNC) and Holocaust testimony analysis. His work emphasizes interdisciplinary applications of linguistic corpora. Notable contributions include founding the Digital Humanities at Oxford initiative, collaborating on CLARIN’s infrastructure, and developing resources like the BNC XML edition. He has advised on projects involving poetry visualization, Grid/Cloud data hosting, and federated identity management. Labs/Teams: Associated with the Oxford e-Research Centre, CLARIN-UK consortium, and the Literary and Linguistic Data Service. Collaborates with institutions like EHRI (European Holocaust Research Infrastructure) on data-driven humanities projects.

Cindy Chenمشاهده پروفایل

دانشیار

• Spatio-temporal Databases
• Data Mining
• Cloud Computing
• +۴ مورد دیگر

Cindy Chen serves as Department Chair and Associate Professor at the Miner School of Computer and Information Sciences within the Kennedy College of Sciences at the University of Massachusetts Lowell. Her academic journey includes a Ph.D. in Computer Science with specialization in Database and Knowledge Base Management from UCLA (2001), an MS in Computer Science from UCLA, and a BS in Space Physics from Peking University. Ph.D.: Computer Science (Database and Knowledge Base Management), University of California at Los Angeles (2001) MS: Computer Science, University of California at Los Angeles BS: Space Physics, Peking University - Beijing, China Her research spans spatio-temporal databases, data mining, cloud computing, and social network analysis. Early work focused on spatio-temporal data models and query languages , evolving into cloud data warehouse optimization and social network mining (particularly online dating behavior), then advancing to high-dimensional indexing , knowledge graph querying , and recent innovations in temporal database granulation using Allan Variance techniques for CAV friction modeling. Current work integrates database systems with autonomous vehicle infrastructure and real-time urban analytics. Her publication timeline reveals a transition from foundational spatio-temporal database systems (1998-2008) to cloud/social applications (2008-2015), then to granulation techniques and CAV systems (2015-present). Key domains include XML databases, skyline queries, social trend discovery, and friction data modeling for autonomous vehicles. Dean's Fellowship (1998) Dean's Fellowship (1999) Dr. Chen has secured significant research funding including the UMASS Transportation Center grant for an Interactive TMC Decision Support Tool (2008) and a UML Healey Grant Award for Spatio-Temporal Knowledge Discovery in Nuclear Physics (2008). Her collaborative projects span transportation systems, nuclear physics applications, and autonomous vehicle infrastructure. She actively advises on database curriculum development and serves as department chair overseeing academic operations.

Peter Bunemanمشاهده پروفایل

استاد

• Database Systems
• Data Provenance
• Semistructured Data
• +۹ مورد دیگر

Peter Buneman is a Professor in the School of Informatics at the University of Edinburgh, affiliated with the Laboratory for Foundations of Computer Science (LFCS). He is a leading researcher in database systems, with a focus on data provenance, semistructured data, XML, and digital curation. He has been instrumental in advancing the theoretical foundations of database query languages and data integration. His research interests include database theory, data modeling, type systems, and the management of scientific data. He has made significant contributions to the understanding of data provenance, XML constraints, and the archiving of scientific datasets. His work bridges theoretical computer science with practical applications in bioinformatics and digital libraries. The recent publications highlight a consistent focus on data provenance, XML query processing, integrity constraints, and database archiving. His work spans both theoretical investigations and practical system design, often addressing challenges in data integration, curation, and long-term preservation. Peter Buneman has been actively involved in academic service, including editing proceedings for major conferences such as PODS and ICDT, and contributing to journals like the Journal of Digital Libraries. His leadership in the database community is evident through his editorial roles and collaborations. He advises and collaborates with researchers in database systems and related fields. His work has been supported by significant research initiatives, including involvement with the Digital Curation Centre, which underscores his commitment to sustainable data management practices. He is a key member of the Database Group at LFCS and has contributed to shaping research directions in data management. His past affiliation with the University of Pennsylvania’s Department of Computer and Information Science further reflects his long-standing impact on the field.