جست‌وجوی استاد و پژوهشگر

• Distributed Databases
• Object-Oriented Databases
• Internet Databases
• +۹ مورد دیگر

Erich Neuhold is a Professor of Computer Science at the University of Vienna and Darmstadt University of Technology. He holds honorary professorships at several institutions, including the University of Guiyang and the New Jersey Institute of Technology. His career spans over five decades, with roles as Director of the Fraunhofer Institute for Integrated Publication and Information Systems (IPSI) and professorships at multiple universities globally. Education: Erich Neuhold earned a Dipl.-Ing. (M.S.) in Electronics and a Dr.-techn. (PhD) in Mathematics and Computer Science from the Technical University of Vienna. He holds special honors in his academic career, including Fellowships from IEEE and the Gesellschaft für Informatik. Research Interests: His work focuses on distributed databases, object-oriented systems, internet databases, information retrieval, semantic web, interoperability, and applications in digital libraries, e-science, and e-government. He pioneered advancements in transaction models, multimedia databases, and semantic integration frameworks. Publications: Over 200 papers and four books, with recent contributions including retrospectives on computing history and foundational work in supercomputing architectures. His articles reflect deep engagement with historical and future trends in computer science. Awards: Recognitions include the Meritorious Service Award from IEEE, medals from academic institutions, and honorary professorships worldwide. Grants & Labs: Led projects like the POREL distributed database system and contributed to initiatives like the EU’s FRESCO e-science cockpit. His work spans academic-industrial collaborations, with budget leadership at IPSI (€10M/year). Labs/Teams: Co-founded the Fraunhofer IPSI and directed research teams in Austria, Germany, and internationally, emphasizing interdisciplinary collaboration in information systems.

• Answer Set Programming
• Logic Programming
• Knowledge Representation
• +۲ مورد دیگر

Wolfgang Faber is a researcher at Vienna University of Technology (TU Wien) specializing in Knowledge-Based Systems within the Faculty of Informatics. Holding the position of Privatdozent, he has completed his habilitation and is qualified to teach at the university level. His academic work centers on Answer Set Programming (ASP), Logic Programming, and Knowledge Representation, with significant contributions to theoretical foundations in these fields. Dr. Faber's research spans multiple areas of computational logic: Answer Set Programming and its theoretical underpinnings Epistemic logic programs and equivalence properties Knowledge representation and reasoning systems Nonmonotonic reasoning formalisms Integration of logic programming with external data sources His publication history reveals a sustained focus on theoretical aspects of ASP, with particular emphasis on program equivalence concepts (strong equivalence, uniform equivalence), computational complexity analysis, and applications to knowledge representation. Over two decades, his research has evolved from foundational work in disjunctive logic programming to specialized topics in epistemic reasoning within ASP frameworks. Dr. Faber has led and participated in numerous research projects including START (2014-2022) on Uniform Equivalence of Epistemic Logic Programs, SemDat (2012-2016), and multiple projects related to hybrid knowledge bases and Answer Set Programming from 2005-2015. His collaborative research extends across European institutions, evident through extensive co-authorship with researchers like Thomas Eiter and Stefan Woltran. While specific awards aren't documented in the available information, his sustained research output and leadership in multiple projects indicate significant recognition within his field. Dr. Faber has made substantial contributions to major systems in the field, most notably the DLV system for knowledge representation and reasoning, which has influenced both academic research and practical applications of Answer Set Programming.

Georg Gottlobمشاهده پروفایل

استاد

• Database Theory
• Web Data Processing
• Query Languages
• +۱۱ مورد دیگر

Georg Gottlob is a Professor of Informatics at the University of Oxford and an Adjunct Professor at Vienna University of Technology (TU Wien). He is a Fellow of St John's College, Oxford, and focuses on algorithms and complexity in areas like database theory, constraint satisfaction, and computational logic. His work bridges theoretical foundations and practical applications, including web data extraction and quantitative finance. Education: Engineer and Ph.D. in Computer Science from TU Vienna (1979, 1981) Previous Positions: Full Professor at TU Vienna (1988-2006), Director of Christian Doppler Laboratory for Expert Systems (1989-1996), McKay Professor at UC Berkeley (1999) Research Interests: Gottlob specializes in graph/hypergraph-based problem decomposition methods for tractable instances of NP-hard problems, with applications in database query optimization, constraint satisfaction, and combinatorial auctions. His work spans database theory, AI, and computational complexity. Article Trends: Recent publications emphasize knowledge graph construction from financial data (2022), complexity analysis in logical frameworks (2021), and foundational work in guarded existential rules (2014). Themes include AI-driven data extraction, computational complexity, and logic programming. Scientific Awards: Fellow of the Royal Society (2010) Ada Lovelace Medal (2017) Wittgenstein Award (1998) Honorary Doctorates (University of Calabria, Klagenfurt) Advising and Leadership: Supervised numerous students and directed industry-funded projects like the Christian Doppler Laboratory. Co-founded Lixto Corporation and established the Oxford-Man Institute of Quantitative Finance (2006). Served as Editor-in-Chief of Artificial Intelligence Communications and on editorial boards of major journals.

Masana Castrillo, Marcمشاهده پروفایل

پژوهشگر

• Deep Learning
• Continual Learning
• Computer Vision
• +۳ مورد دیگر

Herr Marc Masana Castrillo is a Researcher at the Institute of Computer Graphics and Vision within Graz University of Technology (College of Engineering). Holding a PhD in Computer Vision (cum laude) from Universitat Autònoma de Barcelona (2020), he specializes in Deep Learning , Continual Learning , and Neural Network Compression . His work addresses catastrophic forgetting in sequential tasks, out-of-distribution detection, and domain adaptation. PhD Thesis: "Lifelong Learning of Neural Networks: Detecting Novelty and Adapting to New Domains without Forgetting" MSc in Computer Vision (with Honours, 2015) BSc in Mathematics and Computer Science (2014) His research spans continual learning frameworks , feature disentanglement , and multimodal translation . Publications in top-tier venues like TPAMI , BMVC , and ICCV highlight his contributions. He co-developed Avalanche , an open-source PyTorch-based library for reproducible continual learning research. Scientific recognition includes the Best Master Thesis Project at UAB (2015) and the Business Track Award at Accenture Datathon (2016). His email addresses are mmasana@tugraz.at and marc.masana@icg.tugraz.at . He has reviewed for journals like TPAMI and conferences including CVPR and ICCV .

• Information Systems
• Computer Science
• Process Modeling
• +۳ مورد دیگر

Josef Lubas is a PhD candidate in the Research Group Information and Communication Systems at the University of Klagenfurt , Austria. He holds a BSc and MSc and is supervised by Prof. Johann Eder. His work focuses on process modeling, temporal constraints, and legal technology applications in smart contracts. Education: BSc, MSc (details unspecified); current PhD candidate in Informatics Systems. Research Interests: Josef specializes in temporal aspects of process models , conflict resolution in workflow systems , and legal smart contracts . His work bridges theoretical computer science with practical applications in business process management and regulatory compliance. Publications (2020–2023): Focus on temporal logic applications in process scheduling, dynamic controllability, and integrating time-aware models into legal frameworks. Recent work emphasizes smart contract systems with legal enforceability. Labs/Teams: Member of Team ICS within the Information and Communication Systems group. Collaborates with Prof. Eder’s research team on temporal data modeling and process engineering.

Axel Polleresمشاهده پروفایل

استاد

• Semantic Web
• Ontology Languages
• Web Databases
• +۷ مورد دیگر

Axel Polleres is a full professor at the Vienna University of Economics and Business (WU Wien), leading the Department of Information Systems and Operations Management and heading the Data Management group within the Institute for Data, Process and Knowledge Management. He specializes in Semantic Web technologies, knowledge representation, and open data. His work includes contributions to SPARQL, RDF, and W3C standards. Education: PhD and Habilitation in Computer Science (TU Wien) MSc in Computer Science (TU Wien) Research Interests: Semantic Web, Ontology Languages, Linked Data Nonmonotonic Reasoning, Answer Set Programming Query Languages (SPARQL), Data Integration Open Data ecosystems and Quality Assessment Recent Articles Trends: Focusing on knowledge graph evolution, constraint validation (SHACL), and open data pipelines, with applications in city data and semantic web services. His work bridges theoretical foundations with practical implementations. Awards: IEEE 2015 Best Paper Award RR2010 Best Paper Award ISWC2009 In-use Track Best Paper Advising & Labs: Advisor to over 30 PhD/MSc students. Leads the Data Management group at WU, focusing on open data systems and semantic technologies. Involved in projects like FRESH, OMEGA, and W3C standardization efforts.

• Knowledge Representation
• Description Logics
• Computational Logic
• +۳ مورد دیگر

Magdalena Ortiz is a Full Professor and Head of the Knowledge-Based Systems Research Unit at TU Wien, specializing in Knowledge Representation and Reasoning with a focus on Description Logics (DLs). Her work emphasizes integrating DLs with database systems, particularly in query languages and reasoning algorithms. She leads research in semantic technologies, ontology-mediated query answering, and formal methods for data validation (e.g., SHACL). Research interests include expressive query languages, computational complexity of DL reasoning, and applications in graph databases and cloud security. She has extensive experience in EU-funded projects (e.g., FRESH, KtoAPP) and serves editorial roles in AI conferences/journals. Her teaching includes advanced courses on Description Logics, Logic, and Ontology Engineering. Notable contributions include advancements in SHACL validation, Datalog rewritings for ontology-mediated queries, and reasoning with closed predicates. She advises multiple PhD students and collaborates internationally on topics like temporal equilibrium logic and OBDA systems.

Val Tannenمشاهده پروفایل

استاد

• Database Theory
• Programming Language Theory
• Data Provenance
• +۵ مورد دیگر

Val Tannen is a Professor in the Department of Computer and Information Science (CIS) at the University of Pennsylvania, holding appointments since 1987. He has undertaken numerous visiting roles, including at Simons Institute (2023), EPFL (2020, 2011-2012), NUS (2019), and institutions in Greece, France, and elsewhere. Education: Polytechnic Institute of Bucharest (Engineer Diploma, 1977) MIT (PhD in Applied Mathematics/Computer Science, 1983-1987) His research spans database theory, programming language theory, logic, and applications to bioinformatics. Key contributions include provenance frameworks and complex object modeling , impacting data integration, uncertainty management, and systematic biology. Notable awards include ACM Fellowship , Mendelzon Test-of-Time Award , and NSF Presidential Young Investigator . His work has been disseminated through 30+ conference program committee roles and editorial contributions. Scientific Awards: 10 years Mendelzon Test-of-Time Award ACM Fellow 20 years Test-of-Time Award NSF Presidential Young Investigator

• Knowledge Graphs
• Datalog
• Database Systems
• +۴ مورد دیگر

Aleksandar Pavlović is a researcher at the Institute of Computer Sciences specializing in knowledge graph technologies and Datalog-based systems. His work bridges semantic web standards with machine learning methodologies to advance knowledge representation and query processing efficiency. Research interests focus on: Knowledge graph embedding techniques with spatial and geometric interpretations Datalog optimization for SPARQL query evaluation Integration of graph neural networks with symbolic reasoning systems Interoperability solutions for semantic web technologies Recent publications (2023-2024) demonstrate consistent innovation in knowledge graph completion and reasoning, featuring novel embedding architectures like ExpressivE and region-based neural networks. His work shows strong alignment with database community priorities while pushing boundaries in neural-symbolic integration. Collaborations span international institutions through co-authorships with researchers including Sallinger, Schockaert, Angles, and Gottlob. He actively contributes to academic discourse through conference presentations, including recent work on AI-supported language services for long-term care systems.

• 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.

Aldo Lipaniمشاهده پروفایل

پژوهشگر

• Information Retrieval
• Search Evaluation
• Bias Correction
• +۳ مورد دیگر

Aldo Lipani is a researcher at the E-Commerce Research Area (E194-04) within TU Wien, specializing in information retrieval and search evaluation methodologies. Holding a Dr.techn. doctoral degree, he has maintained consistent research output since 2014 with significant contributions to IR evaluation frameworks. His educational background includes completing his doctoral thesis titled "On Biases in Information retrieval models and evaluation" at TU Wien in 2018. This foundational work established his research trajectory in evaluation bias and normalization techniques. Dr. Lipani's research centers on critical evaluation challenges in information retrieval, with particular expertise in bias correction mechanisms, document length normalization, and pooling strategies for test collection construction. His work addresses high-recall search scenarios essential for systematic literature reviews and e-commerce applications, often developing visualization tools like VoMBaT to analyze evaluation measure behavior. Recent publications demonstrate growing focus on transformer model position bias mitigation and contextualized re-ranking approaches. Analysis of his 15 most recent publications reveals a sustained commitment to improving IR evaluation reliability through methodological innovations. Key trends include the application of fixed-cost pooling strategies to systematic review automation, development of bias correction frameworks, and integration of visualization techniques for evaluation transparency. His work consistently bridges theoretical model improvements with practical applications in academic search and e-commerce contexts. As an active member of TU Wien's Network Lab within the E-Commerce Research Area, Dr. Lipani collaborates extensively on projects involving search system evaluation, systematic review automation, and e-commerce search technologies. His research group maintains strong connections with international IR communities through regular publications at major conferences.

• Artificial Intelligence
• Computational Intelligence
• Database Systems
• +۴ مورد دیگر

Univ.-Prof. Wolfgang Faber is a Professor at the Alpen-Adria-Universität Klagenfurt (AAU), affiliated with the Institute for Artificial Intelligence and Cybersecurity. He holds academic positions in both computer science and engineering disciplines. His research focuses on artificial intelligence, computational intelligence, and theoretical computer science, with particular expertise in answer set programming (ASP), knowledge representation, and formal methods. His work integrates areas like ontology reasoning, action reversibility, and hybrid knowledge bases. Education details are not explicitly stated in the provided text, but his professional trajectory reflects advanced qualifications in engineering and computer science. Research priorities include database systems, semantic technologies, and formal languages, often addressing challenges in meta-reasoning and computational logic. His contributions span theoretical advancements and practical applications, such as ASP-based tools for planning and reasoning systems. Notable research trends include the development of efficient ASP solvers, evaluation of Datalog tools for OWL 2 QL meta-reasoning, and exploration of epistemic logic programs. His work on action reversibility in STRIPS planning and paracoherent answer set computation highlights his focus on bridging formal logic with real-world problem-solving. Collaborations and projects involve international conferences and workshops, including contributions to ICLP, JELIA, and Reasoning Web venues. Wolfgang Faber's professional engagement extends to academic service roles, including membership in the AAU Senate. His research is supported through grants and collaborations, though specific grant details are not provided here. He maintains an active presence in academic communities via ORCID and Google Scholar profiles, with a prolific publication record in top-tier conferences and journals.

Milosh Jovanovikjمشاهده پروفایل

دانشیار

• Knowledge Graphs
• Data Engineering
• Semantic Web
• +۸ مورد دیگر

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.

Martin Schälerمشاهده پروفایل

دانشیار

• Database Systems
• Scientific Data Management
• Hardware-sensitive Database Tuning
• +۵ مورد دیگر

Associate Professor Martin Schäler is part of the Database Research Group at the Department of Computer Science, University of Salzburg. His research focuses on Scientific Data Management, Hardware-sensitive Database Tuning, Time Series Analytics, and Data Provenance. He holds a Dr.-Ing. (PhD) from Otto-von-Guericke University Magdeburg (2014), where he also completed his Master's degree in 2010. Prior to his current position, he was a post-doctoral researcher at the Karlsruhe Institute of Technology's DBIS group (2015-2020). His work emphasizes optimizing database systems through hardware-aware techniques and efficient query processing. Notable contributions include studies on main-memory storage structures, semantic change analysis in text data, and encryption methods preserving distance metrics. He has published in top venues such as IEEE TKDE, VLDB, and ICDE. His academic trajectory includes roles as a research assistant, scientific coordinator, and postdoc researcher before securing his tenure-track position at Salzburg University in 2020. Current research trends show a focus on bridging theoretical database advancements with real-world hardware constraints.

• Databases
• Database Theory
• Complexity Theory
• +۲ مورد دیگر

Christoph Koch is an Associate Professor at Technische Universität Wien specializing in databases and artificial intelligence. His research spans database theory, complexity theory, and logic in computer science, with a focus on XML processing, query optimization, and parallel data science techniques. Lead projects: KnowledgeGraph (2020–2028), HINT (2012–2017), Weblearn (2005–2008) Developed the Lixto visual extraction system and contributed to DLV knowledge representation framework Supervised T. Lukasser's diploma thesis on XPath query processing