جستجوی استاد راهنمای دانشگاهی

Dan Olteanuمشاهده پروفایل

استاد

• Database Systems
• Database Theory
• Artificial Intelligence
• +۷ مورد دیگر

Prof. Dan Olteanu is a full professor at the Department of Informatics, University of Zurich, leading the Data Systems and Theory (DaST) group. He holds visiting professorships at the University of Oxford and is an emeritus fellow of St Cross College. His academic journey includes a PhD from Ludwig Maximilian University (2005), postdoctoral roles at Saarland University and Cornell University, and prior faculty positions at Oxford (2007–2020). He has also worked in industry with companies like LogicBlox and RelationalAI, focusing on database systems and AI. Education: Bachelor’s in Computer Science, Politehnica University of Bucharest (2000) PhD in Computer Science, Ludwig Maximilian University (2005) Professional Roles: Full Professor, University of Zurich (since 2020) Visiting Professor, University of Oxford Emeritus Fellow, St Cross College Editorial Roles: ACM TODS, VLDBJ, SIGMOD Conference Chair: ICDT Council (since 2022) His research focuses on data systems theory, including query optimization, probabilistic databases, factorized databases, and in-database machine learning. He co-authored the seminal book Probabilistic Databases (2011) and has pioneered algorithms for efficient machine learning over relational data and incremental maintenance of analytical workloads. His work emphasizes scalable, theoretically grounded solutions for real-world data challenges. Awards: ICDT 2019 Best Paper Award ACM SIGMOD 2018 Distinguished PC Member Award ERC Consolidator Grant (2016) Oxford Outstanding Teaching Award (2009) Grants & Funding: Supported by Google, Microsoft Azure, Amazon AWS, EPSRC, and the European Commission. His research bridges academia and industry, with contributions to commercial systems like LogicBlox and RelationalAI. Labs & Teams: Heads the DaST group at Zurich, focusing on data systems theory and applications. Collaborates widely in the database and AI communities.

Philip Wadlerمشاهده پروفایل

استاد

• Theoretical Computer Science
• Functional Programming
• Programming Language Foundations
• +۶ مورد دیگر

Philip Wadler is Professor of Theoretical Computer Science at the University of Edinburgh and Senior Research Fellow at IOHK. He is an ACM Fellow, Fellow of the Royal Society, and Fellow of the Royal Society of Edinburgh. His work spans programming language design, type systems, and formal verification, with significant contributions to Haskell, Java, and XQuery. He has held leadership roles in ACM SIGPLAN and served on editorial boards for major journals. Research Interests: Wadler's research focuses on the foundations of programming languages , including Gradual and session typing Language-integrated query Functional and logic programming XML data models Parametricity and free theorems Verification of smart contracts Publication Trends: Recent articles emphasize type safety, formal verification, and blockchain applications. Key themes include gradual typing (blame calculus), session types for concurrency, and logical foundations of programming. His 2015–2025 papers show sustained focus on type theory and language design . Awards & Recognition: POPL Most Influential Paper (2003 for 1993 work) SIGPLAN Distinguished Service Award Best Paper SBMF 2018 Royal Society-Wolfson Fellowship (2004–2009) ACM Fellow (2007) Fellow of Royal Society of Edinburgh (2005) Advising & Grants: He has supervised numerous PhD students in programs like the Centre for Doctoral Training in Pervasive Parallelism. His EPSRC Programme Grant "From Data Types to Session Types" (2013–2020) funded major advances in concurrency theory. Current work with IOHK explores blockchain verification using Haskell-based Plutus.

• Network Security
• Data Security
• Cryptography
• +۵ مورد دیگر

Prof. Dr. Jörg Schwenk is a Professor and Chair of Network and Data Security at Ruhr-University Bochum's Faculty of Computer Science. He has held this position since 2003 and serves as Deputy Managing Director of the university's Computer Center. From 2007 to 2010, he was Managing Director of the Horst Görtz Institute for IT Security. His office is located at Universitätsstr. 150, 44801 Bochum (Room MC 4/110), with contact via email at joerg.schwenk@rub.de. His research focuses extensively on practical aspects of information security, particularly in: Cryptographic protocol analysis (TLS, SSH, Noise Protocol) Web and browser security vulnerabilities (XS-Leaks, DOM security) Document security flaws in PDF, OOXML, and OpenDocument formats Email encryption weaknesses and authentication mechanisms Network security implementations and powerline communications Recent publications demonstrate a strong emphasis on discovering and mitigating critical vulnerabilities in widely used protocols and file formats. His work frequently involves developing automated analysis tools (e.g., TLS-Anvil, XSinator) and reveals systemic security issues in standards implementations. Research outputs consistently target top-tier security venues (USENIX Security, CCS, NDSS) with findings that directly impact real-world systems. Schwenk leads a research group at the Horst Görtz Institute focusing on network and data security. The group maintains an active publication record in applied cryptography and systems security, frequently collaborating with industry partners to address emergent threats. His team's work on TLS vulnerabilities (ALPACA, Raccoon attacks) and document security (PDF/OOXML signature flaws) has significantly influenced protocol designs and standardization efforts.

Miloš Rackovićمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Databases
• +۴ مورد دیگر

Miloš Racković serves as a full Professor in the Department of Mathematics and Informatics at the University of Novi Sad, Serbia. He maintains active academic engagement through the Laboratory for the development of information systems, with his office located in the Information technologies and systems office (DMI&DF) on the second floor, room 49. Contact is available via telephone (485)-2868 or email rackovic@dmi.uns.ac.rs, and his personal website (http://www.is.pmf.uns.ac.rs/rackovicm/) provides additional resources. His research spans foundational and applied computer science, with seminal contributions in fuzzy database systems including PFSQL query language development and prioritized fuzzy logic for relational databases and XML. He has pioneered deep learning methodologies through innovative classification techniques using negative and missing features in convolutional neural networks. Additional expertise includes high-performance computing implementations of Lattice Boltzmann methods using OpenCL, robotics (symbolic modeling and trajectory planning), and blockchain applications for Industry 4.0 production processes. His sports analytics work applies neural networks to basketball player and referee movement analysis. Analysis of his 2012-2025 publications reveals a strategic evolution toward interdisciplinary applications, particularly in industrial transformation (blockchain-enabled traceability) and sports analytics. His work consistently bridges theoretical computer science with practical implementations, demonstrating increasing focus on real-world problem solving while maintaining strong foundations in database theory and computational methods. Professor Racković leads the Laboratory for the development of information systems, which focuses on advancing information system methodologies through formal modeling extensions (including Petri net innovations) and practical implementations for uncertainty management. The laboratory's work spans from foundational research in fuzzy logic systems to applied projects in high-performance computing and blockchain integration, fostering innovation in information technology development.

• Databases
• Data Management
• Provenance Analysis
• +۶ مورد دیگر

Val Tannen is a Professor at the University of Pennsylvania, specializing in database systems, provenance analysis, and programming languages. His research focuses on data management, query languages, and systems like DBSP and ORCHESTRA. Collaborations include work with co-authors such as Zachary Ives, Susan Davidson, and Todd Green. Key research interests include provenance for databases, incremental view maintenance, and data integration. His work bridges theoretical foundations and practical applications in systems like DBSP for stream processing and ORCHESTRA for collaborative data sharing. Publications span provenance frameworks, query optimization, and distributed systems. While no awards are explicitly listed, his contributions to database theory and systems are widely recognized.

Foto N. Afratiمشاهده پروفایل

استاد

• Parallel and distributed computation
• Processing of very large data
• MapReduce
• +۶ مورد دیگر

Professor Foto N. Afrati is a Distinguished Faculty Member at the National Technical University of Athens, specifically within the School of Electrical and Computing Engineering and the Division of Communication, Electronic and Information Engineering. She has held this position since 1993, following previous academic ranks at the same university as Associate Professor (1989-1993), Assistant Professor (1985-1989), Lecturer (1982-1985), and Research Fellow (1980-1982). She completed her PhD in Electrical Engineering at Imperial College of the University of London in March 1980, with a dissertation focused on Error Correcting Codes by Algorithms. Her academic journey also included a Diploma from Imperial College (March 1980) and an earlier Diploma in Electrical and Mechanical Engineering from the National Technical University of Athens (June 1976). Professor Afrati's research interests span several critical areas in computer science: Parallel and distributed computation Processing of very large data (including MapReduce) Data and web mining Database Systems Information integration Query optimization Computation and complexity of algorithms Approximation algorithms Her most recent publications demonstrate expertise in MapReduce environments, query optimization with views, and data exchange frameworks. These works are published in prestigious venues like EDBT, VLDB, PODS, and ICDT, with specific focus areas including adaptive sampling techniques, data source integrity, and algorithm complexity in database environments. Professor Afrati has received significant recognition in her field, including Fellow of the Association for Computing Machinery (ACM) Best Paper Award at the International Conference on Database Theory (ICDT) 2009 She has advised numerous PhD students throughout her career, including Theodoros Mitakos, Ezz Hattab, Nikos Kiourtis, and Angelos Vasilakopoulos. Her current PhD students include Victor Kyritsis and Nikos Stassinopoulos. Professor Afrati maintains strong professional networks through her various visiting positions at institutions such as Google, Stanford University, IBM Research Center, University of Helsinki, University of Paris, DIMACS, and others. She has served as associate editor and reviewer for major academic journals and conferences including IEEE TKDE, ACM Transactions of Database Systems (TODS), Journal of ACM (JACM), and Theoretical Computer Science (TCS). Her extensive work in research projects spans both national and international initiatives, with funding from sources including the European Union's Thalis project, ESPRIT working groups, HCM networks, and Greek General Secretariat of Research and Technology grants.

Tova Miloمشاهده پروفایل

استاد

• Databases
• Big Data Management
• Machine Learning for Data Management
• +۷ مورد دیگر

Professor Tova Milo is the Chair for Information Management at the School of Computer Science, Tel Aviv University, leading the prominent Databases Lab (DB Group). Her research spans databases, big data management, crowd-based data sourcing, and business process querying, with significant contributions to data integration and semi-structured data systems. Her research interests focus on innovative approaches to data management challenges through machine learning integration, crowd computing, and business process analysis. Key projects include Business Process Querying (BPQ) for analyzing BPEL specifications, MoDaS for crowd-based data management, and PROX for data provenance summarization. Her work bridges theoretical foundations with practical applications in fraud detection, recommendation systems, and data cleaning. Analysis of her recent publications reveals strong trends in human-in-the-loop data management systems, with growing emphasis on crowd integration for data cleaning and knowledge acquisition. Her research increasingly combines traditional database theory with machine learning techniques for scalable big data processing, while maintaining focus on business process modeling and provenance tracking. ACM PODS Alberto O. Mendelzon Test-of-Time Award (2010) ERC Advanced Investigators grant MoDaS (2011) The Weizmann Prize for Exact Sciences (2017) VLDB Women in Database Research award (2017) IEEE TCDE Impact award (2022) ISF Breakthrough Research Grant (2022) Doctorate Honoris Causa, University of Zurich (2023) ACM Fellow Member of Academia Europaea Professor Milo has advised over 30 graduate students including PhD candidates like Yael Amsterdamer and Ohad Greenshpan, and numerous MSc students working on projects including MoDaS, BPQ, and EDOS. Her research has been supported by major grants including the ERC Advanced Investigators grant and ISF Breakthrough Research Grant. She actively collaborates with industry partners including IBM and Microsoft, particularly in business process management standards. She directs Tel Aviv University's Databases Lab, which maintains the DB Group with multiple research streams including business process querying (BPQ), crowd-based data management (MoDaS), and self-adaptive data dissemination (EDOS/COLT). The lab operates from the Schreiber Building (M-20) and maintains strong international collaborations, particularly with European institutions through the ERC-funded MoDaS project.

• Database Systems
• Data Management
• Graph Databases
• +۵ مورد دیگر

Alin Deutsch is a Professor of Computer Science at the University of California, San Diego (UCSD), specializing in database systems, graph databases, and formal verification. He has contributed significantly to research areas including query optimization, data integration, and privacy-preserving systems. His work spans theoretical foundations and practical implementations, such as the Linked Data Benchmark Council (LDBC) and the TigerGraph database system. He co-authored over 100 papers and has been involved in major conferences like SIGMOD and VLDB. Research interests include graph query processing, parallel computing, data-centric business processes, and automated system verification. Recent work focuses on scalable hybrid analytics and graph databases. Deutsch is also active in database education, co-authoring a paper on UCSD's database curriculum. He has led projects in privacy-aware systems, such as policy-aware location-based services, and contributed to tools like CLIDE for interactive query formulation in service-oriented architectures. His collaborations involve industry partners like TigerGraph and academic institutions globally.

• Databases
• Information Systems
• Data Management
• +۹ مورد دیگر

Johann Eder is a full professor for Information and Communication Systems at the Department of Informatics Systems, University of Klagenfurt, Austria, and currently serves as Deputy Head of Department. He previously held positions at the Universities of Linz, Hamburg, Vienna, and Klagenfurt, and was Vice President of the Austrian Science Funds (FWF) from 2005-2013. He was also a visiting scholar at AT&T Shannon Labs, NJ. Educational Background: Diplom-Ingenieur, University of Linz Doctor of Technical Sciences, University of Linz Johann Eder's research focuses on databases, information systems, and data management for medical research, including temporal information modeling, process evolution, and workflow systems. His work spans temporal data warehousing, exception handling in workflows, and application interoperability, with a particular emphasis on privacy and quality in medical data lakes and federated biobanks. Recent publications highlight trends in temporal reasoning for business processes, medical data quality, and service composition optimization. His editorial roles include positions at ACM Transactions on Database Systems and IEEE Transactions on Knowledge and Data Engineering . He leads the Information and Communication Systems Research Group at AAU, contributing to projects like federated biobank integration and blockchain-based smart contracts.

Marco Mesitiمشاهده پروفایل

دانشیار

• Data Management
• Big Data Visualization
• Data Integration
• +۶ مورد دیگر

Marco Mesiti is an Associate Professor at the Department of Computer Science, University of Milan, Italy. He holds a PhD and Laurea in Computer Science from the University of Genova. His research focuses on data management, big data visualization, and bioinformatics, particularly in biomolecular networks and IoT data. He is a member of AnacletoLAB and has contributed to developing tools like UNIPred-Web for biomolecular network analysis. Education: PhD in Computer Science, University of Genova, 2003 MSc in Computer Science, University of Genova, 1998 Laurea (BSc equivalent) in Computer Science, University of Genova (cum laude) Research Interests: His work spans XML data handling, semistructured data, and applications in bioinformatics, IoT, and credit worthiness. He explores approaches to manage heterogeneous data, including visualization techniques and knowledge graph construction. Recent projects include RNA-centered knowledge graphs and GPU-based algorithms for large networks. Publications: Recent work includes advancements in machine learning for protein design, RNA interaction analysis, and multi-omics data integration. His research emphasizes scalable methods for biomolecular networks and visual analytics tools. Grants & Collaborations: Involved in projects like ELISE and MUSE. Collaborates internationally on bioinformatics and computational biology initiatives. Labs & Teams: Member of AnacletoLAB, focusing on machine learning and data science applications.

• Data Modeling
• Data Security and Privacy
• Healthcare Data Management
• +۵ مورد دیگر

Faiz Currim serves as Professor of Practice in Management Information Systems and Assistant Director of the INSITE: Center for Business Intelligence and Analytics at the University of Arizona's Eller College of Management. He joined the institution in 2011 after six years at the University of Iowa, having earned his PhD from the University of Arizona in 2004. His educational background includes: PhD in Management Information Systems, University of Arizona (2004) Dr. Currim's research focuses on data modeling, security, privacy, and specialized management of healthcare, temporal, and spatial data systems. His work bridges database theory with practical applications in urban mobility, patient care, and workplace wellbeing through advanced techniques including deep learning, network science, and big data analytics. Current projects address real-world challenges in healthcare analytics and smart city infrastructure. Analysis of his recent publications reveals strong trends in applying artificial intelligence to healthcare cost prediction and urban transportation systems, with consistent use of heterogeneous data sources and machine learning frameworks across diverse domains from patient monitoring to bike-sharing optimization. His scientific recognition includes: Best Paper Award at IEEE 2nd International Smart Cities Conference (2016) Dr. Currim directs the INSITE center's initiatives in business intelligence while teaching core courses including Enterprise Data Management and Business Data Communications. His academic leadership spans curriculum development in data security, XML schema, and spatial database applications, with active collaboration across healthcare and urban planning domains. He maintains leadership roles in professional organizations including the Association for Information Systems (AIS), INFORMS, and Association for Computing Machinery (ACM), driving interdisciplinary research through the INSITE center's industry partnerships and analytics projects.

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

Mirian HALFELD-FERRARI is a Professor at the University of Orleans , where she serves as Director of the Pamda Laboratory, member of the Sustainable Development Working Group, and International Relations Manager. Her research focuses on database systems, semantic web technologies, and graph data management. Key contributions include graph rewriting systems , RDF database evolution , and data consistency frameworks . Recent work explores clinical text-to-knowledge graphs , XML schema evolution , and context-driven urban data analysis . She collaborates with researchers across Europe on projects involving graph data science , service composition refinement , and semantic web sanitization . Her leadership roles include organizing workshops at conferences such as ADBIS and serving on editorial boards for international journals.

Dietmar Seipelمشاهده پروفایل

استاد

• Logic Programming
• Deductive Databases
• Knowledge Engineering
• +۵ مورد دیگر

Dietmar Seipel is a Professor at the University of Würzburg, affiliated with the Department of Computer Science within the Faculty of Mathematics and Computer Science. He has held this position since November 1995, establishing a distinguished academic career spanning over 25 years with significant contributions to logic-based computer science. Professor Seipel's research focuses on Logic Programming and Deductive Databases, with substantial expertise in Knowledge Engineering and Artificial Intelligence. His scholarly work bridges theoretical foundations with practical applications, particularly in rule-based systems, knowledge representation, and declarative programming paradigms. He has consistently advanced the field through both theoretical developments and practical implementations, creating tools that enable more effective knowledge management and reasoning systems. His publication trajectory demonstrates a clear evolution from foundational work in disjunctive logic programming to contemporary applications in knowledge representation and semantic technologies. Recent research shows continued innovation in integrating logic programming with modern programming languages and systems, including Python and JavaScript implementations. His work spans theoretical contributions to practical tool development, with applications across diverse domains including space systems, medical informatics, and business process management. Professor Seipel has made extensive contributions to the academic literature, with publications appearing consistently from the 1980s through to the present. His work has influenced both theoretical developments in logic programming and practical applications in knowledge-based systems. He has been actively involved in academic community building through conference organization, particularly for events related to declarative programming and knowledge management.

Dario Colazzoمشاهده پروفایل

استاد

• Databases
• Programming Languages
• Cloud Computing
• +۷ مورد دیگر

Dario Colazzo is a Professor at Université Paris-Dauphine, affiliated with the LAMSADE laboratory. His research focuses on database systems and programming languages, particularly in cloud databases, type systems for semi-structured data, and query processing optimizations. He has contributed extensively to XML and XQuery research, including parallel query execution and static analysis techniques. His teaching includes courses on programming (Java), UML, database systems, and semantic web technologies at both undergraduate and graduate levels (in French). Key research interests span XML/XQuery optimization, JSON processing, distributed systems, and type systems for safe and efficient data handling. His work emphasizes scalable cloud-based solutions and efficient query execution models. Publications highlight advancements in parallel query processing (e.g., PAXQuery), type-based optimizations for XML updates, and semantic graph analytics. He has collaborated with institutions like EDBT, WWW, and VLDB conferences.

Kerstin Schneiderمشاهده پروفایل

استاد

• Databases
• Data Engineering
• Workflow Management Systems
• +۴ مورد دیگر

Kerstin Schneider is a full-time Professor for Databases at Harz University of Applied Sciences since 2007. She operates within the Faculty of Automation and Informatics , focusing on database theory, data engineering, and AI-driven educational technology solutions. Current research emphasizes adaptive e-learning platforms (ALEA system) Interdisciplinary projects in AI Engineering (AiEng 2021-2025) Custom database applications for SMEs (TEA project) Her research interests span: Reliable workflow execution in distributed systems Multimedia information systems Semantic data recommendations Temporal XML database models Recent publications (2021–2017) highlight trends in: Academic database foundations Intelligent e-learning architectures Life science data analytics Historical data visualization Scientific Awards : 2004 Research and Innovation Award of the Rhine-Neckar Triangle Foundation She contributes to academic governance through roles in: Steering Committee for Fundamentals of Databases Examination Board AI Engineering Senate Deputy at Harz University Equal Opportunities Officer for AI Department Key collaborative projects include: APRICOTS (CORBA-based workflow systems) GEIST (Intelligent History Information Systems) Team projects with international universities Open Educational Resources (OER) development