جست‌وجوی استاد و پژوهشگر

• Database Systems
• Big Data Analytics
• XML Processing
• +۷ مورد دیگر

Leonidas Fegaras is an Associate Professor in the Computer Science and Engineering Department at the University of Texas at Arlington's College of Engineering, where he has been employed since 1996, initially as Assistant Professor until 2002 when he was promoted to Associate Professor. His academic journey began with a BEE in Engineering from the National Technical University (1902), followed by an MS in Electrical & Computer Engineering from the University of Massachusetts Amherst (1903), and culminated with a PhD in Computer Science from the same institution in 1992. His educational background includes: PhD in Computer Science, University of Massachusetts Amherst, 1992 MS in Electrical & Computer Engineering, University of Massachusetts Amherst, 1903 BEE in Engineering, National Technical University, 1902 Fegaras's research spans multiple domains within computer science, with a strong emphasis on database systems and big data analytics. His work focuses on developing innovative frameworks for processing large-scale data, particularly in XML, array-based computations, and graph analytics. He has pioneered approaches for query optimization in distributed environments, stream processing, and translation of high-level programming constructs to efficient distributed execution. More recently, his research has expanded into healthcare applications, applying data analytics techniques to clinical data for improved patient outcomes and healthcare decision-making. His interdisciplinary work bridges computer science with healthcare, criminal justice, and environmental science domains. Analysis of his recent publications reveals a clear evolution in his research focus from traditional database systems and XML processing toward modern big data analytics frameworks. His work now heavily emphasizes distributed computing models, particularly leveraging Spark and SQL-based distributed processing. A significant portion of his recent work applies these techniques to healthcare analytics, demonstrating his ability to translate theoretical database concepts into practical applications that address real-world problems in medicine and social sciences. His research shows consistent innovation in query processing techniques across evolving data paradigms. Fegaras has been actively involved in mentoring the next generation of computer scientists, serving as dissertation committee chair for numerous PhD students and supervising many master's theses. His research has been supported by substantial funding from federal agencies including the National Science Foundation and the U.S. Department of Education, with projects totaling over $2 million. Notable grants include the GAANN Doctoral Fellowships in Computer Science and Engineering and several NSF-funded projects focused on big data analytics and database systems. As an educator, Fegaras teaches advanced courses in compilers, web data management, and cloud computing & big data. He has held significant administrative roles including Chairperson of the CSE Graduate Studies Committee since 2009 and membership on the University Graduate Curriculum Committee. His service extends to professional program committees and conference organization, demonstrating his active engagement with the broader computer science research community.

• Digital Innovation
• Internet of Things (IoT)
• Digital Twins
• +۵ مورد دیگر

Nico Adams is a Professor and Optus Chair of Digital Innovation and IoT at James Cook University (JCU), where he also serves as Associate Dean of Industry and Innovation in the College of Science and Engineering. His research focuses on digital twins, IoT applications, and systems science, with a particular emphasis on supporting industries in North Queensland through digital transformation. Previously, he held roles as an Associate Professor at Swinburne University of Technology and Director of Swinburne’s Factory of the Future, pioneering industry-academia collaboration models. He has extensive experience in senior research roles at CSIRO and academic institutions like the University of Cambridge. Education: Doctor of Philosophy (DPhil), University of Oxford Research interests span digital innovation, IoT systems, and the integration of chemical and biological data through ontologies. He has contributed to projects like the Queensland Decarbonisation Hub and flood monitoring systems. His work bridges academia and industry, emphasizing long-term partnerships for technological advancement. Grants and projects include collaborative agreements on decarbonization, drought resilience, and AI-driven flood monitoring. He has authored over 27 publications, focusing on topics like chemical informatics, polymer science, and ontology development.

Michael Burkeمشاهده پروفایل

مدرس پاره‌وقت

• Program Analysis
• Static Analysis-based Tools
• Mobile Security
• +۶ مورد دیگر

Michael Burke is a Senior Research Scientist and Part-Time Lecturer at Rice University's Computer Science Department. He holds a PhD from New York University (1983) and a BA from Yale University (1973). His research focuses on program analysis, static analysis tools, mobile security, parallel computing, and compiler optimization. Previously, he worked at IBM Research for over 25 years, contributing to projects like the PTRAN parallelization system, XJ XML programming language, and Jalapeno Java virtual machine. Dr. Burke has been recognized with numerous awards, including the ACM SIGPLAN Distinguished Service Award (2008), ACM Distinguished Scientist (2007), and IBM Research Division Technical Group Award (2005). He has authored over 60 technical papers and holds multiple patents related to compiler optimization and data analysis. His teaching includes courses on automata theory, compiler construction, and algorithmic thinking. Burke has advised on projects such as the Habanero Multicore Software Research Project and collaborated with organizations like Intel and Lawrence Livermore National Lab on parallel computing frameworks.

John P Bodelمشاهده پروفایل

استاد

• Ancient History
• Classics
• Roman Epigraphy
• +۶ مورد دیگر

John P. Bodel is the W. Duncan MacMillan II Professor of Classics and Professor of History at Brown University. His research focuses on Roman social, economic, and cultural history, with specialties in epigraphy, religion, and Latin literature. He directs the U.S. Epigraphy Project, digitizing and analyzing Greek and Latin inscriptions in the U.S., and co-developed EpiDoc, a semantic markup system for epigraphic texts. His work bridges classical studies with digital humanities, emphasizing interdisciplinary approaches to ancient texts and material culture. Education: PhD in Classical Philology (University of Michigan, 1984), MA (1979) and BA (Princeton University, 1978). Awards include NEH Fellowships, ACLS grants, and international visiting professorships in Rome, Australia, and China. Teaching encompasses Latin language, Roman history, and slavery studies. Major publications include Epigraphic Evidence (2001), Household and Family Religion in Antiquity (2008), and edited volumes on Roman epigraphy and road systems. Current research explores tomb gardens, Roman literacy, and the socio-political roles of inscriptions. Key Projects: U.S. Epigraphy Project (1995–present), EpiDoc digital standards Recent Grants: Mellon Sawyer Seminar ($175K, 2012–2014), French-American Partnership Grant ($301K, 2014–2016) His work on Roman funerary practices and slave trade networks has redefined understandings of ancient social structures. Collaborations with archaeologists and digital humanities experts underscore his commitment to integrating textual and material evidence.

Georgia Koloniariمشاهده پروفایل

دانشیار

• Social Networks
• Graph Databases
• Distributed Systems
• +۴ مورد دیگر

Georgia Koloniari is an Associate Professor at the Department of Applied Informatics, School of Information Sciences, University of Macedonia. She holds a PhD in Computer Science from the University of Ioannina (2009), along with an MSc (2003) and BSc (2001) in Computer Science from the same institution. Her research focuses on distributed systems, graph databases, and peer-to-peer (P2P) systems, with notable contributions to social network analysis, XML data management, and privacy-preserving techniques. She has led or participated in multiple funded research projects, including the Cloud9 project (2011–2014) and the Self-Peer initiative (2005–2008). Her teaching roles include instructing courses such as Distributed Systems , Data Structures , and Advanced Information Systems at the undergraduate level, and IT Infrastructure and Databases at the graduate level. She has also contributed to online educational initiatives, including the development of the Data Structures course in the Open Digital Courses project. Dr. Koloniari’s research interests span social network evolution, graph database management, and distributed data processing. She has published extensively on topics like clustered overlay networks, privacy-preserving record linkage, and temporal query processing. Her work integrates game-theoretic approaches and algorithmic solutions to address challenges in P2P systems and cloud computing. Her recent publications highlight advancements in privacy-preserving techniques (e.g., PRIVATEER toolkit) and time-aware social search systems. She remains active in academic service, serving on program committees for conferences like WWW and EDBT, and reviewing for journals such as IEEE Transactions on Parallel and Distributed Systems. Labs/Teams: Her involvement with the DMOD Lab (Digital Media, Data Management, and Distributed Systems Lab) reflects her focus on interdisciplinary research in data management and distributed computing.

Marcelo Arenasمشاهده پروفایل

استاد

• Data Management
• Semantic Web
• Database Theory
• +۳ مورد دیگر

Marcelo Arenas is a Professor at the Department of Computer Science and the Institute for Mathematical and Computational Engineering at the Pontifical Catholic University of Chile. He is a Fellow of the Association for Computing Machinery (ACM), former director of the Millennium Institute for Foundational Research on Data, and co-founder of the Center for Semantic Web Research. His Ph.D. in Computer Science was obtained from the University of Toronto in 2005. Research interests include data management , applications of logic in computer science , and Semantic Web technologies. He has published extensively on topics such as SPARQL query complexity , graph database systems , and incomplete database theory , with notable works like MillenniumDB and Foundations of Data Exchange . Scientific accolades: 2016 SWSA Ten-Year Award for "Semantics and Complexity of SPARQL" IBM Ph.D. Fellowship (2004) Nine Best Paper Awards across PODS, ISWC, ICDT, ESWC, WWW, and NeurIPS His work on approximate counting algorithms (e.g., FPRAS for #NFA) and explainable AI frameworks has influenced database theory, while serving on program committees for ICDT 2015, ISWC 2015, and PODS 2018 demonstrates leadership in the field. Current projects focus on probabilistic explanations for decision trees and temporal regular path queries in knowledge graphs.

Daniel Weidnerمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Data Mining
• Deductive Databases
• +۵ مورد دیگر

Daniel Weidner is a researcher at the Chair of Computer Science VI (Artificial Intelligence and Knowledge Systems) within the Faculty of Mathematics and Computer Science at the University of Würzburg. His work spans declarative programming, database systems, and artificial intelligence applications. Primary affiliation: Chair of Computer Science VI, University of Würzburg Research focus: AI-driven database systems and logic programming His research interests include declarative technologies, logic programming, and their applications in data mining, tennis analytics, and NoSQL databases. He has extensively contributed to the development of tools that bridge Prolog and Python environments. Weidner has supervised multiple theses and seminar papers, including works on tennis trajectory recognition, heating system data analysis, and declarative program evaluation. His projects often involve Python-based implementations of deductive database systems. Supervised: 4 bachelor's, 2 master's theses Teaching roles: Logic programming, database exercises, and advanced database seminars Scientific awards: No explicit honors mentioned in available records.

Ritu Shandilyaمشاهده پروفایل

دانشیار

• Machine Learning
• Recommender Systems
• Applied Machine Learning (Healthcare & Legal Domain)
• +۵ مورد دیگر

Dr. Ritu Shandilya is an Associate Professor of Computer and Data Science at Mount Mercy University since 2023. She holds a PhD from Iowa State University and has academic credentials from Shobhit University, U.P Technical University, and Kurukshetra University. Her research focuses on machine learning, recommender systems, and their applications in healthcare and legal domains, alongside expertise in big data, search engines, and data mining. Education: PhD, Iowa State University Master of Technology, Shobhit University Master in Computer Application, U.P Technical University Bachelors in Science, Kurukshetra University Her work includes eFeed-Hungers (sustainable feeding systems), MATURE (recommender systems), and eLegPredict (legal judgment prediction). She has collaborated with institutions in India and the U.S., served on editorial boards, and received a Teaching Excellence Award. Dr. Shandilya co-founded eFeed-Hungers.com and continues technical advisory work at eLegalls, LLC. Scientific Awards: Teaching Excellence Award, Iowa State University

• Semantic Web
• Digital Libraries
• Software Engineering
• +۷ مورد دیگر

Gioldasis Nektarios is a Lecturer in the School of Electronic and Computer Engineering at the Technical University of Crete , affiliated with the Distributed Information Systems and Applications Laboratory (TUC/MUSIC) . He has been a permanent member of the laboratory since 2006 and has contributed to numerous Research & Development projects. MSc in Informatics, School of Electronic and Computer Engineering, Technical University of Crete (2002) BSc in Applied Informatics, University of Macedonia (1999) His research interests span critical domains including: Semantic Web technologies and Open Linked Data Software engineering for Service Oriented and Multi-Tier Architectures Data modeling, metadata management, and semantic interoperability Digital libraries and multimedia management systems The article portfolio demonstrates expertise in XML-Semantic Web integration, query mediation, and cultural data systems, with a 2023 publication on location-based game platforms. Key trends include: Interoperability frameworks (2015-2012) Ontology-driven data access (2010-2009) Geospatial and cultural heritage applications (2011-2007)

Olivier Gauwinمشاهده پروفایل

استادیار

• Automata Theory
• Formal Languages
• Logic in Computer Science
• +۶ مورد دیگر

Olivier Gauwin serves as an Assistant Professor at the University of Bordeaux, holding dual roles in academic instruction and research. He teaches within the Computer Science Department at the University Institute of Technology (IUT), while conducting research as a core member of LaBRI's Numeric and Sustainability team. His institutional presence spans both the IUT campus in Gradignan (office 111) and LaBRI's research facilities in Talence (office 311), reflecting his integrated contributions to theoretical computer science and applied sustainability initiatives. His educational trajectory demonstrates deep theoretical foundations: Habilitation à diriger des recherches (HDR) from University of Bordeaux (2020) titled Transductions: resources and characterization PhD in Computer Science from Université Lille 1 (2009) titled Streaming Tree Automata and XPath , conducted at LIFL/INRIA Master's degree (DEA) from Centre de Recherche en Informatique de Lens (2004) titled Fusion itérée de croyances Gauwin's research program bridges abstract theory and practical applications, with early work establishing fundamental results in automata theory for XML stream processing. His investigations into visibly pushdown automata, nested words, and transducers created novel frameworks for efficient query answering in data streams. Recent years show strategic expansion into sustainability, where he adapts formal methods to environmental modeling challenges. This evolution maintains rigorous theoretical grounding while addressing contemporary computational sustainability needs through the Numeric and Sustainability team. Analysis of his 15 most recent publications reveals consistent methodological excellence across theoretical computer science. Core themes include automata minimization (notably proving NP-completeness for visibly pushdown automata), logical characterizations of transductions, and streamability analysis for nested structures. His work demonstrates exceptional coherence—advancing from foundational XML processing (2008-2013) to resource-optimized transducers (2015-2018) and current sustainability applications, always maintaining focus on computational efficiency and formal verifiability. Dr. Gauwin actively mentors the next generation of computer scientists: Supervised PhD completion of Nathan Lhote (2015-2018) on logical characterizations of transductions Guided PhD research of Félix Baschenis (2014-2017) on transducer minimization and resource optimization His research is institutionally supported through LaBRI (UMR 5800), a joint CNRS-University of Bordeaux laboratory, though specific external grants aren't detailed in available materials. Current work continues through the Numeric and Sustainability team, where he integrates automata theory with environmental computation challenges in collaborative projects spanning theoretical innovation and real-world sustainability applications.

Belgin Ergenç Bostanoğluمشاهده پروفایل

دانشیار

• Database Systems
• Data Mining
• Privacy-Preserving Techniques
• +۳ مورد دیگر

Belgin Ergenç Bostanoğlu is an Associate Professor in the Computer Engineering Department at Izmir Institute of Technology (Turkey). Her research focuses on query optimization in distributed databases, association rule mining, privacy-preserving data mining, and graph-based algorithms. She leads the Dworld research laboratory and has held academic and industry roles since the 1980s. Education: B.Sc. in Computer Engineering, Middle East Technical University (1983) M.Sc. in Computer Engineering, Izmir Institute of Technology (2002) Ph.D. in Computer Engineering, Paul Sabatier University, France (2008) Research Interests: Dynamic frequent itemset mining and hiding under multiple support thresholds Subgraph mining in evolving graphs Federated query processing over linked data Privacy-preserving techniques in distributed databases Medical NLP applications (e.g., TurkMedNLI dataset) Her recent work emphasizes large-scale graph analysis, medical NLP dataset development, and adaptive join operators for federated SPARQL queries. She has contributed to over 30 peer-reviewed publications and led projects like the TÜBİTAK ARDEB 3501 platform for dynamic frequent itemset mining. Teaching: Courses include Advanced Database Management Systems, Knowledge Discovery, and Privacy-Preserving Data Mining. Labs & Projects: Manages Dworld lab and coordinates projects such as 'Turkish Medical NLP Model Development' (BAP-funded) and the Behavioral Next Generation Wireless Networks COST Action.

• Cybersecurity
• Mobile Technologies
• Wireless Sensor Networks
• +۵ مورد دیگر

John J Yoon is a Professor of Cybersecurity in the Math/Computer Sciences Department at Mercy College's School of Liberal Arts. He serves as Director of the Mercy College Edge Computing (MCEC) initiative. His research focuses on cybersecurity, mobile technologies, wireless sensor networks, and machine learning applications in network security. Key areas include IoT security, secure coding practices, and distributed data services. His work bridges theoretical advancements with practical implementations, such as deep-learning approaches to IoT threat detection and steganography techniques in Python. Recent publications emphasize edge computing trustworthiness, real-time packet analysis, and collaborative sensor calibration. Notable contributions include an intelligent distance learning framework for heterogeneous online students (2021), a deep-learning IoT attack handling system (2020), and studies on sensor trustworthiness in mobile edge computing (2017-2018). His research spans over three decades with foundational work in XML security (2006) and telecommunications fault management (1993).

• Natural Language Processing
• Computational Linguistics
• Text Analysis Tools
• +۳ مورد دیگر

Francisco Javier Carreras Riudavets is an Associate Professor at the Department of Computer Science and Systems, University of La Laguna. His research focuses on natural language processing, computational linguistics, and the development of specialized software tools for Spanish text analysis. He leads projects like the TIP toolkit, including Estilometría TIP and FreeConj-TIP, which address morphological analysis, syntactic disambiguation, and lexical processing. His work integrates XML-based dictionaries, syntactic tree analysis, and tools for parliamentary text retrieval (DiSeCan). He collaborates with interdisciplinary teams in digital humanities and education, contributing to projects such as Excerpta Search and SententiApp for Latin texts preservation. His teaching innovations include virtual programming labs and concept mapping in computer science education.

• Computer Science
• Data Mining
• Database Systems
• +۷ مورد دیگر

Yi Chen is a Professor at the MT School of Management and Director of the Center for Big Data at New Jersey Institute of Technology (NJIT). His research focuses on database systems, information retrieval, XML processing, privacy/security, and healthcare informatics. He has led numerous NSF-funded projects, including studies on privacy interventions in online publishing ecosystems and meta-information analysis in semi-structured data. Key contributions include work on counter-ad-blocking strategies, GDPR compliance frameworks, and machine learning models for healthcare prediction. He has published over 100 articles in top venues and holds an h-index of 24 with 1,947 citations. Notable awards include recognition in the Japanese Economic Review. Research interests combine computational methods with real-world applications, particularly in privacy-preserving systems, medical data analytics, and workflow optimization. Recent projects explore the impact of transparency frameworks in digital advertising and biomarker extraction using sentiment analysis techniques. His work bridges theoretical advancements with practical solutions for industry challenges. Grants: 11 federal grants including NSF projects on workflow mining, ad-blocking dynamics, and student research initiatives. Lab: Center for Big Data at NJIT, focusing on large-scale data challenges. Publications span key areas like ad viewability prediction, XML search engines (XSeek), and healthcare forum analysis. Collaborations include work on privacy frameworks and optimizing ad auction mechanisms.

• Business Processes
• Blockchain Technology
• Semantic Technologies
• +۵ مورد دیگر

Assoc. Prof. Julius Köpke is an Associate Professor at the University of Klagenfurt's Department of Informatics Systems. His research focuses on business processes, blockchain technology, and semantic interoperability, with particular emphasis on smart contracts, artifact-centric processes, and interorganizational systems. He is affiliated with the Information and Communication Systems research group and contributes to the Institute for Computer Science Systems. Research Interests: - Interorganizational business processes with a focus on blockchain and smart contracts - Application of semantic technologies for data interoperability - Artifact-centric process modeling and data provenance Key Contributions: - Developed SecBPMN2BC framework for secure blockchain-based process modeling - Authored methods for aligning global and local processes, optimizing data-flow implementations - Pioneered lightweight XML-Schema annotation techniques for data translation Recent Work: - Explored LLM-based conversational process modeling tools - Investigated blockchain channel storage for business process data - Published extensively on time-aware processes and temporal constraints Labs/Teams: - Member of the Information and Communication Systems team - Active contributor to the Department of Informatics Systems' research initiatives