جست‌وجوی استاد و پژوهشگر

Patrick Wangمشاهده پروفایل

دانشیار مدعو

• Biomedical Informatics
• Knowledge Graphs
• Natural Language Processing
• +۴ مورد دیگر

Patrick Wang serves as an Adjunct Associate Professor in the Department of Electrical and Computer Engineering at Duke University, teaching courses including IDS 703 Introduction to Natural Language Processing. His primary contact email is patrick.wang@duke.edu. His research spans two major domains: biomedical informatics and computer vision. In biomedical informatics, he specializes in knowledge graph construction (notably ROBOKOP and Biomedical Data Translator systems), biomedical data integration, and hypothesis generation for environmental health and pandemic response. His computer vision work focuses on radar-based systems, autonomous driving algorithms, and object detection techniques leveraging physics-based modeling and camera geometry. Key methodologies include federated data systems, real-time tracking, and spatial resolution optimization. Analysis of his 15 most recent publications reveals a strategic pivot from computer vision (2010-2017) toward biomedical informatics (2018-2022). Early work centered on radar systems and autonomous driving with monocular video, while recent output emphasizes knowledge graphs for COVID-19 data integration, environmental health observations, and universal biomedical data translation. The ROBOKOP framework appears consistently across recent publications, indicating it as his flagship project for federated biomedical knowledge systems. No scientific awards were documented in the provided source material. While his course IDS 703 confirms NLP instruction, no student advising relationships or research grants were specified in the available information. The adjunct position suggests industry collaboration potential, though specific partnerships remain unreported.

• Formal Methods
• Graph Databases
• Database Theory
• +۴ مورد دیگر

Ştefania-Gabriela Dumbravă is an Associate Professor in Computer Science at the École Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE), part of Institut Polytechnique de Paris. She leads the ACMES team at Samovar Laboratory (Télécom SudParis) and participates in international working groups including the Property Graph Schema Working Group and European Research Network on Formal Proofs. Education: PhD in Computer Science, Université Paris-Sud (2016) MSc in Computer Science, Jacobs University Bremen (2012) BSc in Mathematics, Jacobs University Bremen (2010) Research Focus: Her work centers on formal methods for designing and verifying graph database algorithms, with emphasis on: certified database engines, property graph schemas, threshold queries, progressive querying techniques, and knowledge graph evolution. She integrates theorem proving (Coq/Isabelle) with practical database applications. Publication Trends: Her recent works demonstrate strong focus on graph database foundations (schemas, query processing) and practical verification techniques. Publications frequently appear in top-tier venues (VLDB, SIGMOD, ICDE) and emphasize both theoretical rigor and real-world applications in areas like bioinformatics, transportation, and networking. Awards & Honors: EASST Best Software Science Paper (ICGT 2025) ICDE/SIGMOD Distinguished Reviewer Awards (2025) SIGMOD Best Paper & Research Highlight (2023) VLDB Best Paper Runner-Up (2022) Students & Grants: Supervises Master's interns on graph database applications. Leads the ANR JCJC VERDI project (2025-2029) on verified distributed graph systems. Actively recruits PhD candidates for this initiative. Labs & Service: ACMES team at Samovar Lab. Serves on editorial boards (TODS, TGDK) and program committees (VLDB, SIGMOD, ICDE). Coordinates VLDB 2026 Demonstrations Track and co-organizes multiple workshops (GRADES-NDA, TGD).

Damiano Spinaمشاهده پروفایل

مدرس ارشد

• Information Retrieval
• Text Analytics
• Data Science
• +۵ مورد دیگر

Dr. Damiano Spina is a Senior Lecturer in the School of Computing Technologies at RMIT University, Melbourne, Australia. He serves as an Associate Investigator at the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S), the RMIT Research Lead at the Australian Internet Observatory (AIO), and a member of the International Panel on the Information Environment (IPIE). In June 2025, he began a 3-year appointment as an ACM Distinguished Speaker, recognizing his significant contributions to the computing field. Dr. Spina received his PhD in Computer Science from UNED (Spain) in 2014. His academic journey has established him as a leading researcher in information access systems and human-computer interaction. His educational background reflects a strong foundation in computer science with a focus on information retrieval systems. Dr. Spina's research focuses on Information Retrieval (IR), Text Analytics, and Human-AI interaction, with particular emphasis on interactive IR (including conversational assistants) and the evaluation of information access systems. His work bridges theoretical research with practical applications, addressing critical issues such as fairness-aware evaluation, bias detection, and the impact of generative AI on information access. He has developed innovative methodologies that incorporate physiological and cognitive data to better understand user interactions with information systems. His approach often integrates perspectives from cognitive science, behavioral analysis, and ethical considerations to create more effective and equitable information access solutions. His recent publications demonstrate a clear trajectory toward increasingly interdisciplinary research, combining traditional information retrieval with neurophysiological approaches, ethical frameworks, and societal impact assessments. The articles show growing attention to real-world applications, particularly in addressing misinformation, bias in search systems, and accessibility challenges for diverse user groups. His work increasingly incorporates multimodal data and human-centered evaluation methodologies that go beyond traditional relevance metrics. SIGIR 2025 LiveRAG Challenge - First Place Walert - Outstanding Achievement in the 2024 EIP-RACE Demonstrator Competition Award for Excellence in Reviewing ACM SIGIR 2024 Best Presentation Award NTCIR-17 (2023) Best Poster Award Ubicomp-ISWC 2023 RMIT Award for Research Impact (Technology) (2021) ARC Discovery Early Career Researcher Award (DECRA) (2020-2023) Best Short Paper Award ECIR 2020 Best Evaluation Paper Award ECIR 2019 Top Reviewer Award Information Processing & Management (2018) Dr. Spina has supervised numerous PhD and Master's students across diverse research areas including neurophysiological approaches to information retrieval, trust perception in social media, fairness-aware question answering, and sexism identification in social networks. His research has been supported by significant grants including the ARC DECRA award for 'Fair and Transparent Information Access in Spoken Conversational Assistants' (2020-2023) and ongoing projects through the ADM+S Centre. He has also received the 2021 RMIT Award for Research Impact (Technology) for his work's practical applications. Dr. Spina is actively involved with the Australian Internet Observatory (AIO), a national research infrastructure initiative developing tools to analyze digital social data across disciplines. He co-leads the EXIST project series on sexism identification in social networks and has contributed to the Cortana Intelligence Institute (2018-2020) which advanced knowledge on digital assistants. His work often bridges academia and practical applications, particularly in the areas of misinformation management, fairness in information access, and human-AI cooperation.

• Digital Innovation Platforms
• Blockchain Technology
• Fintech
• +۳ مورد دیگر

Ahmad Ghazawneh is a Senior Lecturer at the School of Information Technology , Halmstad University. His research explores the intersection of digital innovation platforms, blockchain technology, and fintech, emphasizing transformative impacts on financial systems and digital economies. Email: ahmad.ghazawneh@hh.se Research Focus: Dr. Ghazawneh investigates blockchain-based financial ecosystems, knowledge graph integration in healthcare, and platform dynamics across multiple domains including mobility systems and social media affordances. Scientific Trends: Recent publications demonstrate expertise in federated health data systems, token-based blockchain ecosystems, conversational AI for healthcare, and sustainable mobility platforms. His work bridges theoretical platform economics with practical implementations.

• Artificial Intelligence
• Big Data
• Human-Robot Interaction
• +۶ مورد دیگر

Diego Reforgiato Recupero is a Full Professor at the Department of Mathematics and Computer Science of the University of Cagliari, Italy, since December 2015. He is the director and creator of the Human-Robot-Interaction Laboratory (http://hri.unica.it) and co-director of the Artificial Intelligence and Big Data Laboratory (http://aibd.unica.it). His roles include quality responsible for the department and membership in the Commission for start-up and spin-off at the University. He teaches multiple courses across disciplines: Computers Architecture for Computer Science bachelor's, Big Data for Computer Science master's, and Web Design and Digital Storytelling for the Master's in Philosophy and Theories of Communication. His research spans interdisciplinary domains including Artificial Intelligence Big Data Analytics Knowledge Graphs Human-Robot Interaction Digital Transformation His scholarly output demonstrates significant focus on AI applications in energy systems (smart grids, district heating), knowledge graph engineering (ontology generation, semantic conversion), and human-centric AI (conversational agents, digital coaching). Publications frequently address data augmentation techniques and transformer architectures across finance, tourism, and mental health domains. He leads the Human-Robot Interaction Laboratory and co-founded the Artificial Intelligence and Big Data Laboratory. His work integrates Apache Spark for big data processing, Unity for synthetic data generation, and RDF/OWL standards for knowledge representation.

Antonia Saravanouمشاهده پروفایل

پژوهشگر

• Data Mining
• Machine Learning
• Anomaly Detection
• +۳ مورد دیگر

Antonia Saravanou is a Ph.D. graduate from the Department of Informatics and Telecommunications at the National and Kapodistrian University of Athens (NKUA), advised by Prof. D. Gunopulos. She holds an M.Sc. in Advanced Information Systems and a B.Sc. in Computer Science from the same department. Since 2011, she has worked as a Research Scientist and Engineer at NKUA and Athens University of Economics and Business (AUEB), and is affiliated with the Knowledge Discovery in Databases Laboratory (KDDLab) and the Management of Data, Information & Knowledge Group (Madgik). Her research spans Data Mining, Machine Learning, and Anomaly Detection, with a focus on Social Network Analysis, Graph Representations, and Healthcare Applications. She has completed research visits at Stanford University's Geometric Computing Group, Spotify Tech Research, and Bloomberg AI. Education: Ph.D., Informatics and Telecommunications, NKUA M.Sc., Advanced Information Systems, NKUA B.Sc., Computer Science, NKUA Her research explores graph-based methods for event detection in social networks, self-supervised node representation learning, and applications in healthcare and news analysis. Projects include music recommendation systems via graph representations, infant mortality prediction models using birth certificate data, and real-time news monitoring frameworks. She has also worked on knowledge graph applications for news ranking and anomaly detection in sparse time series data. Scientific Awards: Outstanding Reviewer for ICLR 2021 Top Reviewer for NeurIPS 2018 As a teaching assistant, she has supported graduate and undergraduate courses at NKUA, including Mining Big Datasets, Data Mining, and Artificial Intelligence. She actively participates in outreach programs like ACM Student Chapter UoA, Rails Girls Athens, and Django Girls.

Nikolaos E. Panagiotouمشاهده پروفایل

پژوهشگر

• Text Mining
• IoT/Smart-Cities
• Spatio-temporal Analysis
• +۳ مورد دیگر

Nikolaos E. Panagiotou is a Research Engineer at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, where he has been working since March 2014. He is also a Ph.D. candidate in Real-time Data Analysis in Massive Streams and Social Media at the same institution under the supervision of Prof. D. Gunopulos. He is an active member of the KDDLAB research group at the University of Athens, participating in EU research projects including INSIGHT and VaVeL. His educational background includes: MSc. with Distinction in Artificial Intelligence, Learning from Data from the School of Informatics, University of Edinburgh (2012-2013) BSc. in Informatics and Telecommunications from the Department of Informatics and Telecommunications, University of Athens (2007-2011) Dr. Panagiotou's research focuses on real-time analysis of high-volume data streams with particular emphasis on text and sensor streams, including news and social media content. His current research interests include: Text Mining: event detection, first story detection, open information extraction IoT/Smart-Cities: sensor analysis, heterogeneous sensor aggregation, real-time visualization Spatio-temporal Analysis: congested road-segments, travel time estimation, OSM His work bridges theoretical research with practical applications in smart city technologies and real-time data processing systems. His publication record demonstrates a strong focus on smart city applications, real-time data processing, and information extraction from diverse data sources. The research shows progression from foundational work on stream mining and event detection to sophisticated applications in urban mobility and news monitoring systems. His most recent work continues to advance techniques for handling sparse data environments and real-time analytics, with particular emphasis on travel time estimation and hybrid analytical approaches. Dr. Panagiotou has been involved in significant EU-funded projects: INSIGHT project: Implementation of real-time analysis modules and visualization engine for the smart city of Dublin VaVeL project: Design of integration schemes and development of real-time analysis modules using spatio-temporal data He has developed multiple demonstration systems including the News Monitor for real-time news analysis and various smart city monitoring dashboards. His technical expertise spans real-time data processing, stream mining, spatio-temporal analysis, and visualization systems, with applications in urban mobility and news monitoring. His collaborative work with researchers across Europe demonstrates his integration into the international research community in data science and smart city applications.

• Database Systems
• Software Engineering
• Conceptual Modeling
• +۵ مورد دیگر

Goran Banjac is a researcher at the Department of Computer Science and Informatics, Faculty of Electrical Engineering, University of Banja Luka. His work focuses on automated conceptual database design, business process modeling, and multilingual database tools. Current projects include AMADEOS (Automated Synthesis of Conceptual Database Models) and EU-funded initiatives. His research spans database systems, software engineering, and model-driven methodologies. Collaborations include Dražen Brđanin, Slavko Marić, and international partners. Recent publications analyze heterogeneous source artifacts, speech-driven design, and UML-based forward engineering. No scientific awards were reported.

Emilio Jesús Gallego Ariasمشاهده پروفایل

پژوهشگر ارشد

• Theorem Proving
• Functional Programming
• Computer Music
• +۷ مورد دیگر

Emilio Jesús Gallego Arias is a non-tenured Research Fellow at the French National Center for Scientific Research (CNRS), hosted at the Institute of Fundamental Computer Research (IRIF) of CNRS and University of Paris Cité. He is also a member of the PiCube Inria team. Previously, he held postdoctoral positions at the University of Pennsylvania (2012–2014) and MINES ParisTech (2014–2019). His research spans mechanically-verified functional and logic programming , with a focus on the Coq proof assistant and the Mathematical Components Library . He develops tools like coq-lsp (language-server for Coq IDEs) and jsCoq (web interface), replacing earlier projects like SerAPI . His work bridges programming language theory , digital signal processing , and formal verification , particularly in the ANR FEEVER project for verifying Faust programs. His 15 most recent works (2014–2024) address type systems , differential privacy , and formal verification in domains like audio processing and mechanism design . Publications span journals (e.g., Journal of Privacy and Confidentiality), conferences (ICML, POPL, FARM), and workshops (CoqPL, UITP). He contributes to open-source projects (GitHub), including DFuzz (linear dependent types), DualQuery (privacy algorithms), and RAM (relational machine). He uses formal methods in collaborative development platforms (Gitter, GitLab) and advocates for free software and accessible audio technology .

• 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)

• Information Systems
• Software Development
• Business Analytics
• +۴ مورد دیگر

Leo Vijayasarathy is Professor and Chair of the Department of Computer Information Systems and Director of the Master of Computer Information Systems (MCIS) program in the College of Business at Colorado State University. He holds an MBA from Marquette University and a Ph.D. in Information Systems from Florida International University. Prior to joining CSU in 2000, he held academic positions at Barry University and North Dakota State University where he served as MIS Coordinator. His research examines the development, use, and organizational impacts of information systems, with emphasis on: Software development methodologies (agile/waterfall selection, testing techniques) Business analytics competence and IT value realization E-commerce adoption and online consumer behavior Database systems and information retrieval effectiveness Supply chain technology integration Recent publications demonstrate strong focus on analytics-driven business value, agile project management, and security in emerging technologies. His work consistently appears in premier journals including Journal of Management Information Systems , IEEE Software , and Information & Management . Awards recognizing his contributions: Mortar Board Award for Excellence in Academic Teaching Outstanding Research Award (NDSU College of Business) Excellence in Service Award (CSU College of Business) Distinguished Service Award (CSU Office of International Programs) He actively mentors graduate students and has secured university grants for teaching/research initiatives. As Director of MCIS, he oversees program development while advising the CIS Student Association and Tech Masters Connect. His editorial service includes the advisory board of Internet Research journal.

• Computer Science
• Artificial Intelligence
• Information Theory
• +۷ مورد دیگر

Anatoly V. Anisimov is a Professor and current Dean of the Faculty of Computer Science and Cybernetics at Taras Shevchenko National University of Kyiv, with a career spanning over five decades. He previously served as Dean of the Faculty of Cybernetics (2004-2016) and has held academic roles ranging from Assistant Professor to Head of Department of Mathematical Informatics. Candidate of Physical and Mathematical Sciences (1972) Doctor of Science (Dr. Sc.) in Physics and Mathematics (1994) Internship at Stanford University (1976-1977) under Donald Knuth His research interests focus on information theory, cryptography, data compression, natural language processing, and algorithm design , with recent work exploring multidelimiter prefix codes, two-base numeration systems, and lightweight authentication protocols for IoT. Over 150 publications and book chapters reflect his contributions to computational linguistics and theoretical computer science. Key article trends reveal a consistent emphasis on encoding techniques, mathematical modeling, and parallel computing , including applications in error correction, semantic analysis, and tensor factorization . His work bridges classical algorithmic theory with modern cybersecurity and AI challenges. Scientific honors include: Glushkov Prize (1994) Soros Professor Grant (1994-1995) State Prize of Ukraine (1998) Honored Worker of Science and Technique (2005) Distinguished Professor Title (2008) Lebedev Prize (2008) Corresponding Member, National Academy of Sciences (2009) Order of Merit (2018) Advising and grants show collaborations with researchers like I.O. Zavadskyi and O.O. Marchenko. He secured international grants (e.g., Soros) and led projects in computational linguistics, information security, and matrix factorization .

• Human-Computer Interaction (HCI)
• User Experience (UX) Design
• Sustainable Interaction Design
• +۴ مورد دیگر

Professor David Benyon, affiliated with the School of Computing at Edinburgh Napier University, is a leading researcher in Human-Computer Interaction (HCI), User Experience (UX) Design, and Blended Spaces. His work bridges digital and physical environments to create sustainable interaction frameworks, notably integrating permaculture principles into UX design. Primary Affiliation: School of Computing, Edinburgh Napier University Research Themes: Sustainable HCI, Blended Spaces, Digital Tourism, Collaborative Interactive Environments Key trends in his publications include: 2024: Explored database concepts and narrative-driven blended experience frameworks 2022: Analyzed spatial interaction, conceptual blending, and medium-specific design theories 2021: Advanced sonification techniques for planetary orbit visualization 2017: Pioneered sustainable HCI through permaculture integration in user experience

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.

• Information Retrieval
• Natural Language Processing
• Applied Machine Learning
• +۷ مورد دیگر

Md Zia Ullah serves as a Lecturer in the School of Computing, Engineering & Built Environments at Edinburgh Napier University, where he contributes to both teaching and research activities. His academic journey includes a PhD from Toyohashi University of Technology (2016), followed by post-doctoral research at French institutions (2017-2022) before joining Napier. He maintains active professional affiliations through memberships in prestigious research groups including the Centre for Algorithms, Visualisation and Evolving Systems and the Centre for Artificial Intelligence and Robotics. B.Sc. (Hons.) from University of Chittagong, Bangladesh (2010) M.Eng. from Toyohashi University of Technology (2013) PhD in Computer Science and Engineering from Toyohashi University of Technology, Japan (2016) Dr. Ullah's research centers on information retrieval systems with particular expertise in query performance prediction, adaptive search strategies, and misinformation detection. His work bridges theoretical advances in machine learning with practical applications in social media analysis and healthcare informatics. He has developed novel approaches for microblog retrieval, semantic expansion techniques, and risk-sensitive search configuration selection that have advanced the field of information access systems. Analysis of his recent publications reveals a strong trend toward addressing misinformation challenges through computational methods, with increasing focus on query performance prediction reliability and selective search strategies. His work demonstrates consistent publication in top-tier venues including SIGIR, CIKM, and ECIR, showing evolution from foundational work on bipartite graph ranking to contemporary challenges in misinformation detection and mental health monitoring through social media analysis. Co-patented adaptive IR technique Active Program Committee member for SIGIR (2018-present), CIKM (2019-present), WSDM (2020-present), SIGKDD (2020-present), ECIR (2019-present), ECMLPKDD (2022-present), CLEF (2017-present) Dr. Ullah currently serves as Co-PI on the Royal Society Edinburgh-funded "False webs: Network to address the misinformation pandemic" project (2023-2025, £19,931), building on his prior involvement in EU Horizon 2020 projects including PREVISION (2019-2021) and FabSpace 2.0 (2015-2018). He supervises doctoral research, notably serving as second supervisor for Katarina Alexander's project on "Developing a Fake News Warning Label." His professional service extends to lecturing data analytics during his post-doctoral period at Université Toulouse I Capitole. Based in the School of Computing, Engineering & Built Environments, Dr. Ullah contributes to research themes in AI and Technologies, particularly within Information Science, Optimization and Learning, and Software Systems. His work connects with practical applications through evaluation forums like TREC, CLEF, and NTCIR where he tests methodologies against benchmark datasets.