XML Data Processing Professors and Supervisors

Tazar Hussainمشاهده پروفایل

مدرس

Ulster UniversityUnited Kingdom

Dr. Tazar Hussain is a Lecturer in Computing Science at the School of Computing, Ulster University , where he teaches deep learning and IoT. He completed his PhD at Ulster University on IoT management frameworks for decision-making under unreliability and worked as a part-time Research Associate on the BTIIC 'Data to Action' project. Previously, he served as a Lecturer at King Saud University (9 years) , securing research funding from NPST and DSU. Education: PhD (Ulster University), MSc in Data Telecommunication and Networks (Salford University), Bachelor of Information Technology (Sarhad University) Research Focus: Deep Learning, NLP, IoT Security, Explainable AI, and Human Activity Recognition (HAR) Projects: Active member of the PwC Advanced Engineering and Research Centre (2021-2026), specializing in Few-Shot Learning and Smart Cities His work bridges IoT systems and cybersecurity , with a focus on intrusion response mechanisms. Publications span machine learning applications in security, risk-based decision frameworks , and C4I systems . He is a certified IBM Security Specialist and trained in smart cities and cloud technologies. Key Trends: 1) Application of Explainable AI in pathology LIS systems, 2) Cognitive modeling for IoT cyberattack responses, 3) Risk-based decision-making in IoT environments, 4) Cost-sensitive intrusion response systems, 5) Formal methods (e.g., Situation Calculus) in cybersecurity Collaborations include Invest Northern Ireland and BTIIC , with expertise aligning to UN Sustainable Development Goals in digital security and smart infrastructure.

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Elisa Bertinoمشاهده پروفایل

استاد

Purdue UniversityUnited States

Elisa Bertino is the Samuel D. Conte Professor of Computer Science at Purdue University, where she also directs the Purdue Cyberspace Security Lab (Cyber2Slab) and serves as Research Director at CERIAS. Since joining Purdue in January 2004, her work has integrated rigorous theory with practical solutions across information security, database systems, and emerging cyber-physical domains. Education Ph.D. in Computer Science, University of Pisa (1980) Research Interests Professor Bertino’s research portfolio is exceptionally broad, spanning information security and assurance , database and data mining technologies , and AI-driven cybersecurity . She pursues foundational advances in access-control models (RBAC, ABAC, trust negotiation), secure data publishing and broadcast protocols for XML and streaming data, privacy-preserving analytics through differential privacy and secure multi-party computation, and zero-trust architectures for 5G/6G and software-defined networks. Application domains include secure mobile and IoT ecosystems, medical informatics, and humanities data. Recent Publication Trends Her 2024–2025 publications reveal a strategic pivot toward next-generation network security (5G/6G, SDN/NFV), trustworthy AI (federated learning, transformer-based malware analysis), and privacy technologies (differential privacy, homomorphic encryption). A recurring theme is the rigorous integration of AI techniques with cryptographic and systems-level defenses to achieve scalable, privacy-preserving security solutions. Scientific Awards & Honors IEEE Fellow ACM Fellow IEEE Computer Society Technical Achievement Award (2002) IEEE Tsutomu Kanai Award (2005) ACM Athena Lecturer Award (2019) Kristian Beckman Award (2020) IEEE 2021 Innovation in Societal Infrastructure Award Advising & Grants Professor Bertino has mentored a large cohort of doctoral students and post-doctoral researchers. Recent externally funded projects include NSF “Privacy-Enhanced Secure Data Provenance” (2011-2016), NIST “Advancing Commercial Participation in the NSTIC Ecosystem” (2012-2013), and Sypris Electronics “Security Techniques for Smart Mobile Devices” (2012). Laboratories & Teams She leads the Cyber2Slab (Cyber Space Security Lab), a vibrant research group investigating insider-threat mitigation, IoT and drone security, digital identity management, cloud data protection, and AI-assisted defense mechanisms. The lab collaborates extensively with federal agencies, industry partners, and international research consortia such as the Data Analytics and Information Science International Technology Alliance (DAIS ITA).

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Costanza Navarrettaمشاهده پروفایل

پژوهشگر

University of CopenhagenDenmark

Costanza Navarretta serves as a Senior Researcher at the Department of Nordic Studies and Linguistics, University of Copenhagen, where she conducts advanced research in computational linguistics and multimodal communication through the Centre for Language Technology. Her work bridges theoretical linguistics with practical applications in digital text modeling and language resource development. Her academic foundation includes: PhD in Computational Linguistics (2002, University of Copenhagen) with dissertation 'The Use and Resolution of Intersentential Pronominal Anaphora in Danish Discourse' Master in Computer Science (1992, University of Copenhagen) with film minor Master in Scandinavian Languages and Literature (1982, University "La Sapienza" of Rome) Visiting studies in Nordic Philology (1980-1982, University of Copenhagen) Navarretta's research centers on multimodal communication systems, computational cognitive science, and intersentential pronominal anaphora. She develops methodologies for annotating and utilizing multimodal corpora while advancing natural language processing techniques for coreference resolution. Her expertise spans language technology, corpus linguistics, machine learning, and XML-based digital text modeling, with particular focus on parliamentary discourse and online interaction environments. As National Coordinator for CLARIN-DK since 2019, she shapes national infrastructure for language resources. Recent publications reveal a concentrated trajectory in parliamentary corpus linguistics, with significant contributions to the ParlaMint project across 20+ European languages. Her work integrates computational analysis of policy domains, gender representation, and sentiment in political debates, demonstrating interdisciplinary convergence between digital humanities, political science, and NLP. The GEHM Zoom corpus project further extends her research into multimodal behavior in virtual environments, reflecting adaptation to contemporary communication contexts. Navarretta actively shapes her field through extensive peer review for LREC, Nodalida, and journals including Natural Language Engineering, while co-organizing annual workshops on multimodal communication. Her leadership includes Programme Responsible for IT and Cognition (2013-2017, 2020-2023) and Head of Studies at the Nordic Research Institute (2015-2017), alongside developing courses at both University of Copenhagen and IT University. Current collaborations through CLARIN and ParlaMint networks demonstrate sustained international engagement in language resource development.

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Ahmed Ezzeldin Khaledمشاهده پروفایل

دانشیار

Northeastern Illinois UniversityUnited States

Ahmed Ezzeldin Khaled is an Associate Professor in the Department of Computer Science at Northeastern Illinois University (NEIU) in Chicago, USA, and a Visiting Associate Professor in the Masters Program in Computer Science at The University of Chicago since March 2024. He joined NEIU in August 2018 after completing his Ph.D. in Computer Engineering from the University of Florida. His educational background includes: Ph.D. in Computer Engineering from University of Florida (2018) M.S. in Computer Engineering from Cairo University (2013) B.S. from Cairo University Dr. Khaled's research focuses on designing systems and applications for distributed systems with the Internet of Things (IoT) as a primary use case. His work spans three main areas: smart healthcare systems and e-Health applications, location-aware services for smart spaces, and utilizing data management techniques for descriptive and predictive analytics. He has developed the Atlas IoT Framework, which includes IoT Device Description Language (IoT-DDL), Atlas Thing Architecture, and Inter-Thing Relationship Framework. His research involves software and hardware platforms from different vendors with various operating environments, focusing on creating interoperable systems for smart spaces. Analysis of Dr. Khaled's recent publications shows a strong trend toward practical implementations of IoT frameworks, particularly in healthcare applications. His work bridges theoretical concepts with real-world deployments, emphasizing context-aware systems, data pipelines, and location-based services. The research demonstrates expertise in creating frameworks that can work across different hardware platforms and communication protocols while addressing specific challenges in healthcare monitoring and smart space development. Dr. Khaled actively mentors students across multiple research domains including IoT applications, healthcare systems, and cloud architecture. His advising approach emphasizes connecting research with teaching, believing that "through the teaching process, we gain a deeper perspective of the subjects we teach and a better view on how the various concepts are linked into a 'bigger picture'." He has developed courses related to operating systems, computer networks, parallel computing, database systems, and the Internet of Things, bringing his research expertise directly into the classroom. Dr. Khaled leads the IoT & Systems Lab at NEIU, which focuses on developing practical IoT solutions for real-world applications. Current active projects include the Atlas IoT Framework for smart spaces, IoMT and Digital Healthcare systems, IoT Emulator (E-IoT) for application development and testing, and Location Based Services for smart tourism. The lab works with various hardware and software platforms to develop and test IoT applications before deployment in real environments, with a particular emphasis on healthcare applications and location-aware services.

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Dominik Freydenbergerمشاهده پروفایل

مدرس ارشد

Loughborough UniversityUnited Kingdom

Dominik Freydenberger serves as a Senior Lecturer and Director of Studies at Loughborough University, affiliated with the Theoretical Computer Science research group since joining in 2017. His academic journey includes a Computer Science degree from the University of Kaiserslautern (2006), doctoral studies at Goethe University Frankfurt am Main (PhD 2011), and postdoctoral positions at Goethe University (until 2015) and Bayreuth University (2015-2017) supported by a Deutsche Forschungsgemeinschaft (DFG) fellowship. His research centers on algorithmic and combinatorial properties of repetition operators in formal models, with significant applications in information extraction systems, real-world regular expressions (including back-reference operators), XML schema inference, and graph database query languages like IBM's AQL. Core disciplines span Database Theory, Formal Language Theory, and Combinatorics on Words, with emerging intersections in Learning Theory. Professional recognitions include a competitive DFG Fellowship and Fellowship of the Higher Education Academy (FHEA), reflecting contributions to both research and academic practice. His work bridges theoretical foundations with practical implementations in data processing technologies.

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