جست‌وجوی استاد و پژوهشگر

• Digital Humanities
• Language Technology
• Computational Linguistics
• +۵ مورد دیگر

Prof. Dr. Franciska de Jong is a Full Professor of e-Research for the Humanities at Utrecht University's Department of Languages, Literature and Communication. She serves as senior advisor to CLARIN ERIC, Europe's language resources infrastructure, following her tenure as its Executive Director (2015-2022). Her career includes roles as Full Professor of Language Technology at the University of Twente (1992-2022) and affiliations with Erasmus University Rotterdam. She has led national and international initiatives including the Dutch 'Driven by Data' program and Horizon Europe's EOSC Focus project. Key roles: CLARIN ERIC Senior Advisor NWO Standing Committee Member (2018-present) Open Science-NL Steering Board (2023-present) Education: PhD Theoretical Linguistics (Utrecht University), MA Dutch Language & Literature. Early career included machine translation work at Philips Research. Research focuses on digital libraries, cultural heritage digitization, text mining, and cross-language retrieval systems. Recent projects emphasize FAIR data principles, open science infrastructure, and sustainability of the European Open Science Cloud. Active in governance bodies like Netherlands eScience Center (2014-2023) and Lorentz Center's Computational Science Advisory Board (2016-2021).

• Cryptocurrencies
• Blockchain Interoperability
• Blockchain Scalability
• +۳ مورد دیگر

Giulia Scaffino is a PreDoc Researcher in the Security and Privacy group at the Technical University of Vienna (TU Wien). Her research focuses on cryptocurrencies, blockchain interoperability, scalability, off-chain protocols, and decentralized finance (DeFi). She holds an MSc in Nuclear and Particle Physics from the University of Pavia, Italy, and is pursuing a PhD at TU Wien. Before her PhD, she worked as a Salesforce developer at Deloitte Digital in Milan. Giulia is involved in projects such as CDL-BOT (2020–2025), Browsec (2018–2024), CoRaF (2022–2025), and SFB SPyCoDe (2023–2026). Her work includes developing frameworks for cross-blockchain smart contracts, optimizing light clients for DeFi, and creating scalable blockchain bridges. She has contributed to publications on topics like IoT data marketplaces and distributed key generation using zk-SNARKs. Her research trends emphasize solving blockchain scalability challenges through innovative protocols and enhancing interoperability between different blockchain systems. Projects like Glimpse and Alba highlight her focus on efficient, secure, and decentralized solutions for modern blockchain ecosystems.

Francis Gacengaمشاهده پروفایل

پژوهشگر

• Research Data Management
• IT Service Management
• Design Science
• +۳ مورد دیگر

Dr. Francis Gacenga, currently at the University of Southern Queensland (UniSQ), serves as a Senior Digital Research Advisor in the Research Infrastructure Admin department. He is affiliated with the Centre for Sustainable Agricultural Systems and Institute for Advanced Engineering and Space Sciences. PhD in Information Systems (USQ, 2013) MBA (University of Nairobi, 2000) Graduate Diploma in MIS (University of Greenwich, 2003) BA(Hons) from Kenyatta University (1997) With over 20 years of experience in IT and academic research, Dr. Gacenga specializes in Research Data Management (RDM), IT Service Management (ITSM), Digital Research Infrastructure, and Design Science. His work focuses on applying FAIR (Findable, Accessible, Interoperable, Reusable) data principles to agricultural and environmental domains. The 15 most recent publications reveal a trajectory from foundational ITSM research (2010-2016) to agricultural data platforms (2019-2024). Key themes include FAIR data implementation, cloud computing integration, reproducible research frameworks, and cross-disciplinary agricultural applications. Senior Member of Australian Computer Society (since 2009) Former Chair of ACS Toowoomba Chapter As Principal Investigator for grants totaling over $500k from GRDC, Soils CRC, and ARDC, he leads digital infrastructure projects. He also supervises Doctoral candidates and contributes to national cybersecurity and data policy committees.

• Computer Science
• Database Systems
• Process Mining
• +۴ مورد دیگر

Andreas Manfred Pointner is an Assistant Professor at FH Hagenberg , specializing in interdisciplinary research at the intersection of computer science, healthcare informatics, and software engineering. He leads research in graph databases, process mining, and attribute grammars with applications in healthcare IT and automated data systems. His affiliations include the Web Intelligence and Innovation Laboratory , AIST Center of Excellence , and Medical Engineering/TIMed Center . He has contributed to projects such as RiskAI (risk management in enterprises), PASS (plan analysis automation), and REPO (radiology e-health platforms). Research Interests: Graph database optimization, interoperability in healthcare systems (HL7 standards), fuzzing techniques for software testing, and process mining for audit event analysis. His work bridges theoretical formal methods with practical applications in clinical workflows and automated data cleansing. Notable Contribution: Developed a graph transformation framework for complex data structures Recipient of the Best Paper Award 2022 for contributions to intelligent systems Collaborative Projects: Focus on AI-driven solutions for enterprise risk management and healthcare interoperability He actively participates in international conferences and has supervised projects involving 3D model analysis, contour extraction, and global disease monitoring systems.

• Data Governance
• Semantic Modeling
• Knowledge Graphs
• +۵ مورد دیگر

Zaiwen Feng is a researcher actively contributing to data governance, semantic modeling, and causal inference. His work focuses on knowledge graphs, graph-based methods, and service-oriented architectures through collaborations with institutions like the University of Queensland and universities in China. Research Focus : Graph Differential Dependencies, Entity Resolution, Causal Effect Estimation, and Ontology Alignment Methodologies : Machine Learning, Variational Autoencoders, Prompt Engineering, and Semantic Retrieval Application Areas : Biomedical Data, Property Graph Recommendation, and Process Model Repositories Key trends in his publications include automated semantic modeling , neural approaches for entity resolution , and causal inference with graph structures . He frequently collaborates with researchers like Keqing He, Wolfgang Mayer, and Selasi Kwashie across conferences such as HPCC, BIBM, and WISE.

Jacqueline Griffinمشاهده پروفایل

دانشیار

• Healthcare Operations Research
• Supply Chain Resilience
• Discrete Event Simulation
• +۴ مورد دیگر

Jacqueline Griffin is an Associate Professor in Mechanical and Industrial Engineering at Northeastern University's College of Engineering, serving as Director of Industrial Engineering and Operations Research. She holds a PhD from Georgia Institute of Technology (2012) with prior degrees from Lehigh University. Her research focuses on healthcare operations optimization, supply chain resilience, and decision-making under uncertainty, with emphasis on multi-objective resource allocation, simulation modeling, and stochastic optimization. She leads NSF-funded projects addressing pharmaceutical supply chain resilience and outpatient clinic design. Notable awards include the ARCS Foundation Fellowship and Omega Best Reviewer Award. Griffin's research integrates operations research methods to improve healthcare systems, including dynamic bed management, disaster preparedness algorithms, and patient flow optimization. She has designed simulation frameworks for hospital layouts and emergency response systems. Her work spans academic-industry collaborations with Brigham and Women’s Hospital, Boston Children’s Hospital, and the National Institutes of Health. Education: PhD Industrial Engineering (Georgia Tech 2012), MS/BS Industrial Engineering (Lehigh 2006/2005) Grants: $1.5M in NSF funding for supply chain resilience and healthcare systems projects Professional Affiliations: INFORMS, IIE, POMS Her teaching includes graduate courses on operations research and supply chain management. Recent innovations include gamified educational tools for supply chain decision-making and EHR-integrated diagnostic safety interventions. She advises interdisciplinary teams on healthcare system modeling and has published over 30 peer-reviewed articles since 2011.

• Cloud Computing
• Distributed Systems
• Data Processing
• +۴ مورد دیگر

Luis Antunes Veiga is an Associate Professor and Senior Researcher at INESC-ID Lisbon, affiliated with the Distributed Systems Group and the Computing Systems and Communication Networks Laboratory. His research focuses on Cloud Computing, Edge Computing, Distributed Systems, and Big Data processing. He teaches courses such as 'Cloud Computing and Virtualization' and 'Operating Systems, Virtualization and Cloud Computing.' His work emphasizes scalable systems, network-aware workflows, and resource-efficient data processing. Research Interests: His primary areas include distributed systems architectures, edge computing frameworks, graph processing algorithms, and software-defined systems. He explores topics like latency-aware network design, resource auction mechanisms for edge environments, and interoperable service workflows. His contributions span theoretical frameworks and practical implementations, such as the RATEE system for edge resource trading and the VeilGraph incremental graph processing framework. Publications: His recent work addresses challenges in distributed systems, such as elastic scaling of stream processing, efficient graph processing in Spark, and latency optimization in internet-scale workflows. These publications reflect a trend toward integrating software-defined approaches with edge and cloud infrastructures. Notable Awards: Best Young Researcher INESC-ID, Excellence in Teaching (IST 2012), and a Best-Paper Award at ACM/IFIP/Usenix Middleware 2007. Labs & Teams: Active in the Computing Systems and Communication Networks Laboratory, leading projects on edge computing and distributed systems.

• Transportation Engineering
• Intelligent Transportation Systems
• Infrastructure Resilience
• +۷ مورد دیگر

Sean Qian is a Professor at Carnegie Mellon University (CMU), jointly appointed in the Department of Civil and Environmental Engineering, Heinz College of Information Systems and Public Policy, and the Department of Electrical and Computer Engineering. He directs the Mobility Data Analytics Center (MAC) and co-founded TraffiQure Technologies to commercialize AI-driven infrastructure solutions. His research focuses on dynamic network modeling, intelligent transportation systems, climate resilience, and infrastructure interdependency. Supported by NSF, U.S. DOT, and industry partners, his work integrates AI, big data, and policy analysis to address urban mobility challenges. Education: PhD in Civil Engineering (UC Davis, 2011), MS in Statistics (Stanford, 2012), and dual MS/BS in Civil Engineering (Tsinghua University, 2006/2004). Research emphasizes smart cities, EV integration, cybersecurity for infrastructure, and equity in mobility policies. He serves on editorial boards for Transportation Research journals and TRB committees. Awards include the NSF CAREER Award (2018) and Greenshields Prize (2017). Grants and collaborations include projects with Fujitsu, IBM, and state agencies, addressing curbside management, climate adaptation, and rural mobility. His lab develops tools like the Rural Access Mobility Platform and social digital twin technologies for infrastructure resilience.

• Smart Grid
• IoT Data Management
• Cloud Resource Management
• +۳ مورد دیگر

Thanasis Papaioannou is a Senior Researcher at the STEcon lab at Athens University of Economics and Business (AUEB), where he has been since 2006. He concurrently teaches Python Programming and Android Programming at the University of Thessaly and Data Management in IoT at the Technological Educational Institute of Thessaly. His research focuses on smart grid demand-side management, IoT data management, gamification for energy conservation, and privacy mechanisms in distributed systems. Education: He holds a B.Sc. (1998), M.Sc. (2000) in Computer Science from the University of Crete, and a Ph.D. (2006) in Informatics from AUEB. He has held postdoctoral roles at EPFL (2008-2013) and positions at CERTH (2013-2016). Research Interests: His work spans IoT-enabled gamification for energy efficiency, decentralized management frameworks, and blockchain applications for trustworthy systems. Notable contributions include frameworks like ONTOCHAIN and CHArGED, addressing challenges in energy conservation and distributed trust. Publications: Over 65 papers in high-impact venues including IEEE Transactions on Smart Grid and ACM e-Energy. Recent work emphasizes blockchain-semantic convergence, decentralized IoT governance, and energy market coordination under uncertainty. Professional Impact: Project manager in 17 national/EU projects, with over 1200 citations. Advises on energy systems and decentralized technologies, emphasizing user-centric design and behavioral interventions.

Jianliang Wuمشاهده پروفایل

استادیار

• Systems Security and Privacy
• Formal Analysis
• Machine Learning Security and Privacy
• +۴ مورد دیگر

Jianliang Wu is an Assistant Professor in the School of Computing Science at Simon Fraser University. His research focuses on systems security and privacy, formal analysis, and machine learning security. He holds a PhD from Purdue University (2022), and MSc and BSc from Shandong University (2015 and 2012). His research interests include Bluetooth security, IoT privacy, and formal methods for protocol analysis. He teaches courses such as Network Security, Software Security, and Networks, including CMPT 403 (System Security and Privacy) and CMPT 479 (Special Topics in Computing Systems). His work spans both theoretical and applied cybersecurity, with a strong emphasis on real-world system vulnerabilities and mitigation strategies. Recent research highlights include systematic reviews of Bluetooth protection strategies, analyses of IoT data exposure via companion apps, and formal model-driven discovery of protocol design flaws. His contributions address critical challenges in wireless communication security and IoT ecosystem vulnerabilities. No scientific awards are explicitly mentioned in the provided text. Advising and grants details are not available here. He is affiliated with the School of Computing Science, which hosts labs like the Tangent Lab, though direct lab affiliations for Wu are not specified.

• Process Modelling
• Business Process Management
• Computer Science
• +۳ مورد دیگر

Toomas Saarsen is a Lecturer (0.90 FTE) at the University of Tartu's Faculty of Mathematics and Computer Science since 2017. He holds a Doctor's Degree (2017) from the same institution under supervisor Marlon Dumas, focusing on process model structures and their interplay. His research interests include process modeling, business process management, and systems theory. Education: PhD in Computer Science (2011–2017), MSc in Computer Science (1991–1992), and Applied Mathematics (1986–1991), all from the University of Tartu. Notable projects include leading the 'Data-Driven Management of Software and Business Processes' (2014–2019), funded by the Estonian Research Council (€1,499,565). Research focuses on process documentation assessment, enterprise modeling, and strategic risk analysis using FEM models. His work bridges theoretical models with practical implementation challenges in business process management.

Tracy Senecaمشاهده پروفایل

استاد بالینی

• Digital Preservation
• Library Science
• Web Archiving
• +۳ مورد دیگر

Tracy Seneca is a Clinical Professor and Head of Digital Programs and Services at the University of Illinois at Chicago (UIC) Library. She holds a Master of Arts in Applied Technology from DePaul University and a Master of Library and Information Studies from the University of California, Berkeley, alongside a B.A. in Humanities from UC Berkeley. Her work focuses on digital preservation, web archiving, and metadata standards, with significant contributions to collaborative digital initiatives like the Chicago Collections Consortium and the End of Term Web Archive. She has led projects such as the Chicago Building Permit Collection digitization and the implementation of the International Image Interoperability Framework (IIIF) in academic settings. Her professional service includes roles in the iPRES steering committee, the Chicago Collections Consortium, and the UIC Faculty Senate. Awards include the Center for Research Libraries Primary Source Award and the Larry L. Sautter Golden Award for Innovation. Teaching activities include workshops on web archiving and library instruction courses. Her publications span topics from digital humanities tools to consortial repository development, emphasizing interoperability and accessibility in cultural heritage preservation.

Francesco Lelliمشاهده پروفایل

استادیار

• Artificial Intelligence
• Data Science
• Digitalization
• +۷ مورد دیگر

Francesco Lelli is an Assistant Professor at Tilburg School of Economics and Management (TiSEM), Tilburg University, where he holds a position in the Department of Information Systems and Operations Management. His academic work bridges theoretical research with practical applications in digitalization, smart technologies, and industry transformation. He actively contributes to the Master in Information Management program, teaching Business Process Integration and Service-Oriented Architecture courses. His research focuses on human-device interaction, artificial intelligence ethics, Industry 4.0 applications, and data-driven decision-making. He has published extensively on topics like smart device agency, cybersecurity in financial systems, and interoperability frameworks. Notable datasets include studies on S&P500 security breaches and human-smart device relationships. Recent publications highlight trends in AI ethics, Industry 4.0 digital twins, and sociotechnical system analysis. His work emphasizes societal relevance, with projects addressing technology adoption challenges and ethical dimensions of emerging technologies. Francesco maintains an open-door policy for collaboration and mentorship, offering thesis guidance in information systems, cloud computing, and AI applications. He actively engages with industry partners to ensure research translates into real-world impact.

Frank van Harmelenمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Representation
• Semantic Web
• +۳ مورد دیگر

Frank van Harmelen is a full professor at the Vrije Universiteit Amsterdam and scientific director of The Network Institute. He specializes in Artificial Intelligence, Knowledge Representation, and the Semantic Web. His research includes foundational contributions to OWL, Sesame, and large-scale reasoning engines. He holds a PhD from the University of Edinburgh (1989) and has been recognized with awards like the 10-Year Impact Award (2012). Research interests span symbolic knowledge representation, large knowledge bases, and medical guideline formalization. Notable projects include the EU-funded Large Knowledge Collider and the formalization of Dutch breast-cancer guidelines using dynamic temporal logic. Awards: Distinguished Lecturer (2003), Keur der Wetenschap (2005), European AI Society Fellow (2007), and Most Cited Article Award (2011). Advising includes student Jacopo Urbani, co-author of prize-winning work. His work integrates theorem-proving with medical applications and semantic web infrastructure.

Ben Mitchellمشاهده پروفایل

استادیار مهمان

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۲ مورد دیگر

Dr. Ben Mitchell is a Visiting Assistant Professor in the Department of Computer Science at Swarthmore College. He teaches courses in Artificial Intelligence, Machine Learning, and Computer Science fundamentals. His research focuses on AI, machine learning, and deep learning, with recent work emphasizing medical imaging applications and ethical implications of AI. He has been recognized with a Best Paper Award at FLAIRS 2019. Mitchell's teaching spans introductory programming to advanced topics like neural networks and computer ethics. His work also extends to robotics and medical engineering, as seen in collaborations on surgical manipulators and diagnostic models. Education: Not explicitly stated in provided texts. Key Roles: Course instructor for CS63/CS66, advisor on AI projects. Grants/Awards: Best Paper Award (2019). Research interests include the intersection of AI/ML with real-world applications like healthcare, while addressing ethical challenges in data usage. His labs focus on practical implementations of search algorithms, neural networks, and reinforcement learning.