جست‌وجوی استاد و پژوهشگر

• Digital Preservation
• Information Science
• Records Management
• +۴ مورد دیگر

Dr James Currall is an Honorary Senior Research Fellow at the School of Humanities, University of Glasgow. His research spans digital preservation, records management, and information science, with notable contributions to statistical methodologies in veterinary medicine and the theoretical underpinnings of archival authenticity. He has collaborated extensively on projects addressing digital curation challenges, including the Effective Records Management Project (2002). His work explores intersections between technology and institutional practices, such as the sustainability of digital assets and metadata standards. Key contributions include critiques of digital preservation funding models and analyses of authenticity in digital archives. Currall has published widely in journals like Journal of Small Animal Practice , Archives and Manuscripts , and D-Lib Magazine , reflecting his interdisciplinary approach. Notable projects include the espida Process framework for digital curation cost modeling and collaborative efforts on metadata governance. His research often emphasizes practical applications, such as improving statistical literacy among veterinary clinicians and advancing strategies for long-term digital asset management.

Semih Yumusakمشاهده پروفایل

پژوهشگر ارشد

• Data Science
• Machine Learning
• Cybersecurity
• +۵ مورد دیگر

Dr. Semih Yumusak is a Research Fellow at the University of Southampton, focusing on interdisciplinary research at the intersection of data science, cybersecurity, and network systems. His current work emphasizes data marketplace architecture, privacy-preserving techniques, and applications of machine learning in finance and social analysis. He contributes to projects like the Universal Platform Components for Safe Data Exchange (UPCAST), aiming to enhance interoperability and security in data monetization. His research interests include modular data systems, maritime migration pathways analysis through cellular data, and academic collaboration networks. Recent publications highlight innovations in privacy negotiation frameworks, financial text mining, and network topology optimization. Dr. Yumusak collaborates with international teams on topics ranging from knowledge graph construction to sentiment analysis in product reviews. While no formal awards are listed, his active involvement in funded research projects underscores his academic impact. His work bridges technical challenges in data governance with societal applications, such as leveraging big data for refugee migration safety and improving stock market speculation analysis through social media insights.

Rohit Nishantمشاهده پروفایل

دانشیار

• AI for Sustainability
• Digital Sustainability
• Green Information Systems
• +۴ مورد دیگر

Rohit Nishant is an Associate Professor at Laval University's Department of Organizational Information Systems within the Faculty of Social Sciences (FSA). He leads the Emerging Information Technologies for Business axis at the Centre for Research in Information Technologies and Business (CeRTIA). His research focuses on AI sustainability, digital transformation, cybersecurity, and societal impact of technology. He holds a Doctor of Administration and Ph.D. in Organizational Information Systems from the National University of Singapore, an MBA from TAPAI Management Institute, and a B.Sc. in Manufacturing Engineering from the National Institute of Foundry and Forging Technology. Teaching areas include data mining, business intelligence, AI for managers, and sustainability-focused information systems. His work explores AI ethics, green IS, and blockchain applications in supply chains. Recent studies address quantum computing's societal implications, metaverse ecosystems, and fake news propagation mechanisms. He contributes to policy frameworks for AI safety and cybersecurity in digital transformation contexts. Rohit's research has been published in top journals like Journal of Strategic Information Systems , Decision Support Systems , and Journal of Industrial Ecology . He actively participates in conferences such as AMCIS and EGOS, and collaborates internationally on projects involving climate change mitigation through data management and AI.

Kevin Lybargerمشاهده پروفایل

استادیار

• Artificial Intelligence
• Natural Language Processing (NLP)
• Health Informatics
• +۶ مورد دیگر

Dr. Kevin Lybarger is an Assistant Professor in the Department of Information Sciences and Technology at George Mason University’s College of Engineering & Computing. He also holds an Affiliate Assistant Professor role at the University of Washington School of Medicine to facilitate collaborative research. His research focuses on artificial intelligence (AI), natural language processing (NLP), and their applications in healthcare, including clinical informatics, health-focused conversational agents, public health, information integrity, and correctional system informatics. Lybarger’s work emphasizes optimizing textual information use for decision-making and driving societal impact through technology. Lybarger earned his PhD and MS in Electrical and Computer Engineering from the University of Washington and a BS in Electrical Engineering from Seattle University. He collaborates with groups like the University of Washington Biomedical Language Processing (UW BioNLP) and the Transformation, Interpretation and Analysis of Language (TIAL) Group. His research spans health informatics (e.g., extracting social determinants of health from clinical notes), NLP advancements (e.g., text simplification for medical education), and interdisciplinary challenges like AI-driven cybersecurity and ethical AI applications in probation/parole records analysis. Recent work includes developing machine learning models for surgical site infection identification and improving clinical documentation through voice technologies. Notable collaborations include projects with the UW BioNLP group on biomedical text processing and participation in the 2022 n2c2 shared task on social determinants of health extraction. His research addresses both technical and ethical dimensions of healthcare NLP, aiming to bridge gaps between computational methods and real-world clinical needs.

Cecile Parisمشاهده پروفایل

استاد مدعو

• Natural Language Processing
• Social Media Analytics
• Computer-Human Interaction
• +۴ مورد دیگر

Cecile Paris is a Chief Research Scientist at CSIRO's Data61 and Director of the Collaborative Intelligence (CINTEL) FSP. She holds adjunct professorships at RMIT University, University of Wollongong, and others. Her research focuses on Natural Language Processing (NLP), Social Media Analytics, and Human-AI Collaboration. Paris earned a PhD in Artificial Intelligence from Columbia University (1987) and has held senior roles internationally, including at USC's Information Sciences Institute and the University of Brighton. Education: PhD in AI (Columbia University, 1987), MSc (Columbia, 1982), BA (UC Berkeley, 1980). Research Interests: NLP, Social Computing, User Modelling, and AI ethics. Her work emphasizes practical applications in health, emergency management, and digital services. Notable projects include We Feel (social media emotion mapping) and Accurait (AI-driven lease management). Paris has led teams that won awards for innovations like the ESA ASPIRE system and social media mental health monitoring tools. Awards: Fellow of ATSE (2016), Fellow of Royal Society NSW (2019), ACS Disruptor Award (2015), and multiple CSIRO Excellence Awards. She has supervised over 20 students, many of whom received distinguished awards for their theses. Grants: Includes CSIRO-funded projects on social licence to operate, mental health analytics, and collaborations with institutions like the Black Dog Institute. Labs/Teams: Leads the Language and Social Computing team at Data61, fostering interdisciplinary research in AI and human collaboration.

Anca VASILESCUمشاهده پروفایل

مدرس

• IoT (Internet of Things)
• E-Learning and Distance Education
• Formal Modelling of Processes
• +۷ مورد دیگر

Anca VASILESCU is a Lecturer at the Department of Mathematics and Computer Science, part of the Faculty of Mathematics and Computer Science at Transilvania University of Brașov. Her research focuses on formal modeling of non-sequential processes, distributed systems, IoT applications in healthcare and smart living, e-learning methodologies, and cybersecurity. She has contributed to projects such as the FitPi wearable IoT solution and e-UPU emergency room triage system. Her academic work spans interdisciplinary areas including smart education technologies (Long Life Learning, Distance Learning), digital literacy, and healthcare informatics. She also explores bio-inspired architectures for wireless sensor networks and cybersecurity in IoT ecosystems. Publications highlight her expertise in machine learning for medical data processing, formal methods in hardware design, and innovative air quality monitoring systems. Her work is featured in journals like Environmental Engineering and Management Journal and conferences such as the Balkan Conference on Informatics. While no scientific awards are explicitly listed, her contributions to IoT integration in emergency scenarios and educational technology reflect impactful applied research. Advising and grants details are not provided in available materials.

• Artificial Intelligence
• Virtual Reality
• Healthcare Technology
• +۷ مورد دیگر

Maria Dascalu is a Professor at the University of Thessaly, Greece, and a guest lecturer at the Faculty of Engineering in Foreign Languages (FILS) at the Polytechnic University of Bucharest (UPB). Her research focuses on integrating emerging technologies like Virtual Reality (VR), Artificial Intelligence (AI), and Machine Learning into education, healthcare, and career guidance. She leads projects such as CareProfSys, an AI-driven system combining VR and ontology-based recommendations to enhance employability and neurorehabilitation. Her work also explores gamification, chatbots for career counseling, and eHealth applications. Key areas: VR applications, ontology design, education technology, and healthcare innovation Contributions include developing immersive training platforms and assistive technologies for visually impaired individuals Research trends highlight interdisciplinary approaches combining engineering, computer science, and pedagogy. Her studies on power systems and nonlinear circuits demonstrate expertise in electrical engineering. Over 80 articles span topics from AI in workplace upskilling to hackathons in STEM education. No scientific awards explicitly listed, but her extensive publication record reflects impactful contributions. Active in academic outreach, she collaborates on initiatives like Google Summer Schools and virtual training platforms for neurorehabilitation. FilS UPB affiliation highlights involvement in multilingual engineering education.

Hanna Krasnovaمشاهده پروفایل

استاد

• Social Media
• Digital Integration
• Privacy
• +۴ مورد دیگر

Prof. Dr. Hanna Krasnova is a Professor of Information Systems at the University of Potsdam, specializing in Social Media and Data Science. She previously held an Assistant Professorship at the University of Bern. Her research focuses on the societal impact of social media, including phenomena like 'phubbing' (smartphone-induced snubbing), digital integration of refugees, privacy concerns, and the psychological effects of social media use. Her work has been widely recognized, including a Best Paper Award at ICIS 2013 and extensive media coverage (e.g., CNN, BBC). Her key research areas include digital well-being, privacy calculus, and the sharing economy. She leads projects at the German Internet-Institute on topics like 'Digital Technologies and Well-Being' and 'Digital Integration,' exploring how technology aids refugee integration. Krasnova advises numerous PhD and Master’s students, including Dr. Katharina Baum and Dr. Olga Abramova. Her contributions extend to academic leadership, serving as Doctoral Consortium Co-Chair at ECIS 2018 and Track Chair at multiple conferences. Over 3,000 citations on Google Scholar highlight her scholarly impact. She is also noted for accessible outreach, with her findings featured in global media.

• Bioinformatics
• Computational Biology
• Machine Learning
• +۳ مورد دیگر

Hong Qin is a Professor affiliated with the University of Tennessee at Chattanooga, USA, and previously with Tuskegee University's Department of Agricultural and Environmental Sciences. His research spans computational biology, machine learning, environmental informatics, and healthcare data science. He has co-authored over 20 papers since 2007, focusing on topics like viral fitness modeling, optimization algorithms, and AI applications in healthcare diagnostics. Research interests emphasize interdisciplinary approaches, including bioinformatics for viral mutation analysis, swarm intelligence for optimization problems, and explainable AI for medical imaging. Recent work includes federated learning for healthcare privacy, blockchain interoperability, and environmental monitoring via satellite imagery. His publications reflect a strong focus on AI-driven solutions for global health challenges, such as SARS-CoV-2 variant analysis and equitable AI frameworks for public health. He has contributed as an editor for journals like IEEE ACM Transactions on Computational Biology and Bioinformatics, highlighting his role in shaping bioinformatics research.

Timothy Tzen Vun Yapمشاهده پروفایل

استادیار

• System Identification
• Blockchain Technology
• Data Engineering
• +۳ مورد دیگر

Dr. Timothy Tzen Vun Yap is an Assistant Professor at the School of Mathematical & Computer Sciences, Heriot-Watt University Malaysia. Previously, he served as Senior Lecturer and Chair of the Center for Big Data and Blockchain Technologies at Multimedia University. He holds a PhD in Engineering from Multimedia University's System Identification and Control Group. His research focuses on blockchain technology, machine learning, data engineering, and system identification, with emphasis on consensus mechanisms, Sybil resistance in blockchain networks, and sentiment/aspect modeling. His research interests span technical domains including spyware detection, network security, educational data mining, and cryptocurrency efficiency. Notable contributions include advancements in Bitcoin block propagation, dataset curation for malware classification, and machine learning applications in intrusion detection systems. He has also explored the intersection of machine learning and healthcare, such as predictive modeling for breast cancer risk factors. His publications reflect a trend toward interdisciplinary solutions, blending cybersecurity with machine learning and applying data science to societal challenges like tourism and education. Collaborations often target practical implementations of theoretical models, such as optimizing blockchain protocols or improving real-time network traffic analysis. Though no formal awards are listed, his prolific output (59+ research outputs) and diverse collaborations underscore his active role in academic and applied research. His work contributes to UN Sustainable Development Goals through technological solutions addressing education equity, healthcare accessibility, and secure digital infrastructure.

Mark Hedgesمشاهده پروفایل

دانشیار

• Digital Humanities
• Digital Curation
• Digital Libraries
• +۴ مورد دیگر

Mark Hedges is a Reader in Cultural Informatics and Head of the Department of Digital Humanities at King's College London. He holds a PhD in Mathematics from University College London and an MA in Late Antique and Byzantine Studies. Before academia, he spent 17 years in software and systems consultancy. His research focuses on digital curation, crowdsourcing in humanities, and the social impact of digital technologies, particularly in post-genocide Rwanda. He leads interdisciplinary projects like CENDARI and FISHNet, and collaborates on EU initiatives such as PARTHENOS. Education: PhD in Mathematics, University College London (1986) MA in Late Antique and Byzantine Studies, King's College London (2004) BSc in Mathematics and Philosophy, Bedford College (1983) Research Interests: Digital humanities methodologies, participatory research, digital archives, computational methods for cultural heritage, and technology's societal impact. His work bridges technical innovation with ethical and practical challenges in democratizing access to cultural data. Grants & Projects: UKRI Horizon Europe funding (2025) for language evolution studies EU-funded PARTHENOS (2015–2019, €12M) for humanities research infrastructures CENDARI (2013) for historical research ecosystems Rwanda digital archives initiatives with Aegis Trust Labs & Affiliations: Director of King's Centre for e-Research Computational Humanities Research Group King's Cybersecurity Centre (EPSRC-NCSC ACE-CSR)

• Software Engineering
• Machine Learning
• Precision Agriculture
• +۷ مورد دیگر

Önder Babur is an Assistant Professor in the Department of Information Technology at Eindhoven University of Technology. His research focuses on software engineering, machine learning applications, precision agriculture, and digital twin technologies. He has contributed to projects involving business process modeling, drone analytics, and energy market methodologies. Babur collaborates with institutions like Wageningen University & Research and has supervised PhD candidates in generative AI approaches and digital twin systems. His research interests span model analytics, clone detection, API usage analysis, and low-code platforms. Notable projects include an empirical study of business process models on GitHub and foundational work in digital twins for energy markets. Babur has co-developed datasets for drone imagery analysis and systematic reviews of food recommender systems. His work bridges theoretical software engineering advancements with practical applications in agriculture and energy systems. Advising PhD candidates include Gürkan Soykan (digital twins in energy markets) and Jeroen Doornbos (generative AI in drone analytics). Projects emphasize collaborative frameworks like SAMOS for model management and Apache Spark-based distributed analytics. Babur’s contributions span 45+ peer-reviewed publications and two active PhD supervisions.

Jinyang Zhengمشاهده پروفایل

استادیار

• AI for Business
• Moderating Content Platforms
• Managing Two-sided Platforms
• +۵ مورد دیگر

Jinyang Zheng is an Assistant Professor of Information Systems at Simon Business School, specializing in AI-driven business transformation and digital platform moderation. His research focuses on leveraging causal inference, structural modeling, and unstructured data analysis to address challenges in two-sided platforms and digital resilience. Education: Ph.D. in Business Administration, University of Washington Foster School of Business B.S. in Statistics, Fudan University Research Interests: His work spans AI for business, moderating content platforms, managing two-sided markets, and digital resilience strategies. Recent studies explore AI's role in shelf monitoring, information sharing in ride-hailing, and the impact of editorial reviews on UGC platforms. Publications: Zheng’s work appears in top journals like Management Science , Information Systems Research , and MIS Quarterly . His recent research investigates live commerce sustainability, autonomous vehicle impacts, and privacy policies in misinformation monitoring. Awards: 2023 Gordon Davis Young Scholar Award (INFORMS) Jay Ross Young Faculty Award (Purdue University) Simon School Teaching Honor Roll Outstanding Teacher at Purdue University Teaching & Advising: Known for excellence in teaching courses like social media analytics and machine learning for business. No formal advisee list is publicly disclosed. Labs/Teams: Active in platform economics and AI governance research clusters at Simon Business School.

• Machine Learning
• Digital Preservation
• Privacy-Preserving Data Analysis
• +۶ مورد دیگر

Rudolf Mayer is an Lecturer at the School of Logic and Computation and School of Information Systems Engineering at Vienna University of Technology . He is affiliated with the university through his roles in teaching and research, focusing on Machine Learning , Digital Preservation , and Privacy-Preserving Data Analysis . His work spans both academic research and applied projects, with a strong emphasis on collaborative and secure data management . His research interests include Machine Learning , Privacy-Preserving Techniques , Digital Preservation , and Music Information Retrieval . Over his career, Mayer has contributed to Developing frameworks for digital preservation of scientific and business processes Advancing privacy-preserving data analysis through platforms like WellFort Exploring adversarial machine learning and model stealing attacks Integrating semantic web technologies into data management systems His publications highlight trends in collaborative cybersecurity , model robustness , and digital archiving with applications in federated learning, self-organizing maps, and music analysis. Mayer has supervised 15+ graduate students , covering topics such as adversarial attacks , model watermarking , and privacy-preserving anomaly detection . Notable projects he has been involved in include the NEWSROOM initiative for cybersecurity automation, the Research Studio Digital Memory Engineering , and contributions to the PLANETS project for long-term digital access.

• Artificial Intelligence
• Causal Inference
• Machine Learning
• +۴ مورد دیگر

Emre Kiciman is a leading researcher in artificial intelligence, causal inference, and social computing. His work spans machine learning, ethics in AI, and applications in healthcare and cybersecurity. He has authored over 135 publications in top venues such as ICWSM, KDD, and NeurIPS, focusing on causal discovery, LLM security, and human-AI collaboration. His research bridges theoretical advancements with real-world impacts, including improving mental health monitoring via social media and developing causal tools for robust decision-making. He collaborates widely with institutions and tech companies, contributing to open-source causal AI frameworks and ethical guidelines for AI systems.