جست‌وجوی استاد و پژوهشگر

• Data Curation
• Open Science
• Qualitative Research
• +۳ مورد دیگر

Sebastian Karcher is a Research Associate Professor in the Political Science Department at Syracuse University, where he serves as Director of both the Center for Qualitative and Multi-Method Inquiry and the Qualitative Data Repository . He holds additional affiliation as a Senior Research Associate at the Campbell Public Affairs Institute. Karcher earned his Ph.D. from Northwestern University in 2014 and maintains an active research profile focused on advancing qualitative research methodologies. His research bridges data curation , open science infrastructure , and qualitative methodology , with specific interests in: Ethical frameworks for sensitive data sharing Repository development for qualitative research Transparency-enhancing tools and practices Interdisciplinary data synthesis approaches Indigenous data sovereignty initiatives Karcher has secured substantial research funding including grants from the National Science Foundation and Mellon Foundation. Key projects include: Data Services for Indigenous Scholarship and Sovereignty Support for Institutes on Qualitative Research (2021-2026) Privacy Interoperability frameworks Open Science through Journal Editors' Discussion Interface His scholarly contributions include the 2024 ASIS&T Best Short Paper Award. He teaches qualitative methodology courses and develops pedagogical resources for data management. As an open-source contributor, he maintains tools for Zotero and Citation Style Language. Through the Qualitative Data Repository, Karcher leads initiatives to develop curation standards and infrastructure supporting ethical reuse of qualitative research data across disciplines including health sciences, sustainability research, and social sciences.

Maria Halkidiمشاهده پروفایل

دانشیار

• Data Mining
• Machine Learning
• Recommender Systems
• +۶ مورد دیگر

Maria Halkidi is an Associate Professor in the Department of Digital Systems at the University of Piraeus, Greece, where she conducts cutting-edge research in data mining and machine learning with over two decades of academic experience. Her educational background includes: Bachelor's degree in Informatics from the University of Piraeus (1997) Master's degree from Athens University of Economics and Business (1999) Ph.D. from Athens University of Economics and Business (2003) Dr. Halkidi's research focuses on fundamental and applied aspects of data mining, particularly recommender systems, graph data mining, cluster validity assessment, and distributed data mining. Her work bridges theoretical frameworks with practical implementations in sensor networks, social media, and real-time analytics, contributing significantly to algorithmic development in these domains. Analysis of her recent publications reveals a strong trajectory toward fairness and diversity optimization in recommender systems, alongside innovative approaches to graph clustering quality assessment and scalable sentiment analysis. Her research consistently addresses real-world challenges in dynamic data environments, with increasing emphasis on multi-stakeholder optimization and privacy-aware recommendation frameworks. Scientific awards: No specific awards or honors were documented in the provided materials. Dr. Halkidi has participated extensively in National and European-funded research projects, including a prestigious Marie-Curie fellowship at the University of California, Riverside. She serves on program committees for major international conferences in data mining and machine learning, demonstrating active community engagement. While specific graduate students aren't listed in the source materials, her professorial role indicates ongoing mentorship of Master's and Ph.D. candidates. She maintains active research affiliations with the Network oriented systems & services lab and the DataStories research group at the University of Piraeus, where she collaborates on interdisciplinary projects involving big data analytics, social network analysis, and distributed systems.

Tobias Gebelمشاهده پروفایل

پژوهشگر

• Research data management
• Qualitative secondary analysis
• Labor market research
• +۲ مورد دیگر

Tobias Gebel serves as Deputy Head of the IT and Research Infrastructure Department at the German Institute for Economic Research (DIW Berlin), where he leads initiatives in research data systems and infrastructure. His role centers on advancing data management practices for economic and social research. His educational background includes: Doctorate in Sociology from Bielefeld University Studies in Sociology at Chemnitz University of Technology Gebel's research integrates technical and social science methodologies, with primary expertise in research data management, qualitative secondary analysis, and labor market dynamics. He pioneers frameworks for anonymizing survey data, developing digital repositories for historical economic archives, and enabling sustainable reuse of qualitative organizational data. His work bridges data science with labor economics, emphasizing ethical data sharing and infrastructure innovation to address challenges in employment research and organizational studies. Recent publications reveal a cohesive trajectory: advancing data anonymization protocols for large-scale surveys (e.g., LINOS and SOEP projects), establishing digital archives for historical economic documents (WBdigital), and applying qualitative secondary analysis to labor market phenomena like job recalls. These efforts demonstrate an interdisciplinary fusion of data engineering, labor economics, and organizational theory, with consistent focus on methodological rigor and practical applicability in real-world policy contexts. No scientific awards are documented in the provided information. Gebel actively leads grant-funded projects including the current QualiDataNet initiative—a federated infrastructure for archiving qualitative research data—and previously contributed to CoyPu (resilience platforms for economic ecosystems), eLabour II (IT-based labor sociology research), and WBdigital (digitization of DIW's historical publications). These projects underscore his strategic role in securing and executing research funding to build national data ecosystems. He co-develops critical research infrastructures including the Research Data Center for Business and Organizational Data (FDZ-BO) and QualiDataNet, which standardize data curation, anonymization, and access protocols for qualitative datasets. These teams collaborate with federal agencies and academic networks to promote FAIR data principles across German social science research.

Zhou Yangمشاهده پروفایل

استادیار

• Software Engineering
• Artificial Intelligence
• AI for Software Engineering
• +۳ مورد دیگر

Zhou Yang is an Assistant Professor at the University of Alberta and Fellow at the Alberta Machine Intelligence Institute (Amii), with research focusing on the intersection of software engineering and artificial intelligence. His academic journey includes a Ph.D. from Singapore Management University, an M.Sc. in Software System Engineering from University College London, and undergraduate studies at Yangzhou University. His research interests span Software Engineering, Artificial Intelligence, AI for Software Engineering (AI4SE), Software Engineering for AI (SE4AI), Large Language Models, and Cybersecurity. Yang's work explores how human and AI collaboration can improve code writing, how AI impacts open-source communities, and how developers build software in emerging environments like VR/AR. His recent publications demonstrate strong trends in code language models, with significant contributions to ASE, ICSE, ISSTA, and top journals like TOSEM and TSE. His research addresses critical challenges including token efficiency in code generation, user perception of AI coding assistants, privacy preservation in code models, and fairness in AI systems. 2024 IEEE Computer Society Best Paper Award (1 out of 183 submissions) ACM Distinguished Paper Award from ISSTA 2024 Distinguished Reviewer Award from Internetware 2024 SMU Research Staff Excellence Award (1 of 4 university-wide) SMU Presidential Fellowship Award SMU Dean's List Award 1st Place in ACM Student Research Competition at ICSE 2024 Yang actively mentors graduate students with regular one-on-one meetings, constructive feedback, and support for top-venue publications. He provides full funding through teaching assistantships and research grants, including travel support for conferences. His lab focuses on responsible research conduct and societal implications of AI work. Though early-career, he actively builds professional networks for students through collaborations and supports diverse career paths in academia and industry. He leads research in the Alberta Machine Intelligence Institute, focusing on practical applications where software engineering principles enhance AI systems and where AI techniques solve real-world software engineering challenges.

Francisco José García Peñalvoمشاهده پروفایل

استاد

• Educational Technology
• eLearning
• Human-Computer Interaction
• +۵ مورد دیگر

Francisco José García-Peñalvo is a Full Professor in the Department of Computer Science and Automation at the University of Salamanca (USAL), where he has earned four six-year periods of recognized research, one six-year period of recognized transferring and innovation, and five five-year periods of recognized teaching. He serves as Deputy Director of the Research Institute for Educational Sciences (IUCE) and Coordinator of the Doctorate Programme in Education in the Knowledge Society at USAL. Additionally, he holds international positions as a Researcher of International Impact at the Universidad Nacional San Agustín in Peru and previously served as a Distinguished Professor at Tecnológico de Monterrey in Mexico (2016-2018). His research interests focus on educational technology, particularly eLearning, human-computer interaction, informal learning, mobile learning, computational thinking, and open innovation. He has pioneered work in challenge-based learning, learning analytics, and educational robotics, examining how technology can enhance teaching and learning processes across various educational contexts. His work often bridges theoretical frameworks with practical applications in both formal and informal educational settings. García-Peñalvo leads the GRIAL Research Group (research GRoup on InterAction and eLearning), a Consolidated Research Unit of the Junta de Castilla y León Government since 2006. His publication record includes over 100 papers in JCR SCIE/SSCI-indexed journals (63 Q1), with research trends showing increasing focus on learning analytics, educational robotics, and open innovation in educational contexts. His work demonstrates a consistent commitment to understanding how technology can transform educational practices and improve learning outcomes. Gloria Begué Award for teaching excellence (2019) Maria de Maeztu Award for research excellence (2023) Stanford's World's Top 2% Scientists list (2019-2023) With 30 Ph.D. theses supervised, García-Peñalvo has significantly contributed to developing the next generation of researchers in educational technology. He serves as Editor-in-Chief of Education in the Knowledge Society and Associate Editor for prestigious journals including IEEE Access, Computers in Human Behavior, and Computers in Human Behavior Reports. His research has been supported by numerous projects including the VALS European Project and the WYRED project, focusing on virtual placements, open innovation, and youth empowerment in digital society. The GRIAL research group he leads continues to explore innovative approaches to technology-enhanced learning, with current work focusing on learning analytics in challenge-based environments and the role of social robots in educational contexts.