جست‌وجوی استاد و پژوهشگر

• Data Science
• FAIR Data Management
• Knowledge Graphs
• +۵ مورد دیگر

Renat Shigapov is a Researcher at the University of Mannheim's Research Data Center within the Mannheim Center for Data Science. He also serves as a Data Scientist for BERD@NFDI and coordinates the NFDI working group "Knowledge Graphs". His expertise lies in data science applications, FAIR research data management, and automating scientific tasks across the research lifecycle. Shigapov received his doctorate from the Faculty of Physics at the Karlsruhe Institute of Technology. His physics background provides a strong analytical foundation for his current work in data representation and knowledge structuring. His research focuses on making business, economic and related data in Germany FAIR (findable, accessible, interoperable and reusable) through the BERD@NFDI project. Key research areas include: Structuring and semantically enriching unstructured data Releasing structured (meta)data as knowledge graphs Digitizing printed materials through OCR and data extraction Developing APIs and SPARQL endpoints for knowledge graph access At the University of Mannheim, Shigapov provides comprehensive data science support across all research phases: Data acquisition: API, SQL, SPARQL and web-scraping techniques Data processing: Cleaning, analyzing, structuring and linking datasets Data publication: Archiving and sharing as FAIR linked open data As coordinator of the NFDI working group "Knowledge Graphs", he leads national efforts to establish standards for knowledge graph implementation in research data infrastructure. His philosophy centers on "automating every task" to enhance research efficiency and data accessibility.

• Organizational Behavior
• Employee Well-being
• Sustainable Tourism
• +۴ مورد دیگر

Analia Lopez Carballeira is an Assistant Professor at the University of Santiago de Compostela (USC), affiliated with the Department of Business Organization and Marketing within the Faculty of Economic and Business Sciences. Her research focuses on organizational behavior, employee well-being, sustainable tourism, and public health management. She is a member of the CVSO research group (Creation of Sustainable Value in Organizations) and holds a Doctorate from the University of Vigo (2017), where her thesis explored burnout syndrome in Galician public healthcare. Her research interests include leadership styles, work-family balance, and innovative pedagogical methods like flipped classrooms and microlearning. She has also examined occupational stress in law enforcement and healthcare sectors, emphasizing resilience-building strategies and role conflict resolution. Analia's recent work spans sustainable tourism technology applications, public safety professional well-being, and experiential learning approaches to bridge academia and industry. Her contributions highlight interdisciplinary solutions for organizational sustainability and human resource management challenges.

Anisa Rulaمشاهده پروفایل

استادیار

• Data Management
• Knowledge Graphs
• Data Quality Assessment
• +۴ مورد دیگر

Anisa Rula is an Assistant Professor in Computer Science at the Department of Information Engineering, University of Brescia since 2021. Previously, she was a researcher at the University of Bonn's SDA group (2017–2019). She holds a PhD in Computer Science from the University of Milano-Bicocca (2014). Her research focuses on data management and exploration, particularly in data quality assessment for Information Systems and Knowledge Graphs. Key interests include semantic data enrichment, large datasets, and knowledge extraction. Education: PhD in Computer Science, University of Milano-Bicocca (2014) Prior academic and research roles at University of Bonn (2017–2019) Research Interests: Data Quality Assessment for Knowledge Graphs and Information Systems Large-Scale Dataset Management & Exploration Procedural Knowledge Extraction from Text Ontology-Driven Semantic Enrichment Human-in-the-Loop Data Annotation Systems Publications reflect her expertise in Knowledge Graph lifecycle management, quality assessment tools like KGHeartBeat, and LLM applications for schema mining and data discovery. Her work emphasizes practical implementations such as MantisTable for semantic table interpretation and K-hub ontology for industrial knowledge extraction. Awards: None explicitly mentioned in text. Advising & Grants: No student advisees listed. Active in developing open-source tools and collaborative frameworks for data quality and semantic web applications. Labs/Teams: Involved in Knowledge Graph validation and quality initiatives, including contributions to the EU Business Graph platform and cross-institutional workshops on Linked Data Quality.

• Reverse Engineering
• Digital Twin Technology
• Product Lifecycle Management
• +۶ مورد دیگر

Sebastien REMY serves as a faculty member at Troyes University of Technology within the Laboratory of Mechanical & Material Engineering (LASMIS). His academic role combines teaching in mechanical design and computational engineering with research focused on industrial digital transformation. Research interests span Reverse Engineering methodologies applied to legacy systems, Digital Twin development for infrastructure and heritage preservation, and integration of Product Lifecycle Management (PLM) systems within Industry 4.0 frameworks. His work bridges geometric modeling with knowledge management in mechanical engineering contexts, particularly addressing end-of-life product management and real-time data integration for physical systems. Supervision includes 12 doctoral candidates across diverse projects including aerospace reverse engineering (with SAFRAN), railway infrastructure digital twins (with SNCF), and environmental data integration in design processes. Current research emphasizes semantic enrichment of 3D models and modification propagation analysis in complex mechanical assemblies. Teaching activities cover Computer-Aided Design (CAD), PLM systems, and digital transformation concepts within mechanical engineering curricula, contextualized within Industry 4.0 and future factory paradigms.

Marian de van der Schuerenمشاهده پروفایل

مدرس

• Malnutrition
• Gerontology
• Personalized Nutrition
• +۴ مورد دیگر

Marian de van der Schueren is a Lecturer leading the Nutrition, Dietetics and Lifestyle Lectorate at HAN University of Applied Sciences. Her work focuses on demonstrating the cost-effectiveness of dietary support, particularly for elderly populations and chronic disease management. She emphasizes client-centered care and data-driven approaches to elevate dietetics as a profession. Expertise areas include malnutrition assessment via GLIM criteria, personalized nutrition strategies, and lifestyle interventions. She holds a secondary academic role as Special Professor of Dietetics at Wageningen University and serves on multiple national advisory boards including the Malnutrition Knowledge Center and Dutch Journal of Lifestyle Medicine. Current Projects: ProBUS (protein-enriched diets for hip fracture recovery), SCOOP (malnutrition screening in obese patients), and MOCIA (cognitive function through lifestyle) Key Focus: Nutrition-exercise synergy for elderly health maintenance Her research spans 20+ projects aiming to integrate dietetic practices with modern healthcare systems through innovation and evidence-based practices.

Lisa Ehrlingerمشاهده پروفایل

پژوهشگر

• Data quality
• Knowledge graphs
• Ontologies
• +۵ مورد دیگر

Lisa Ehrlinger is a Senior Researcher at the Information Systems Research Group within the Digital Engineering Faculty of the University of Potsdam. She holds a PhD in Engineering Sciences ("passed with distinction") and an MSc in Computer Science from Johannes Kepler University Linz (JKU), both with distinction. Her work bridges academic research and industrial application. Her research focuses on Data Quality , Knowledge Graphs , Ontologies , Semantic Technology , Data Catalogs , and Data Integration , particularly with NoSQL databases. She has over 7 years of applied research experience at the Software Competence Center Hagenberg GmbH (SCCH), including project management and team leadership. Her recent publications emphasize SHACL validation , Data Stream Pollution , Dashboard Design , and Ontology-Driven Analysis , reflecting trends in data quality automation , semantic modeling , and industrial data governance . She co-chaired the Quality of Databases (QDB) workshop (2023, 2024) and serves on the MIT CDOIQ Symposium review board (since 2023). Her outreach includes lecturing at JKU and reviewing for journals like ACM Journal of Data and Information Quality (JDIQ) and Elsevier Journal of Information Fusion .

Arash Termehchyمشاهده پروفایل

دانشیار

• Machine Learning
• Data Systems
• Human-Data Interaction
• +۶ مورد دیگر

Arash Termehchy is an Associate Professor in the Department of Electrical Engineering and Computer Science at Oregon State University's College of Engineering. His research focuses on data-centric systems, including machine learning on structured/heterogeneous data, human-data interaction, and scalable/robust reasoning systems. He leads the IDEA Lab and teaches courses such as CS 549 (Scalable Reasoning & ML), CS 540 (Database Management Systems), and CS 440 (Database Management Systems). His work has been recognized with awards like the 2019 ACM SIGMOD Research Highlight Award and multiple Best Paper selections. Termehchy holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. His research spans data cleaning methods for ML, scalable relational learning, and systems for translational biomedicine (e.g., RTX-KG2). He explores how users' data focus evolves during visual analysis and develops adaptive visualization techniques like ShiftScope. His work emphasizes practical applications of AI in data systems, including entity augmentation, query generation, and model consistency through declarative constraints. Key contributions include Schema-independent relational learning (Castor), variational databases, and the Data Exploration Game framework. His research bridges theoretical foundations (e.g., logical scalability of learning algorithms) with real-world systems (e.g., Universal-DB for graph analytics). Current projects address challenges in handling incomplete data, scalable schema mappings, and human-in-the-loop data exploration. Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign Labs/Teams: IDEA Lab (Investigating Data-centric AI & Exploratory Analytics) Grants: NSF III Collaborative Research on Similarity Metrics (2014), Yahoo! Key Scientific Challenges (2011)

Tomas Saorin Perezمشاهده پروفایل

استاد

• Metadata and Resource Description
• Knowledge Organization Systems
• Semantic Web
• +۷ مورد دیگر

Tomas Saorin Perez is a Professor at the Department of Information and Documentation within the Faculty of Communication and Documentation at the University of Murcia. His research focuses on metadata, semantic web, knowledge graphs, and collaborative platforms like Wikipedia and Wikidata. He holds a Doctorate (2006) from the University of Murcia with a thesis on library automation in the digital context. His expertise spans knowledge organization systems, information architecture, content management systems (CMS), SEO strategies, and digital publishing frameworks. He actively contributes to GLAM-Wiki initiatives, promoting cultural heritage digitization through Wikimedia projects. Recent research emphasizes quantitative analysis of encyclopedic data to measure cultural relevance (Wiki3DRank model), multilingual literary canon analysis, and pandemic-related structured data generation. His work bridges library science with computational methods, addressing challenges in digital content management and open knowledge ecosystems. Key projects include the ODiSEA International Research Data Registry and Wiki Loves Monuments, showcasing his commitment to institutional collaboration and open data innovation.

• Companion Animal Epidemiology
• Breed-Related Health Disorders
• Animal Welfare Science
• +۲ مورد دیگر

Dan O'Neill is an Associate Professor in Companion Animal Epidemiology at the Royal Veterinary College (RVC), specializing in veterinary epidemiology and animal welfare. He leads the VetCompass Programme, a pioneering initiative collecting primary-care veterinary data for research. With a DVM from Dublin Vet School (1987) and an MSc/PhD from RVC, his career spans clinical practice, academia, and research leadership. He has expanded VetCompass globally and collaborates extensively with students and international researchers. His research centers on breed-related disorders, epidemiological methods, and welfare across companion animals, particularly dogs, cats, and exotic species. Key interests include conformation health, data-driven clinical decision-making, and One Health translational studies. His work often addresses brachycephalic welfare challenges and pandemic-related behavioral impacts. O'Neill's publications emphasize large-scale epidemiological trends, such as disorder predispositions in specific breeds, climate-related health risks, and ethical breeding frameworks. His recent articles frequently explore the intersection of genetics, conformation, and welfare in companion animals. Honors & Leadership Chairs the UK Brachycephalic Working Group and co-founds international committees (ICECDogs, LAGECDogs) Recipient of the RCVS Fellowship (2018), Blaine Award (2019, 2023), and International Canine Health Award (2021) Member of RCVS Knowledge Quality Improvement Board and RVC Clinical Research Ethical Review Board Teaching & Advising Teaches epidemiology across undergraduate and postgraduate programs, supervises student projects, and integrates VetCompass data into curricula. Actively mentors early-career researchers and advises on veterinary policy reforms.

Sally Koernerمشاهده پروفایل

دانشیار

• Community Ecology
• Disturbance Ecology
• Biodiversity
• +۲ مورد دیگر

Sally Koerner is Associate Professor and Director of Undergraduate Studies in Biology at the University of North Carolina Greensboro. She leads the Koerner Biodiversity Lab, investigating grassland plant communities and factors influencing biodiversity under global change. Her research examines mechanisms of biodiversity maintenance, impacts of global change drivers, and biodiversity-ecosystem function relationships. Major publications demonstrate reintroduced bison significantly increase grassland diversity, reveal independent (non-interactive) effects of multiple global change drivers, and show water availability gradients drive species richness patterns across five continents. Research employs experimental manipulations of rainfall, nutrient addition, and grazing across global grassland ecosystems to understand community responses.

Nick Turnbullمشاهده پروفایل

مدرس ارشد

• Governance and public policy
• Political rhetoric and communication
• Interpretive philosophy of social science
• +۳ مورد دیگر

Nick Turnbull is a Senior Lecturer in Politics at the University of Manchester, affiliated with the School of Social Sciences. He holds a PhD in Social Science and Policy from the University of New South Wales (2005) and a Bachelor of Social Science from the same institution (1997). His research focuses on governance, political rhetoric, and interpretive philosophy of social science, with particular emphasis on modern slavery policy and problematology. He has practical policy experience in Australia’s public service and non-government sectors. Teaching: He instructs undergraduate courses like Public Policy Problems and Politics Undergraduate Dissertation, and postgraduate modules such as Understanding Governance. His teaching philosophy centers on problem-based learning, emphasizing group work and contemporary political debates. Research: His work integrates rhetoric and governance theory, exploring how political actors use persuasive language in policymaking. Key areas include trafficking policy discourse, the Eurozone crisis, and UK higher education governance. He is a leading expert in Michel Meyer’s problematology, applying questioning theory to social science. Editorial Roles: Associate Editor of the International Review of Public Policy, Deputy Editor-in-Chief of Revue Internationale de Philosophie (2006–2021). Awards: 1997 University Medal for academic excellence. Projects: Co-researcher on the ESSTED project enriching social science teaching with empirical data. Key contributions include analyzing populism’s relational frameworks and critiquing modern slavery policy framing. He actively participates in organizations like the International Public Policy Association and contributes to policy debates on global inequalities and digital futures.

K. Selçuk Candanمشاهده پروفایل

استاد

• Data Science
• Database Systems
• Machine Learning
• +۵ مورد دیگر

K. Selçuk Candan is a Professor of Computer Science and Engineering at Arizona State University (ASU) and the Director of the Center for Assured and Scalable Data Engineering (CASCADE). He holds affiliations with the Global Institute of Sustainability and the Center for Cybersecurity and Digital Forensics. His academic roles include interim co-director of the School of Computing and Augmented Intelligence (2022) and coordinator of the Big Data Systems concentration. He earned his Ph.D. from the University of Maryland and his B.S. from Bilkent University. Education: Ph.D. Computer Science (University of Maryland, 1997), B.S. Computer Engineering (Bilkent University, 1993) Affiliations: CASCADE Director, Global Futures Scientist, NSF APPEX Center His research focuses on data management, analysis of heterogeneous data, and applications in healthcare, energy, and cybersecurity. He has authored over 250 peer-reviewed publications and secured $34M in grants. Key projects include pandemic modeling, building energy optimization, and cybersecurity for smart infrastructure. Recipient of the 2023 Daniel Jankowski Legacy Award and ACM SIGMOD Contributions Award, he emphasizes interdisciplinary collaboration and mentorship. He has advised 16 doctoral students and 35+ graduate students, contributing to teaching excellence awards. His work bridges academia and industry, with grants from NSF, DOE, and DoD. Current efforts include causal learning frameworks, spatio-temporal modeling, and cyber-infrastructure for pandemic response.

K. Selcuk Candanمشاهده پروفایل

استاد

• Data Management
• Multimedia Databases
• Distributed Systems
• +۵ مورد دیگر

K. Selcuk Candan is a Professor of Computer Science and Engineering at Arizona State University (ASU) and Director of the Center for Assured and Scalable Data Engineering (CASCADE). He holds affiliations with multiple institutes, including the Global Futures Scientists and Scholars and the Center for Cybersecurity and Trusted Foundations. Candan has been at ASU since 1997, following his PhD from the University of Maryland. His research focuses on managing and analyzing non-traditional data types like multimedia, web, and scientific data. Key interests include scalable data processing, sensor data integration, and accessibility technologies for visually impaired individuals. He has led numerous grants from NSF, DoD, and others, resulting in over 250 peer-reviewed publications and 9 patents. Notable contributions include the DataStorm framework for coupled simulations and the OASIS system for accessible digital content. Candan has served as program chair for top conferences like SIGMOD and MM, and is an ACM Distinguished Scientist. His awards include the SIGMOD Contributions Award and Dan Jankowski Legacy Award. He has advised numerous students and led interdisciplinary projects in areas like pandemic modeling (APPEX Center) and building automation security. His work bridges theory and application, emphasizing real-world impact in healthcare, urban systems, and educational accessibility.

• Genomics
• Autism Spectrum Disorder
• Clinical Genetics
• +۳ مورد دیگر

Dr. Bridget Fernandez is a Clinical Professor of Pediatrics at the Keck School of Medicine, University of Southern California (USC), and Associate Director of Clinical Research at The Saban Research Institute, Children’s Hospital Los Angeles. She holds an MD from Memorial University of Newfoundland and an MS in Clinical Epidemiology. Her career includes leadership roles such as Medical Director of Newfoundland’s Provincial Medical Genetic Program (over 20 years) and Chair of Memorial University’s Department of Human Genetics (2012–2020). She has also chaired Canada’s national Medical Genetics Examination Board and led the Canadian College of Medical Geneticists as its President. Her research focuses on genomic studies in autism spectrum disorder (ASD), particularly in Hispanic populations, aiming to close knowledge gaps in genetic variation and clinical outcomes. She leads projects correlating genomic variants with ASD phenotypes and improving diagnostic methodologies through optical genome mapping and long-read sequencing. Dr. Fernandez has worked extensively with Canadian families and now focuses on Hispanic/Latinx cohorts in Los Angeles. In grants and advising, she has managed large-scale genomic studies and collaborative projects like FORGE Canada Consortium. Her work bridges clinical practice and research, emphasizing ethical genomic testing and precision medicine. She contributes to initiatives like the Canadian Open Genetics Repository for variant interpretation. Key professional roles include leadership in medical genetics education, policy development for genomic sequencing in Canada, and clinical program development. Her research integrates molecular genetics, epidemiology, and clinical outcomes to advance ASD understanding and care.

Ihab F. Ilyasمشاهده پروفایل

استاد

• Data Quality
• Machine Learning
• Database Systems
• +۴ مورد دیگر

Ihab F. Ilyas is a Professor and holds the Thomson Reuters–NSERC Industrial Research Chair in Data Quality at the University of Waterloo's Department of Computer Science. His research focuses on data quality, machine learning for data enrichment, probabilistic data management, and knowledge graph systems. He leads projects like Holoclean (a probabilistic data repair system) and Data Civilizer (a data unification platform). His work bridges database systems and machine learning to address challenges in data integration, error detection, and large-scale knowledge representation. Education: PhD in Computer Science from Purdue University (2004), MSc and BSc from Alexandria University, Egypt (1999 and 1995). His publications span vector search, knowledge graph construction, and data curation techniques, with recent emphasis on adaptive indexing and scalable systems. He has contributed to open-source tools and frameworks for data cleaning and machine learning integration. Research interests include probabilistic data management, machine learning applications for data quality, and scalable systems for big data. His work often addresses real-world challenges in data integration and semantic representation, with a focus on practical, deployable solutions.