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Doina CarageaView profile

Professor

• Machine Learning
• Deep Learning
• Data Science
• +7 more

Doina Caragea is a Professor in the Department of Computer Science at Kansas State University, affiliated with the Carl R. Ice College of Engineering. She holds the Don and Linda Glaser Keystone Research Scholar title and is actively engaged in research and teaching in machine learning, deep learning, and data science. Education: Ph.D. in Computer Science, Iowa State University, 2004 M.S. in Computer Science, University of Bucharest, 1997 B.S. in Computer Science, University of Bucharest, 1996 Her research focuses on machine learning and data mining with applications in text analytics, bioinformatics, digital agriculture, and security informatics. She has made significant contributions to semi-supervised learning and domain adaptation, especially in scenarios with limited labeled data. Her interdisciplinary work bridges computer science with life sciences and social sciences to solve real-world challenges. The recent publication trend highlights her focus on deep learning architectures, particularly transformer models and contrastive learning, applied to disaster image classification—indicating a growing interest in crisis informatics and multimodal AI for humanitarian applications. Scientific Awards: Iowa State University Research Excellence Award IBM Fellowship (2002, 2003) Don and Linda Glaser Keystone Research Scholar Doina Caragea has secured over $12 million in external funding as PI, co-PI, or senior personnel from NSF and industry sources. She has advised four doctoral students and more than 25 master’s students, demonstrating a strong commitment to graduate education and mentorship. She teaches graduate and undergraduate courses, including CIS831/CIS532: Deep Learning (offered Fall 2017, 2019–2023) and CIS761: Database Management Systems (designed in 2013, offered Spring 2016–2024). Her courses cover foundational and advanced topics in deep learning, neural networks, relational databases, SQL, and NoSQL systems.

Ching-yu HuangView profile

Associate Professor

• Bioinformatics
• Data Mining
• Image Processing
• +6 more

Ching-yu Huang is an Associate Professor in the Department of Computer Science and Technology at Kean University within the College of Science, Mathematics and Technology. With a Ph.D. in Computer and Information Sciences from NJIT, he bridges industry experience in Finance, Telecommunications, and Biotechnology with academic roles, focusing on data mining, image processing, and educational technology. Education : Ph.D. (NJIT, 1998), M.S. (NJIT, 1993), B.Eng. (Tamkang University, 1990) Research Interests span bioinformatics (SNP genotype calling), data mining, image processing, GIS, and cyber-learning. His work integrates machine learning with practical applications in medical imaging, social media analysis, and educational tools. Publication Trends show expertise in data analytics for public health, geospatial systems, and educational technologies, with recent studies on pandemic impacts, blockchain, and AI-driven visualization tools. Collaborations with students highlight real-world problem-solving. Scientific Awards : NSF Grant Co-PI (2025-2029) Kean Presidential Excellence in Teaching (2023) NSF DUE Grant Co-PI (2021-2026) Multiple SpF and STEMPact Awards (2017-2023) Teaching & Grants : Courses include Data Mining, Database Systems, and Unix Programming. He has secured significant NSF funding for cybersecurity and data science education, mentoring over 20 students in research initiatives. Labs & Teams : Faculty advisor for Code Samurai peer-tutoring Collaborator in NIH UMDNJ research Co-PI in NSF grants for educational innovation

• Embedded Systems
• Fault Tolerance
• Precision Agriculture
• +5 more

Maurizio Rebaudengo is a Full Professor at the Department of Control and Computer Science (DAUIN) of the Polytechnic University of Turin. He is a member of the PIC4SeR Interdepartmental Center for Service Robotics and holds expertise in embedded systems, fault tolerance, and sensor network applications. Research Interests: Embedded systems, fault tolerance, precision agriculture, RFID technology, wireless sensor networks, and system dependability Scientific Awards: Ramamoorthy Best Paper Award (1997) Leadership Roles: Program Chair for the 4th International EURASIP Workshop on RFID, Committee Member for Public Administration Agreements (2020-2024) Projects: Scientific Director for HONEY (Hybrid ONline tEchnologY for particle therapy), FDM (Food Digital Monitoring), IDEM (Internet of Data for Environmental Monitoring), and OPLON (Healthy Longevity Opportunities). Teaching: Course lecturer for Electronic Calculators, Computer Science, Systems Programming, and Cybersecurity at both undergraduate and postgraduate levels. His work spans IoT applications in agriculture and healthcare, focusing on low-cost sensor networks , RFID-based traceability , and cyber-physical system resilience . Recent publications emphasize particulate matter monitoring and secure communication protocols in wireless environments.

Florije IsmailiView profile

Professor

• Machine Learning
• Semantic Web
• Data Mining
• +6 more

Florije Ismaili is a Full Professor at the Faculty of Contemporary Sciences and Technologies at South East European University (SEEU) in Tetovo, Macedonia. With a PhD in Computer Science from Technical University of Sofia and a Master's in Informatics from New Bulgarian University, her research focuses on Machine Learning , Semantic Web , Internet of Things (IoT) , and Data Mining . She has led research initiatives and taught courses including Web Programming and Distributed Systems. Doctor of Computer Science (2011), Technical University of Sofia, Bulgaria Master of Science (2005), New Bulgarian University, Sofia Bachelor of Mathematics (2003), EGE University, Izmir, Turkey Her publications demonstrate expertise in applying Machine Learning to domains like education, healthcare, and smart farming. She specializes in Semantic Web techniques for IoT data integration and causal reasoning in complex datasets. Recent work includes predictive modeling of student success and ethical considerations in AI applications. Professor Ismaili's research spans IoT semantic annotation, Cloud Computing architectures for healthcare, and causal rule mining. She has contributed to journals such as IEEE Transactions and Springer publications, with a focus on contextual data integration and ethical data analysis. Her career at SEEU includes prior roles as Assistant Professor, Head of Research Office (CST Faculty), and Young Assistant. She has collaborated on projects addressing database migration, hate speech detection, and e-Government maturity assessment.

• Image processing
• 3D visualization
• Virtual Reality
• +7 more

Prof. PhD Miroslav Nikolov Galabov is a Professor at the Faculty of Mathematics and Informatics, St. Cyril and St. Methodius University of Veliko Turnovo in Bulgaria. His academic career spans several decades with significant contributions to computer science, particularly in the areas of 3D visualization, virtual and augmented reality, and image processing. He maintains active research collaborations and participates in multiple funded projects at the university. Professor Galabov's research interests focus on cutting-edge technologies including: Image processing and computer vision 3D visualization and modeling Virtual and Augmented Reality systems Microprocessor systems and embedded computing System programming and software architecture Multimedia systems and publishing technologies E-business applications and social network technologies His scholarly output demonstrates a clear evolution from foundational work in digital signal processing and image compression toward contemporary research in cloud infrastructure, semantic web technologies, and digital twin applications. Recent publications show a strong emphasis on practical implementations of AWS infrastructure, microservices architecture, and blockchain solutions for IoT systems. His work consistently bridges theoretical computer science with real-world applications across multiple domains including education, business, and cultural heritage preservation. Professor Galabov actively participates in significant research projects including: "Изследване и анализ на приложението на технологични инструменти и инфраструктура като креативна среда за трансфер на знания" (2025-2025) "Изследване, анализ и популяризиране на мобилни технологии и софтуерни приложения в полза на студенти със специални потребности" (2025-2025) "Изследване възможностите на технологиите за виртуална и добавена реалност за атрактивно представяне и популяризиране на българското фолклорно наследство" (2023-2023) Multiple projects related to 3D visualization, e-learning, and digital infrastructure development

Cedric du MouzaView profile

Professor

• Database Systems
• Data Mining
• Digital Humanities
• +6 more

Cédric du Mouza is a full Professor within the CEDRIC Laboratory at the Conservatoire National des Arts et Métiers (CNAM) in Paris, France. His research activities lie at the intersection of database systems, data mining, and digital humanities, with a strong emphasis on social network analysis, knowledge base population, and spatial/temporal data management. Education details are not explicitly provided in the source material. His research interests can be summarized as follows: Database Technologies: scalable indexing, distributed repositories, spatial and temporal data structures. Data Mining & Machine Learning: community detection, influence maximization, recommender systems. Digital Humanities: prosopographic databases, historical social networks, credibility assessment of historical sources. Social Media Analytics: Twitter user profiling, early detection of popular accounts, reducing filter bubbles. Across more than two decades, Prof. du Mouza has produced a rich scholarly record that blends theoretical advances with practical applications. Recent publications (2020-2024) highlight a methodological shift toward end-to-end evaluation frameworks for knowledge base population, uncertainty modeling in historical corpora, and real-time influence maximization in advertising ecosystems. These works are published in premier venues such as SIGIR , VLDB Journal , WISE , CIKM , and leading French conferences (EGC, BDA). No specific scientific awards, funded projects, or doctoral student names are mentioned in the supplied text. Prof. du Mouza collaborates extensively within interdisciplinary teams involving historians, computer scientists, and statisticians, reflecting CEDRIC’s integrative research culture. While no dedicated laboratory or team name is provided, his continuous affiliation with CEDRIC/CNAM confirms an active and ongoing role in both research and graduate-level education.

Samira Si-Said CherfiView profile

Professor

• Data Quality
• Conceptual Modeling
• Ontology Engineering
• +5 more

Samira Si-Said Cherfi is a Professor at the Centre d'études et de recherche en informatique et communications (CEDRIC) within the Conservatoire National des Arts et Métiers (CNAM) in Paris. With a research career spanning over 25 years, she has established herself as a leading expert in data quality, conceptual modeling, and ontology engineering. Her work bridges theoretical computer science with practical applications in healthcare systems, business process management, and knowledge representation. Her research interests focus on data quality assessment , conceptual modeling methodologies , ontology engineering for complex systems , and cyber-physical security in healthcare infrastructures . She has pioneered approaches for evaluating RDF data completeness, developing quality metrics for conceptual schemas, and creating ontologies for healthcare security. Her work demonstrates how formal modeling techniques can solve real-world problems in information systems. Analysis of her recent publications reveals a strong trend toward cyber-physical security and healthcare information systems , where she applies semantic technologies to address cascading effects in critical infrastructures. Her work consistently connects theoretical foundations in conceptual modeling with practical applications in knowledge graphs and data integration. She has made significant contributions to understanding how OWL semantics can be effectively utilized in RDF-based knowledge graphs. As an active member of the academic community, she has served as guest editor for special journal issues and contributed to major international conferences including RCIS, CAiSE, and EDOC. Her leadership in the field is evident through her editorial roles and collaborative research projects. Professor Si-Said Cherfi leads research within the CEDRIC laboratory, specifically contributing to the 'Complex data, machine learning and representations' and 'Data mining and statistics' research teams. Her work often involves interdisciplinary collaboration with healthcare professionals, security experts, and industry partners to address complex challenges in information systems security and data quality.

• Temporal Databases
• Time Series Analysis
• Database Systems
• +4 more

Anton Dignös is a professor at the Free University of Bozen-Bolzano , specializing in temporal databases , time series analysis , and database systems . His research focuses on efficient query processing for interval data, temporal joins, and schema design, with significant contributions to in-memory and time series databases. Key research areas include: Temporal Data Management : Advanced techniques for interval and duration queries. Time Series Analytics : Machine learning integration and pattern detection. Schema Optimization : Automated design and tuning of database schemas. Visual Analytics : Tools for period data comparison and correlation analysis. His work spans collaborations with researchers like Johann Gamper and Michael H. Böhlen , addressing challenges in healthcare systems, industrial applications, and financial data analytics. Notable contributions include algorithms for temporal anti-joins , range-duration queries , and machine learning-based anomaly detection .

• Database Systems
• Data Warehousing
• OLAP Analysis
• +3 more

Professor Zbyszko Królikowski is a faculty member at Poznań University of Technology, where he works in the Faculty of Computer Science and Telecommunications, specifically in the Institute of Computer Science. He holds the academic title of Professor (indicated by "prof. dr hab. inż.") and has been actively contributing to the field of computer science, particularly in database systems and data warehousing. His scientific work spans multiple disciplines, with 75% focus on Computer and Information Sciences and 25% on Information and Communication Technology. Professor Królikowski has established himself as an expert in data warehousing, having authored a comprehensive monograph titled "Data warehouses: logical and physical data structures" published in 2007. His research interests primarily revolve around database systems, with specific focus on: Data warehousing and OLAP analysis Logical and physical data structures for databases Sequential data analysis Materialized views and query optimization Database performance evaluation Evolution of data warehouse systems Professor Królikowski has maintained an active research profile with publications spanning nearly two decades, from the early 2000s to 2021. His work shows a consistent focus on database technologies, evolving from traditional relational database systems to more contemporary approaches including in-memory architectures and graph databases. Analysis of his publication trends reveals a progression from theoretical database modeling to practical applications in production planning and modern database technologies. He has contributed to the academic community not only through his publications but also by supervising doctoral research. Notably, he supervised Mikołaj Morzy's dissertation on "Advanced database structures supporting effective association discovery" in 2004 and has served as a reviewer for numerous other doctoral dissertations in related fields. Professor Królikowski has collaborated extensively with other researchers in the database community, particularly with scholars from Poznań University of Technology including Tadeusz Morzy, Bartosz Bębel, and Robert Wrembel. These collaborations have resulted in numerous joint publications that have contributed significantly to the field of data warehousing and database systems.

Hayden WimmerView profile

Associate Professor

• Artificial Intelligence
• Data Mining
• Digital Forensics
• +5 more

Dr. Hayden Wimmer is an Associate Professor in the Department of Information Technology at Georgia Southern University, with affiliate status at the Institute for Health Logistics & Analytics. He holds a PhD in Information Systems from the University of Maryland Baltimore County, an MS from UMBC, an MBA from Penn State, and a BS from York College of Pennsylvania. His research focuses on: Artificial Intelligence : Generative models, ethical safeguards, and neural network applications Data Science : Mining techniques for fraud detection and big data analytics Digital Forensics : Mobile device analysis and IoT security frameworks Publication analysis shows consistent output since 2012 (176+ works), with recent emphasis on AI ethics (2025), counterfeit detection systems (2025), and healthcare data interoperability (2017-2018). He leads multiple funded projects including: NSA grants for cybersecurity education ($200k+) Microsoft Azure research grants for cloud-based AI NSF-funded workforce development initiatives ($300k total funding) Dr. Wimmer directs the DAC Lab and holds key editorial positions in major information systems journals.

Sriram MohanView profile

Professor

• Data Science
• Computer Science Education
• NoSQL Databases
• +3 more

Sriram Mohan is a Professor and Department Head of Computer Science and Software Engineering at Rose-Hulman Institute of Technology. He has served as a consultant in Hadoop and NoSQL systems for clients in Media, Insurance, and Telecommunication sectors, and has been fundamental in revamping the software engineering program and founding the Engineering Design program. Education: PhD in Computer Science, Indiana University, 2007 MS in Computer Science, Indiana University, 2003 BE in Computer Science, University of Madras, 2001 Dr. Mohan's research spans data science and computer science education, with specific interests in NoSQL databases, Hadoop, distributed database systems, and software engineering pedagogy. He has integrated reflection and problem-based learning into the software engineering curriculum, fostering innovative educational approaches through studio-based integration of Humanities, Science, Math, and Engineering. Awards: Outstanding Young Alumni Award, School of Informatics and Computing, Indiana University (2015) He actively mentors students through curriculum development initiatives and serves as a facilitator for MACH, a faculty development program focused on building change agent capabilities among educators and administrators.

Patrick GirardView profile

Professor

• Human-Computer Interaction
• Task Modeling
• Interactive Systems Design
• +3 more

Patrick Girard is a Full Professor in Data Engineering at ISAE-ENSMA (Institut Supérieur de l'Aéronautique et de l'Espace - École Nationale Supérieure de Mécanique et d'Aérotechnique) in France. He is a member of the Data Engineering Team within the LIAS (Laboratoire d'Ingénierie des Applications de la Sensorique) laboratory, with dual affiliations at ISAE-ENSMA in Chasseneuil and ENSIP in Poitiers. Professor Girard's research focuses on Human-Computer Interaction , with particular expertise in task modeling , interactive systems design , and programming by demonstration techniques. His work spans theoretical foundations to practical applications in model-based development, user interface design methodologies, and educational technology for programming. He has made significant contributions to task model validation, simulation techniques, and the application of these principles in complex systems engineering, particularly in aerospace contexts. His publication history demonstrates a consistent evolution from foundational work on programming by demonstration and task-oriented architectures in the 1990s to more recent applications in complex systems engineering and avionics. A distinctive trend in his work is the integration of formal methods with practical HCI approaches, creating robust frameworks for developing user-centered interactive systems with safety-critical applications. Professor Girard has mentored numerous researchers throughout his career, with frequent collaborations showing sustained relationships with scholars like Loé Sanou, Nicolas Guibert, and Thomas Lachaume. His research has involved multiple interdisciplinary projects, often connecting academic research with industrial applications, particularly in the aerospace sector. Within the LIAS laboratory, Professor Girard works in the Data Engineering Team alongside colleagues in Automatic Control and Real Time research groups. The laboratory maintains strong industry partnerships, especially with aerospace companies, enabling practical implementation of theoretical research in real-world engineering contexts. His work bridges computer science theory with practical engineering applications, particularly in the French aerospace ecosystem.