جست‌وجوی استاد و پژوهشگر

Lasse Mårtenssonمشاهده پروفایل

استاد

• Medieval Nordic Languages
• Philology
• Paleography
• +۴ مورد دیگر

Lasse Mårtensson is Professor of Nordic Languages at Uppsala University's Department of Nordic Languages, specializing in medieval Nordic philology, paleography, and digital manuscript analysis. His current research focuses on scribal attribution, text transmission, and Nordic onomastics, with leadership roles in major projects like the Riksbankens jubileumsfond-funded 'Digitization of West Nordic Manuscripts' (2022–2025). Research Interests: Martensson's work spans three core areas: Grafonomy & Paleography : Developing computational methods to analyze scribal habits in medieval manuscripts using digital tools like quill-feature analysis. Textual Criticism : Critical editions of Old Norse/Icelandic texts (e.g., Codex Upsaliensis ) for the Medieval Nordic Text Archive (MENOTA). Onomastics : Quantitative study of personal names in medieval Swedish runic inscriptions, highlighting Viking Age naming traditions. Publication Trends: His 15 most recent articles (2010–2025) demonstrate a consistent focus on integrating digital humanities with traditional philology, particularly in scribal identification, orthographic analysis, and Old Norse textual studies. Computational paleography and quantitative approaches dominate his methodological innovations. Awards & Honors: Dag Strömbäcks belöningsfond (2015) for the monograph Skrivaren och förlagan . Westinska priset (2008) for his doctoral dissertation. Icelandic Ministry of Education Scholarship (1999–2000). Supervision & Projects: Advises PhD student Birger Mård on Old Swedish bynames. Secured 13.4M SEK (2016–2020) for the project 'Nya ögon på Sveriges medeltida skrivare,' applying digital paleography to Swedish medieval scribes. Co-investigator in 4+ international projects including 'Konungsbók Snorra Eddu' (Iceland, 2016–2018). Academic Service: Co-editor of Scripta Islandica (2013–present), chair of the Icelandic Society, board member of Svenska fornskriftsällskapet and Kungl. Humanistiska Vetenskaps-Samfundet, and coordinator of the Early North European Seminar (ENES).

• Systems Security
• Applied Cryptography
• Web Security
• +۳ مورد دیگر

Pablo Picazo-Sanchez is an Associate Senior Lecturer at the School of Information Technology at Halmstad University. His research focuses on systems security and applied cryptography, with emphasis on areas like Web Security, Browser Extensions, Biometrics, and RFID Security. He has published extensively in top-tier conferences and journals since 2023. His recent work includes developing frameworks for detecting fake browser extension reviews (FakeX), analyzing parliamentary debates using computational linguistics (Policy Parsing Panthers), and enhancing password security via client-side stretching (Clipaha). He also contributes to advancing cryptographic protocols (IBE.js, Attribute-based encryption with enforceable obligations) and educational technology (Closing the Gap). His research trends highlight a blend of cybersecurity innovation and interdisciplinary applications in AI ethics, language processing, and automated systems.

Marcus Klangمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Marcus Klang is a Research Engineer at the Department of Computer Science , Lund University , affiliated with the Robotics and Semantic Systems research group. He contributes to initiatives like eSSENCE (e-Science Collaboration) and ELLIIT (Linköping-Lund IT and mobile communication initiative). His work focuses on automatic methods for identifying and connecting entities in natural language text, leveraging multilingual open data sources like Wikipedia and knowledge graphs like Wikidata. Research Areas: Natural Language Processing, Machine Learning, Entity Linking, Knowledge Graph Construction Key Contributions: Development of scalable text processing systems for biomedical domains His research aligns with UN Sustainable Development Goals in health and information systems. He actively collaborates in projects such as AI-based text mining for medicine and leads technical development in named entity recognition frameworks like EasyNER. Recent projects include: Artificial intelligence-based text mining for medical domains Biomedical text mining for systems biology AI Lund research network He has participated in public outreach activities like Robotics Week for schools and interdisciplinary workshops on AI ethics.

Sándor Darányiمشاهده پروفایل

استاد

• Digital Libraries
• Information Retrieval
• Digital Preservation
• +۵ مورد دیگر

Sándor Darányi is a Professor at the Swedish School of Library and Information Science, University of Borås (since 2011), with a career spanning over four decades in information science, digital libraries, and cultural heritage preservation. He also holds an Honorary Professorship at Szeged University, Hungary. His research focuses on advanced access to digital libraries, automatic indexing, information visualization, digital preservation, narrative genomics, and quantum interaction models for semantics. Education: Candidate of Science (CSc) in Ethnography, Hungarian Academy of Sciences (1994) PhD in Information Science, Eötvös Loránd University (1989) MA in Library and Information Science, Eötvös Loránd University (1985) MSc in Agricultural Sciences, University of Agriculture (1975) Research Interests: Darányi’s work bridges computational methods with cultural studies, including: - Formalization of folk narratives for big data analysis - Quantum-inspired models of semantic change - Haptic interfaces for accessibility in museums - Evolving semantics in digital ecosystems - Cultural heritage digitization projects Professional Activities: Editorial Board Member of Journal of Information Science Education Organized major conferences such as SEMANTiCS, IC-ININFO, and AMICUS workshops Supervised doctoral students in computer science and information studies Co-developed the PERICLES project on digital preservation Labs/Teams: His research groups have pioneered projects like the MuseIT inclusive museum initiative and the SHAMAN digital preservation framework, leveraging high-performance computing and cloud technologies.

Lili Jiangمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Privacy Protection
• Fairness in AI
• +۴ مورد دیگر

Lili Jiang is an Associate Professor at the Department of Computing Science, Umeå University, where she serves as Director of Studies and Programme Director for the MSc in Computing Science. She holds a PhD in Computer Science with expertise in AI trustworthiness, data mining, and natural language processing. Her research bridges computer science and artificial intelligence, focusing on privacy, fairness, and federated learning systems. Her research interests center on: Developing trustworthy AI systems with emphasis on privacy-preserving techniques Ensuring algorithmic fairness in socio-technical decision-making Advancing few-shot learning methods for NLP tasks Creating robust data federation frameworks for cross-database analysis Recent publications demonstrate strong focus on few-shot learning (particularly in NLP), privacy-preserving AI , and applied data mining for industrial/environmental systems. Her work consistently addresses real-world challenges through multimodal learning and explainable AI techniques. She leads the Deep Data Mining research group and collaborates with the Interpresence institute. Key projects include: Explainable, Safe, Contact-Aware Planning for Heavy Machinery (XSCAVE, 2024-2028) Assessment and Engineering of Equitable AI Systems (2022-2024) Privacy-aware Federated Database Infrastructure for Micro-Data Analysis (2018-present)

• Uncertainty management
• Information fusion
• Probabilistic expert systems
• +۸ مورد دیگر

Joel Brynielsson serves as an Associate Professor at KTH Royal Institute of Technology within the Division of Theoretical Computer Science, School of Electrical Engineering and Computer Science, while simultaneously holding the position of Research Director at the Swedish Defence Research Agency (FOI) since 2008. His academic credentials include a Ph.D. in Computer Science (2006) and M.Sc. in Computer Science and Engineering (2000), both from KTH, followed by achieving Docent (Habilitation) status in Computer Science in 2015. Dr. Brynielsson's research spans uncertainty management, information fusion, probabilistic expert systems, command and control systems, operations research, game theory applications, web mining, privacy-preserving data mining, and cyber security. His work bridges theoretical computer science with practical security applications, particularly in national defense contexts. His recent publication record shows consistent scholarly output through 2024, with research focusing on cybersecurity practices in Swedish administrative authorities, cyber-threat perception in the financial sector, and social media applications for crisis management. The interdisciplinary nature of his work is evident in collaborations across security, defense, and emergency management domains. Associate editor for Springer Security Informatics journal Technical program chair for IEEE EISIC conferences (2013-2019) Regular reviewer for security and informatics journals Research funding from EU, Swedish Armed Forces, and public authorities Through his dual appointments, Dr. Brynielsson maintains a vital connection between academic research and practical defense applications, contributing significantly to both scholarly knowledge and real-world security solutions.

• Natural Language Processing
• Clinical Text Mining
• Artificial Intelligence
• +۷ مورد دیگر

Hercules Dalianis is a Professor at the Department of Computer and Systems Sciences, Stockholm University. His research focuses on Natural Language Processing, particularly in clinical text mining for Swedish language data. He leads the Natural Language Processing Research Group and serves as director of the Health Bank - Swedish Health Record Research Bank infrastructure. MSc in Electrical Engineering (1984), KTH PhD in Technology (1996), KTH Professor of Computer and Systems Science (2011), Stockholm University His research addresses privacy-preserving NLP for clinical text analysis, including automated de-identification , domain adaptation of BERT models , and clinical entity recognition . Current projects like DataLEASH and Privacy-Preserving Techniques explore machine learning solutions that balance data utility with patient confidentiality. Key publication trends show emphasis on Swedish clinical text processing , ICD-10 coding automation , and privacy-aware language modeling . Collaborations span Karolinska University Hospital, Nordic healthcare institutions, and international AI research communities. He teaches courses in Internet Search Techniques and Business Intelligence (ISBI) , Natural Language Processing (NLP) , and Principles and Foundations of Artificial Intelligence (PFAI) . His work has produced the open-access textbook Clinical Text Mining: Secondary Use of Electronic Patient Records , establishing foundational frameworks for clinical NLP in low-resource languages.