Maj Schian Nielsen is a Senior Research Librarian at the University Library of the University of Agder. Her work focuses on multilingualism, crosslinguistic awareness, and German language pedagogy. She is affiliated with the research groups 'Media and Communication Studies' and 'Multilingualism in Society and Education (MUSE).' University of Agder Research Groups: Media and Communication Studies, MUSE Her research explores how multilingual awareness can enhance grammar instruction in German third-language (L3) teacher education programs across Denmark and Norway. Recent publications analyze curriculum structures, educational materials, and the integration of generative AI tools like ChatGPT in multilingual education contexts. Scientific output trends reveal a focus on: Cross-linguistic pedagogy L3 German acquisition Grammar teaching methodologies AI applications in language learning Teacher training for multilingual classrooms Systemic Functional Linguistics (SFL) frameworks She has not been publicly recognized with scientific awards listed in the available data.
Habib Ullah is an Associate Professor in Data Science at the Norwegian University of Life Sciences (NMBU), Norway, where he conducts research at the intersection of computer vision and machine learning. He is affiliated with the Institute of Data Science under the Faculty of Science and Technology. He has previously held academic positions at COMSATS University Islamabad, Pakistan, and the University of Ha'il, Saudi Arabia, and served as a postdoctoral researcher at The Arctic University of Norway. Educational Background: PhD in Information and Communication Technology (Computer Vision), University of Trento, Italy (2011–2015) MSc in Electronics and Computer Engineering, Hanyang University, South Korea (2007–2009) BSc in Computer Systems Engineering, NWFP University of Engineering and Technology, Pakistan (2002–2006) Habib Ullah's research is primarily focused on computer vision and machine learning, with applications in aquaculture, agriculture, and human behavior analysis. He investigates underwater fish feeding sounds using audio classification, develops zero-shot learning models for recognizing unseen classes, and applies deep learning to detect stress in salmon via skin dot patterns. He also explores AI-driven controlled environment agriculture, leveraging sensors and automation for optimal crop growth. His work emphasizes practical AI solutions for real-world challenges in environmental and biological domains. The recent publications highlight a strong trend in leveraging deep learning for zero-shot and semi-supervised learning, particularly in computer vision tasks such as sea ice classification, crowd anomaly detection, and agricultural monitoring. His research spans remote sensing, biomedical signal processing, and human activity recognition, demonstrating interdisciplinary versatility. The keywords reflect a focus on robust feature representation, knowledge transfer, and model generalization. Scientific Awards and Funding: Industrial PhD grant 'Advancing Controlled Environment Agriculture AI' from The Research Council of Norway (Project number 354125, 2 million NOK, 2024) Team member (Coordinator-Participant) in the Battery Cell Assembly Twin (BatCAT) project funded by Horizon Europe (7 mEuro, 2023–2027) Development of an AI-Based Image Analysis System for Monitoring Plant Status (Funding: 1.8 mNOK, starting 2025) Habib Ullah actively supervises PhD projects and contributes to academic service through editorial and organizational roles. He has served as an Associate Editor for IEEE Access, Guest Editor for MDPI Remote Sensing, and Editor of the Springer book Machine Learning Techniques and Sensor Applications for Human Emotion, Activity Recognition, and Support (ML-SHEARS) . He has also been a Track Chair and Program Committee Member for several international conferences, reflecting his leadership in the academic community. His research is supported by significant grants and collaborative projects, indicating strong institutional and international engagement. He is involved in multiple research teams and projects, including the BatCAT project on battery manufacturing and AI applications in controlled environment agriculture with RIFT LABS AS. His lab work integrates deep learning, sensor fusion, and data analytics for environmental and biological monitoring systems.
Egor Kostylev serves as an Associate Professor in the Department of Informatics within the Faculty of Mathematics and Natural Sciences at the University of Oslo. His research focuses on the theoretical foundations connecting symbolic and sub-symbolic artificial intelligence, particularly examining relationships between formal logic systems and machine learning approaches. His educational background includes an MSc (Specialist, 2005) and PhD (Candidate, 2009) from Lomonosov Moscow State University under Prof. Vladimir A. Zakharov. He subsequently held research positions at the University of Edinburgh (2010-2013) and the University of Oxford (2013-2020) before joining the University of Oslo in 2020. Kostylev's research interests center on bridging symbolic AI formalisms with sub-symbolic approaches. He investigates connections between various logics (Description Logics, Temporal Logics, Datalog), query languages (SPARQL, Regular Path Queries, OTTR), and machine learning formalisms (Graph Neural Networks, Markov Logic Networks). His work addresses critical challenges in Explainable, Trustworthy, and Green AI through theoretical foundations that connect different AI paradigms. His publication record demonstrates consistent high-impact contributions in theoretical computer science and AI, with numerous publications in top venues including AAAI, LICS, Journal of the ACM, and ICLR. His recent work shows a clear trajectory toward unifying logical reasoning with neural network approaches, particularly through graph neural networks and their connections to logical formalisms. The research spans theoretical foundations of knowledge representation, temporal reasoning in knowledge bases, and the logical expressiveness of modern neural architectures. As a research leader, Kostylev supervises multiple PhD students including Shuwen (Aurora) Liu, Maximilian Pflüger, Roxana Pop, Dongzhuoran Zhou, and Erik Snilsberg. He serves as a Research Theme Leader for the Integreat SFF: Norwegian Centre for Knowledge-driven Machine Learning. His teaching responsibilities include IN3020/4020 Database Systems courses. He leads the Data and Knowledge Management (DKM) research group at the University of Oslo, which focuses on foundational aspects of knowledge representation, database theory, and the intersection with modern machine learning techniques. The group actively collaborates with international researchers and contributes to advancing theoretical understanding of how symbolic and neural approaches to AI can complement each other.
Jaakko Timo Henrik Järvi is a Professor in the Department of Informatics at the University of Bergen, Norway, with additional affiliations at the University of Turku, Finland. His research focuses on programming language design, generic programming, and human-computer interaction, particularly in GUI frameworks and software reuse. His research interests include generic programming, programming language design (especially the Magnolia language), high-performance computing, array programming, and GUI engineering. He emphasizes formal methods and algebraic specifications to build reusable and efficient software systems. His work bridges theoretical foundations with practical applications in software development and education. The recent publications highlight a strong trend in declarative GUI frameworks, multi-selection models, and generic programming. His work explores domain-specific languages for GUI structure manipulation, reusable selection semantics across platforms, and optimizing array computations using the Mathematics of Arrays. These efforts reflect a consistent focus on software abstraction, correctness, and reusability. Jaakko Järvi has supervised doctoral students, including Tetiana Yarygina, whose dissertation explored microservice security. While no specific grants are detailed, his work on VisAST was supported by the Research Council of Norway (Project 250683), indicating active external funding. He frequently collaborates with researchers like Magne Haveraaen, Knut Anders Stokke, and Sean Parent. He contributes to tools and frameworks such as the MultiselectJS library and the VisAST educational tool. These are outcomes of collaborative research teams focused on improving software development practices and computer science education.
Anya Helene Bagge is an Associate Professor in the Department of Informatics at the University of Bergen, where she is a researcher at the Bergen Language Design Laboratory. Her work focuses on programming languages and software language engineering, with strong ties to education and tool development. Research Interests: Programming language design and implementation Software language engineering Semantics of programming languages Domain-specific languages and language extensions Program transformation using Rascal, MPL, and Stratego/XT Aspect-oriented programming, especially Domain-Specific Aspect Languages Her recent publications reflect a consistent focus on software language engineering, refactoring, microservice security, and programming education. Themes across her work include language design, program analysis, and the development of educational tools and methodologies. Scientific Awards: The Realist Committee's Teaching Award 2016/17 Lecturer of the Year in Computer Science (Spring 2015) Anya Bagge actively supervises students, including PhD and Master’s candidates such as Tero Hasu, Kristoffer Haugsbakk, and Nina Andersen. She has been involved in numerous academic activities, including organizing the OOPSLE workshop and serving on program committees for conferences like SLE, HILT, and WCRE. She has also taught core courses including INF101, INF225, and INF328, demonstrating a strong commitment to both research and teaching. Labs and Teams: She is affiliated with the Bergen Language Design Laboratory , collaborating with researchers such as Magne Haveraaen, Eva Burrows, and Tero Hasu.
Magne Haveraaen is a Professor in the Department of Informatics at the University of Bergen, where he leads the Bergen Language Design Laboratory (BLDL). He is actively engaged in research on programming theory, formal methods, language design, and high-integrity systems. His work centers on algebraic specifications, generic programming, domain engineering, and the design of the Magnolia programming language. He has been a long-standing instructor of key courses such as INF220 (Program Specification) and INF222 (Programming Languages), and contributes to national and international academic forums. University: University of Bergen School: Faculty of Mathematics and Natural Sciences Department: Department of Informatics Academic Rank: Professor Email: magne.haveraaen@uib.no His research interests include programming language design, formal specifications, generic and mouldable programming, multicore and GPU computing, and algebraic methods in software development. He emphasizes correctness, reuse, and high-integrity software through theoretical and practical innovations. He has contributed extensively to the literature on algebraic reasoning, array programming, and domain-specific abstractions. The recent publications highlight a consistent focus on algebraic semantics, language design (especially Magnolia), array programming, and formal verification. Themes across these works include correctness by design, specification-driven development, and adapting programming models for modern architectures. His involvement in workshops like ARRAY, WGP, and CALCO underscores his leadership in programming language theory. No scientific awards are listed in the provided texts. He advises students and welcomes collaboration in programming theory, language design, and formal methods. He has led funded projects such as MoSIS and SHIP and is involved in the High Integrity Systems Forum. He organizes and participates in key conferences including NWPT, GPCE, and SCAM. He leads the Bergen Language Design Laboratory (BLDL), which focuses on experimental language design, and contributes to the SAGA initiative on scientific computing with algebraic abstractions. His work integrates theory with practical tooling and language implementation.
Vibeke Roggen is an Associate Professor emerita at the University of Oslo's Department of Classics, specializing in Neo-Latin studies, textual criticism, and Latin grammar. Her academic career includes leadership roles as Chair of Norway's National Council for Greek and Latin (2007–2011) and director of a cooperative project between Oslo and Azerbaijan University of Languages (2008–2013). Her research spans multiple Neo-Latin domains including the transmission of Catullus, analysis of Petrarch's Africa , and pedagogical approaches to classical languages. She maintains active engagement in public scholarship through initiatives like NRK Radio's 'Den lille latinskolen' program. Publication analysis reveals sustained focus on Latin linguistics and historical transmission, with recent works including comprehensive Latin grammars (2022) and dictionaries (2015). Her scholarly output demonstrates consistent exploration of language evolution, cross-cultural linguistic connections, and pedagogical applications of classical studies across different historical periods.
Ragnhild Kobro Runde is an Associate Professor in Computing Education at the Department of Informatics, University of Oslo. Her work focuses on software engineering methodologies, formal methods in system design, and computing education at both secondary and undergraduate levels. She is affiliated with the Computing Education research group. Her research explores topics such as UML sequence diagram semantics, formal specification techniques (Event-B/STAIRS), and the transition from block-based programming (Scratch) to text-based languages (Python) in schools. She also investigates how ICT exposure impacts mathematics self-belief and academic performance in PISA assessments. Runde has contributed to over 30 peer-reviewed publications since 2005, appearing in journals like Formal Aspects of Computing and Software and Systems Modeling. Her work frequently addresses challenges in software design, security risk analysis, and service-oriented architecture modeling using UML extensions. Key contributions include developing pattern languages for web application security risk analysis, analyzing nondeterminism in sequence diagrams, and creating methodologies for dynamic service composition using UML 2.x. She has collaborated with international researchers on computing education initiatives and formal methods applications.
Ludmila Ivanova Torlakova is an Associate Professor at the Department of Foreign Languages, University of Bergen, specializing in Arabic linguistics and phraseology. Her work explores idioms, figurative language, and metaphorical frameworks across political, literary, and educational contexts, with a focus on Modern Standard Arabic and its socio-cultural dimensions. Her research spans metaphor analysis in crisis communication (e.g., Oman's COVID-19 discourse), political rhetoric, and literary texts like Hanan al-Shaykh's novels. She investigates ʾiḍāfah constructions, body-part idioms, and pedagogical strategies for teaching multi-word expressions, contributing to lexicography and media studies. Torlakova’s publications highlight trends in Arabic phraseology, including the persistence of historical idioms in contemporary media and metaphorical framing in political and health-related discourses. Her academic lectures address topics such as curriculum design for Arabic programs and the intersection of language and cultural identity.
Kazuhiro Ogata is a Professor in the School of Information Science at Japan Advanced Institute of Science and Technology (JAIST). He actively teaches courses such as i116 Basic of Programming, i217 Functional Programming, and i219 Software Design Methodology, indicating a strong commitment to computer science education and curriculum development. Institution: Japan Advanced Institute of Science and Technology (JAIST) School: School of Information Science Position: Professor Email: ogata@jaist.ac.jp Research Laboratory: http://www.jaist.ac.jp/~ogata/lab/ His research interests center on programming languages, software design methodology, formal methods, and compiler construction. He emphasizes formal verification using theorem proving and rewriting logic, particularly with tools like Maude. His work bridges theoretical computer science with practical software engineering and education, focusing on correctness, design patterns, and language semantics. The analysis of his recent publications reveals a consistent focus on formal specification, verification of software systems, and educational tools for programming. His work spans functional programming, concurrent systems, and distributed algorithms, often using rewriting logic as a unifying framework. He integrates formal methods into both research and teaching, promoting rigorous software development practices. No scientific awards are explicitly mentioned in the provided texts. Kazuhiro Ogata advises students through his laboratory at JAIST and has developed structured course materials that suggest active mentorship. While specific grant information is not available, his sustained research output and tool development imply ongoing project funding. He contributes to academic outreach through summer schools and educational frameworks. He leads a research laboratory focused on formal methods and programming language design, fostering a collaborative environment for students and researchers. The lab develops tools for teaching and verifying software systems, emphasizing correctness and educational impact.
Silvia Lizeth Tapia Tarifa is an Associate Professor in the Department of Informatics at the University of Oslo, specializing in formal methods for parallel and distributed systems. She serves as one of the principal investigators for the NFR SJM (Smart Journey Mining) project, which runs until 2026, and actively participates in Digital Twins research with a focus on GDPR-compliant data management. Her academic affiliations include the Reliable Systems research group and the Analytical Systems and Reasoning (ASR) group at the Department of Informatics. Professor Tapia Tarifa's research spans formal methods, concurrency theory, and distributed systems with particular emphasis on self-adaptive systems, semantics of concurrent languages, compositional reasoning about distributed system behavior, and formal modeling of resource usage. Her work bridges theoretical computer science with practical applications in digital twins, GDPR compliance, and resource management in distributed environments. She has made significant contributions to the ABS language framework and active object models for parallel and distributed computing. Her publication record shows a consistent focus on formal verification techniques applied to emerging challenges in distributed computing. Recent work demonstrates increasing attention to digital twins technology, user journey modeling, and privacy-preserving systems. The research trajectory reveals evolution from foundational work on concurrent language semantics toward applied research in self-adaptive systems and GDPR-compliant architectures, while maintaining strong theoretical underpinnings in formal methods. Young Research Talent grant from Research Council of Norway (2017), the only computer science grant in that call Fellow at United Nations University, International Institute for Software Technology (2007) Active participation in formal methods community as general chair, PC chair, and committee member Professor Tapia Tarifa has supervised PhD and master's students while teaching graduate-level courses. She has led significant research initiatives including the Analysis and Complex System Research Program at SIRIUS Center (ended 2023) and the EU MSCA-ITN REMARO project on Reliable AI for Marine Robotics (ended 2024). Her current research portfolio includes multiple active grants focused on digital twins, user journey analysis, and privacy-preserving distributed systems. She collaborates extensively with researchers across Europe through various EU-funded projects including FP7 ENVISAGE, FP7 FET UpScale, and FP7 FET HATS. Her research activities are centered around the ABS language framework and its applications to distributed systems verification. She maintains active collaborations through the SIRIUS Center and participates in the international formal methods community through conference organization and program committees.
Crystal Chang Din is an Associate Professor at the Department of Informatics, University of Bergen. Her research focuses on formal methods, software verification, and didactics. She has organized conferences such as the KeY Symposium 2023 and served as PC Chair for FTfJP 2025. Her work includes developing verification tools like KeY-ABS and exploring concurrency semantics in programming languages. She teaches courses including INF113 (Operating Systems) and INF100 (Introduction to Programming). Notable contributions include modular reasoning systems for code reuse and runtime enforcement frameworks. She advises master’s students such as Eirik Halvard Sæther and Ida Sandberg Motzfeldt. Her publications span topics like feature model evolution, deadlock detection, and concurrent programming semantics. She has contributed to international journals like Formal Aspects of Computing and conferences such as NWPT and iFM. Her research emphasizes practical applications in distributed systems and formal verification techniques.
Einar Broch Johnsen is a Professor at the Department of Informatics, University of Oslo. His research focuses on programming models, formal methods, and distributed systems, with significant contributions to languages like ABS and SMOL. He has led major projects including the Sirius Center (2015-2023) and EU initiatives Envisage and HyVar. His work spans asynchronous systems, cloud computing, and digital twins, emphasizing rigorous verification techniques. Recent publications show a trend toward AI integration, robotics, and knowledge-based systems, blending formal methods with practical applications in autonomous decision-making and semantic validation. Johnsen holds editorial and committee roles for journals including Formal Aspects of Computing and conferences like FASE and iFM. He teaches courses on computability and concurrency models, advancing both theoretical and applied aspects of software engineering.
Tom Heine Nätt is an Associate Professor at the Department of Computer Science and Communication at Høgskolen i Oslo og Akershus. His academic work focuses on foundational computer science concepts, information security, and programming language theory. He has contributed extensively to technical lexicon entries covering IT infrastructure, cyber-security practices, software development methodologies, and digital literacy education. His research interests include exploring system reliability through redundancy mechanisms, mitigating cyber-threats via robust validation techniques, and clarifying core IT concepts for educational purposes. He has authored over 50 entries in the Store Norske Leksikon , addressing topics ranging from API architecture to quantum computing basics . Professionally, he teaches courses in software engineering and cyber-security at HiOA. His publications consistently emphasize clear technical communication and practical application of theoretical principles.
Tore Brattli is a Senior Lecturer and Study Program Manager in Media and Documentation Science at the Department of Language and Culture, UiT The Arctic University of Norway, under the Faculty of Humanities, Social Sciences and Teacher Education. He plays a key role in shaping the BA, MA, and one-year programs in media and documentation science, with a focus on information technology integration. His research interests include: Information Retrieval Search Engines Databases Digitalization Classification and Cataloging Knowledge Organization Semantic Change in Digital Terminology His teaching spans courses such as Databases, Search Engines and Data Modeling (MDV-1004), Document Organization and Retrieval (MDV-1201), Document Institutions in a Digital Age (MDV-1210), and Big Data, Social Media and Retrieval (MDV-3051). His recent publications reflect a strong focus on the evolution of digital concepts, classification systems like Dewey Decimal, and innovations in library services, especially in digital and networked environments. Themes across his work include the transformation of scholarly communication, automatic classification using semantic indexing, and the impact of digital media on traditional library structures. Notable scientific contributions include studies on the semantic expansion of the term "digital," experiments in automatic classification for public libraries, and analyses of digital journal paradigms. His work bridges library science, information systems, and digital humanities. He advises on curriculum development and leads program management but no formal advisees or students are listed. There is no mention of grants, awards, or laboratory affiliations. His research is primarily theoretical and applied within academic and library contexts.
