جست‌وجوی استاد و پژوهشگر

Andreas L Opdahlمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Graphs
• Information Systems Development
• +۴ مورد دیگر

Andreas L Opdahl is a Professor at the Department of Information Science and Media Studies at the University of Bergen. He leads the Intelligent Information Systems (I2S) research group, focusing on AI-driven solutions for news media and public sectors, including knowledge graphs, ontologies, and large language models. His work emphasizes ethical AI integration in journalism and data quality frameworks for automated fact-checking. Research interests span AI applications in media, cybersecurity, enterprise modeling, and semantic technologies. Notable contributions include developing methodologies for hacker attack representation (HARM), integrating safety and security requirements (CHASSIS), and advancing knowledge graph platforms for newsrooms. His publications address challenges in information systems development, including interoperability, ontology evaluation, and multi-perspective problem analysis. Opdahl has contributed to foundational work on misuse cases for security threat modeling and semantic quality criteria in requirements engineering. His recent research explores emerging technologies like LLMs for news classification and the ethical dimensions of AI in journalism. He has been involved in projects such as the News Angler platform and semantic annotation frameworks using real-time data. His academic career includes roles as an author in leading conferences (e.g., IEEE, ACM) and journals, with a focus on conceptual modeling, enterprise systems, and requirements engineering. Collaborations span institutions like NTNU, the University of Amsterdam, and international research networks.

• Media and journalism studies
• Media and conflict
• Freedom of speech
• +۶ مورد دیگر

Kristin Skare Orgeret is a Professor at the Institute of Journalism and Media Studies , Faculty of Social Sciences, OsloMet – Større Oslo universitet. Her work focuses on media and conflict , freedom of speech , media's societal role , and power relations . She leads the MEKK (Media in War and Conflict) research group and the NFR-funded DD-MAC project (Decoding Digital Media in African regions of Conflict), as well as international collaborations under NORPART and Intpart programs. Research Themes : Digital journalism in conflict zones, fact-checking under authoritarian regimes, journalist safety, and media's role in democratic transitions. Projects : DD-MAC (2021–2025), NORPART (Tanzania, Uganda, Nicaragua, Colombia), Safety Matters (Brazil, South Africa, USA). Awards : OsloMet Communication Prize 2022. Expertise : Media in conflict, digital disinformation, African media dynamics, and press freedom. Her recent publications analyze social media weaponization in Mali, disinformation trends, and the evolution of digital journalism globally. She actively contributes to public debates on media ethics and freedom.

Mateus De Oliveira Oliveiraمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Automated Theorem Proving
• Parameterized Complexity
• +۳ مورد دیگر

Mateus De Oliveira Oliveira is an Associate Professor in the Department of Informatics at the University of Bergen. His research focuses on theoretical computer science, automated theorem proving, parameterized complexity, formal verification, graph theory, and computational logic. His work spans algorithm design for constraint satisfaction problems, automated reasoning systems, and formal verification techniques. Notable contributions include advancements in width-based automated theorem proving, Petri net synthesis, and parameterized complexity analysis for graph algorithms. He leads the Autoproving project funded by the Research Council of Norway, exploring automated theorem proving through parameterized complexity theory. Recent publications highlight developments in symbolic functional decomposition, state canonization for theorem proving, and optimal dynamic programming algorithms. His research bridges foundational theory with practical applications in automated systems and formal methods.

• Drilling Automation
• Autonomous Systems
• Verification and Validation
• +۷ مورد دیگر

Rodica Georgeta Mihai is an Associate Professor in the Department of Informatics at the University of Bergen, Norway. She is also affiliated with NORCE Norwegian Research Centre AS, where she contributes to advanced research in drilling automation and digital well technologies. Her work bridges theoretical computer science and practical engineering applications in the energy sector. Position: Associate Professor Institution: University of Bergen Department: Department of Informatics Affiliation: NORCE Norwegian Research Centre AS Email: rodica.g.mihai@uib.no Phone: +4755584350 Her research interests lie at the intersection of computer science and petroleum engineering, focusing on drilling automation, autonomous systems, verification and validation in distributed control environments, AI safety, and graph algorithms . She explores how intelligent systems can make safe and efficient decisions in complex, uncertain drilling conditions. The recent publications demonstrate a strong trend toward applied AI in drilling operations, particularly in autonomous decision-making, safe mode transitions, distributed control, and online verification of multi-vendor systems . Earlier works were rooted in theoretical computer science, especially graph searching and structural graph theory. The shift reflects a move from foundational algorithms to real-world deployment in energy systems. Rodica Mihai is actively involved in major research initiatives, including the DigiWells project, funded by the Research Council of Norway and industry partners such as Equinor and Aker BP. Her work emphasizes system reliability, safety, and interoperability in automated drilling environments. DigiWells: Digital Well Center for Value Creation, Competitiveness and Minimum Environmental Footprint Demonstration of Automated Drilling Process Control She advises on the design of safe and resilient automation systems, ensuring smooth human-machine transitions and robust operation under uncertainty. Her contributions are presented at leading conferences such as SPE/IADC and include guest lectures at institutions like BI Norwegian Business School.

Duc Tien Dang Nguyenمشاهده پروفایل

استاد

• Multimedia AI
• Deepfake Detection
• Image Forensics
• +۳ مورد دیگر

Duc Tien Dang Nguyen is a Professor at the Department of Information and Media Studies , University of Bergen , Norway. He actively contributes to the Intelligent Information Systems (I2S) research group, focusing on Multimedia AI , Deepfake Detection , and Image Forensics . His work addresses Information Disorder through algorithmic solutions and cross-modal analysis. Education : Implied PhD in Computer Science or related field Research Trends emphasize visual content verification , generative synthetic data for detection, and UX/UI design in lifelog systems. Recent publications (2024) explore vision-language models and context-aware algorithms for misinformation. Grants include funding from the Research Council of Norway (Ref: 309339) . Collaborations span institutions including Kristiania University College , Vietnam National University , and University of Trento .

• Computer Science
• Software Engineering
• Process Analysis
• +۵ مورد دیگر

Associate Professor Patrick Stünkel is affiliated with the Western Norway University of Applied Sciences (HVL) within the Department of Computer Science, Electrical Engineering and Mathematical Sciences. He has taught courses such as ING301: Computer Science and Advanced Programming for Engineers (Spring 2026). His research focuses on Computer Science , particularly in Software Engineering , Formal Methods , and Multi-Modeling . Key Research Areas Control Flow Analysis for BPMN Models Runtime Verification of Timed Petri Nets Behavioral Consistency in Multi-Modeling Process Data Science in Digital Pathology Comprehensive Systems for Multi-Model Consistency Publications Trends 2024 works emphasize BPMN validation , visual debugging tools , and timed Petri net verification . 2023-2022 research explores pathology workflow optimization and multi-model consistency frameworks . Earlier works (2017-2020) address graph rewriting , model repair , and database refactoring tools .

• Model-Driven Engineering
• Formal Methods
• Business Process Modeling
• +۵ مورد دیگر

Professor Yngve Lamo is a faculty member at Western Norway University of Applied Sciences (HVL) in the Department of Computer Science, Electrical Engineering and Mathematical Sciences. His research spans formal methods, model-driven engineering, and healthcare information systems with a particular focus on business process modeling and mental health technology applications. Institution: Western Norway University of Applied Sciences Department: Computer Science, Electrical Engineering and Mathematical Sciences Location: Bergen KRONSTAD D410 Contact: +47 55 58 75 67 Professor Lamo's research focuses on formal methods in software engineering, particularly model-driven engineering approaches for business process modeling and analysis. His work demonstrates significant contributions to BPMN formalization using graph transformation systems, multi-model consistency management, and healthcare information systems. He has developed tools like the Visual Debugger and BPMN Analyzer 2.0 that provide practical solutions for model analysis and verification. His publication trends reveal a strong focus on applying formal methods to healthcare systems, particularly in mental health technology. Recent work (2022-2024) shows increasing emphasis on privacy-preserving data analysis, adaptive mental health systems, and multi-dimensional health data frameworks. His research bridges theoretical computer science with practical healthcare applications, demonstrating consistent productivity with numerous publications each year across top venues in software engineering and health informatics. Professor Lamo has made significant contributions to model-driven engineering, particularly in the areas of BPMN analysis, multi-model consistency, and healthcare information systems. His work on the Visual Debugger tool and BPMN Analyzer 2.0 represents practical applications of his theoretical research in formal methods. His research program demonstrates strong continuity in model-driven engineering approaches while expanding into healthcare applications. Current projects focus on adaptive technology for mental health care, privacy-preserving data analysis for health systems, and advanced techniques for multi-model consistency management. Professor Lamo's work shows strong interdisciplinary collaboration, particularly between computer science and healthcare domains.

• Software Engineering
• Programming Languages
• Runtime Verification
• +۳ مورد دیگر

Volker Stolz is a Professor at the Department of Informatics, University of Bergen, within the Faculty of Mathematics and Natural Sciences. He teaches Mobile Application Development (DAT153), Model-driven Software Engineering (DAT355), Model Checking (PCS955), and Refactoring (DAT159). He serves as program director for INF/INF-F/INF-H programs and exchange coordinator for DATA & INF, with his office located at Kronstad (D403). His research focuses on Software Engineering, particularly Programming Languages and Software Testing, where he develops productivity tools to create safer, faster code with fewer crashes in applications. His work spans Runtime Verification, Formal Methods, and Internet of Things (IoT), emphasizing model-driven approaches for reliable software systems in mobile and web environments. Recent publications (2024-2025) demonstrate deep engagement with Runtime Verification for timed systems, advanced software testing techniques like clone elimination, and emerging applications in IoT data acquisition. His work bridges theoretical computer science with practical engineering challenges, particularly in time-series analysis and formal verification of concurrent systems. Stolz leads significant research initiatives including: Ongoing: MSCA DN "TUAI - Towards an Understanding of Artificial Intelligence" Completed: EU H2020 project "COEMS - Continuous Observation of Embedded Multicore Systems" Completed: AURORA bilateral project "SecuTrace" (NO/FR, 2020-2022) Completed: DIKU/CAPES bilateral project "Modern Refactoring" (NO/BR, 2017-2021) He serves as General Chair for ECOOP'25, a premier conference in object-oriented programming. He actively contributes to the Smart Software System (S3) research group and IoT research lab at the University of Bergen, driving innovation in software verification and reliable system development through collaborative projects and industry partnerships.

Harald Königمشاهده پروفایل

استاد مدعو

• Software Engineering
• Formal Methods
• Model Transformations

Harald König serves as Adjunct Professor at Fachhochschule für die Wirtschaft Hannover (FHDW) in Germany. His research focuses on formal methods in software engineering, particularly model transformations and theoretical foundations of computer science. König has industry experience from SAP AG where he worked on financial services software including claims management systems. His current research examines: Multi-model consistency management Formal foundations of object-oriented modeling Graph transformations Category theory applications König collaborates on developing formal frameworks for model repair and consistency checking in software engineering, with recent publications focusing on colored Petri nets and verification techniques.

Lars Michael Kristensenمشاهده پروفایل

استاد

• Formal Methods
• Software Engineering
• Model Checking
• +۱ مورد دیگر

Lars Michael Kristensen is Professor in the Department of Computing, Mathematics, and Physics at Western Norway University of Applied Sciences. He received his Ph.D. from University of Aarhus (2000) and conducts research on formal methods for concurrent systems, particularly Coloured Petri Nets (CPNs) and model checking techniques. His research focuses on: Explicit state space exploration algorithms Software verification and testing Model-driven engineering Industrial applications of formal methods Kristensen leads projects applying formal methods to industrial automation, IoT protocols, and distributed systems. He co-authored the standard textbook on Coloured Petri Nets and co-develops the CPN Tools software suite. His awards include the Danish Research Councils' Young Researcher Award (2007).

• Computer Science
• Software Engineering
• Systems Reliability
• +۳ مورد دیگر

Åsmund Aqissiaq Arild Kløvstad is a Research Fellow at the University of Oslo's Department of Reliable Systems within the Faculty of Mathematics and Natural Sciences. His work focuses on formal methods, software engineering, and systems reliability. He is involved in the project BedreFlyt: A Digital Twin for Resource Planning in Healthcare , demonstrating expertise in healthcare informatics and resource optimization. Kløvstad’s research intersects theoretical computer science with practical applications in concurrency, formal verification, and algorithmic correctness. While specific educational background details are not provided, his publications indicate advanced expertise in programming languages, symbolic execution, and formal semantics. No awards or student advisement roles are explicitly listed, though his contributions to peer-reviewed journals highlight active research engagement.

Nikolay V. Shilovمشاهده پروفایل

استادیار

• Formal Methods
• Program Logics
• Model Checking
• +۱۲ مورد دیگر

Nikolay V. Shilov is an Assistant Professor at Innopolis University, Russia, affiliated with the School of Software Engineering and the Institute of Information Systems. He holds a PhD and has over 30 years of experience in theoretical computer science, formal methods, and logic in computer science. Education: Ph.D. in Computer Science, Novosibirsk Computing Center of Siberian Branch of the Soviet Academy of Sciences, 1987 His research interests span Formal Methods , Program Logics , Model Checking , Knowledge Representation , Multiagent Systems , and Computer Language Ontology . He has extensive experience in applying dynamic logic, temporal logic, and description logic to problems in software verification and knowledge reasoning. His recent work emphasizes formal verification of standard mathematical functions and cyber-physical systems. The 15 most recent publications reflect a strong focus on formal verification , education in formal methods , multiagent systems , and platform-independent specification . Topics include model checking with floating-point arithmetic, recursion elimination, functional programming pedagogy, and ontology for computer languages. There is a consistent thread of bridging theory with practical applications in software engineering and education. Scientific Awards and Honors: No specific awards listed in the provided text. Nikolay Shilov has supervised several Master’s and PhD students, including Peter Schneider, Sergey Berezin, Evgeny Bodin, Natalia Garanina, and Aizhan Sateckbayeva. He has been involved in externally funded research projects supported by the Russian Basic Research Foundation, focusing on formal specification and verification of standard mathematical functions and natural language-based requirement extraction. He is also active in academic service, serving on program committees of major conferences like FM 2019 and co-chairing the PSSV workshops since 2016. He leads and participates in research seminars such as ru-STEP (Russian Seminar on Software Engineering, Theory and Experimental Programming) and is deeply involved in programming contests, including the Open All-Siberian Programming Contests, emphasizing the educational value of formal methods and algorithmic thinking.

• Human-Computer Interaction
• Universal Design of ICT
• Web Accessibility
• +۵ مورد دیگر

Evelyn Eika is an Associate Professor at OsloMet – Oslo Metropolitan University , affiliated with the Faculty of Technology, Art and Design within the Department of Computer Science – Human-Computer Interaction and Universal Design of ICT . Her work focuses on improving accessibility and usability in digital systems, particularly for screen reader users and educational technology applications. Academic Rank : Associate Professor Research Groups : Universal Design of ICT (UD-ICT) Research Interests : Evelyn’s research spans Human-Computer Interaction , Universal Design of ICT , and Web Accessibility . She investigates text readability for assistive technologies, student engagement in digital learning environments, and the role of design thinking in engineering education. Recent work includes pragmatic attendance management systems and grammar-checking tools for accessibility. Key Trends in Publications : Her 15 most recent articles (2025–2018) emphasize accessibility , usability , and educational technology , with subfields like screen reader optimization, sentence length analysis, and peer feedback mechanisms in academic writing. Labs & Collaborations : Evelyn collaborates with the Applied Artificial Intelligence and UD-ICT research groups at OsloMet. She works with professors like Frode Eika Sandnes on projects involving web accessibility, educational tools, and user experience studies.

Ingrid Chieh Yuمشاهده پروفایل

دانشیار

• Data Management
• Knowledge Systems
• Software Product Lines
• +۷ مورد دیگر

Ingrid Chieh Yu is an Associate Professor in the Department of Informatics at the University of Oslo, where she also serves as Head of Research and Vice Head of Department (2021-2024) and Deputy Centre Director of SIRIUS. Her academic home is within the Data and Knowledge Management (DKM) research group, with additional affiliations to the Concurrent Security and Robustness for Networked Systems (ConSeRNS) initiative. Professor Yu's research spans multiple domains in computer science, with early work focused on formal methods, software product lines, and concurrent systems. In recent years, her research has expanded significantly into explainable AI, counterfactual explanations, and machine learning interpretability. She has made substantial contributions to feature model evolution, software configuration, and model checking techniques. Her work demonstrates a consistent thread of applying formal methods to practical software engineering challenges, with a notable pivot toward AI explainability in the past five years. Her publication record shows a clear evolution from foundational work in software engineering and formal methods (2006-2015) to increasingly AI-focused research (2016-present). The most recent publications (2020-2025) predominantly address explainable AI, counterfactual explanations, and robust recourse methods, reflecting her adaptation to emerging challenges in machine learning. She maintains strong collaborative relationships with researchers including Einar Broch Johnsen, Crystal Chang Din, and Peyman Rasouli. Professor Yu teaches core computer science courses including INF2220 Algorithms and Data Structures, INF3230 Formal Modeling and Analysis of Communicating Systems, and INF5130 Selected Topics in Rewriting Logic. Her teaching reflects her research expertise, bridging theoretical foundations with practical applications. She leads significant research projects including HyVar: Scalable Hybrid Variability for Distributed Evolving Software Systems and Leveraging Energy-Aware Programming (LEAP), demonstrating her capacity to secure and manage substantial research initiatives. Her work with the SIRIUS center indicates strong industry connections and applied research focus.

• Validation Intelligence
• Software Testing
• Software Validation and Verification
• +۴ مورد دیگر

Arnaud Gotlieb serves as a Research Professor and Chief Research Scientist at Simula Research Laboratory in Norway, where he heads the Department Validation Intelligence for Autonomous Software Systems. His academic career spans over two decades with significant contributions to software testing and artificial intelligence integration. Gotlieb's research focuses on Validation Intelligence of Autonomous Software Systems , Software Testing , Software Validation and Verification , and the application of Constraint Programming and Machine Learning to safety-critical systems. His innovative work bridges theoretical computer science with practical industrial applications, particularly in industrial robotics and autonomous systems. His publication record shows a consistent trajectory of high-impact research with approximately 15 recent publications (2024-2025) focused on metamorphic testing, constraint acquisition, explainable AI for autonomous driving, and verification of AI systems. The research demonstrates a clear evolution from foundational constraint programming work toward contemporary challenges in trustworthy AI and autonomous systems validation. Gotlieb has developed several influential tools including ITE (Stratified Disjunctive Reasoning), TITAN / FLOWER (Test suite optimization), EUCLIDE (constraint-based platform for critical C programs), and FPSE (Floating Point Symbolic Execution), which have advanced the field of automated software testing.