جست‌وجوی استاد و پژوهشگر

Agaraoli Aravazhiمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Healthcare Operations Management
• Predictive Analytics
• +۳ مورد دیگر

Agaraoli Aravazhi is a Scientific Staff member at the Logistics Department of Molde University College - Specialized University in Logistics, specializing in AI applications for healthcare and logistics systems. He holds a Bachelor of Technology in Mechanical Engineering from Amrita Vishwa Vidyapeetham University and a Master of Science in Engineering Logistics from Molde University College. Education : B.Tech (Mechanical Engineering), MSc (Engineering Logistics) Research Groups : Center for Healthcare Operations Management, ABC-AI (Applied, Basic, and Conscientious Artificial Intelligence), Digitization for Sustainability His research focuses on AI-driven hospital production processes , predictive analytics for healthcare operations , and logistics optimization . He has contributed to studies on patient treatment process monitoring, surgical case volume forecasting, and inventory management in hospitals. The scientific publications highlight his work in applying hybrid machine learning models to healthcare challenges, developing connectivity metrics for transportation systems, and exploring blockchain applications for health records. While no formal awards are listed, his research involves collaborations across multiple disciplines including medicine, logistics, and data science. Additional contributions include teaching SAP best practices for digital workforce preparation and text mining applications for extracting insights from hospital administrative documents. He is actively involved in the Center for Healthcare Operations Management, focusing on transforming clinical workflows through technology.

• Software Engineering
• Software Security
• Artificial Intelligence in Software Engineering
• +۲ مورد دیگر

Professor Jingyue Li is a Professor in the Department of Computer Science at the Norwegian University of Science and Technology (NTNU), Faculty of Information Technology and Electrical Engineering. She earned her Ph.D. in Software Engineering from NTNU in 2006 and maintains extensive industry experience from global corporations including IBM and DNV Research and Innovation. She currently serves on the EASE steering committee and holds the position of General Chair for FSE 2025. Her educational background includes: Ph.D. in Software Engineering from NTNU (2006) Professor Li's research spans empirical software engineering with core focus areas in software security, AI integration in software development, and blockchain technologies. Her methodological approach emphasizes design science to create innovative tools and frameworks, particularly for security-critical systems and decentralized applications. Recent projects demonstrate strong industry collaboration in supply chain management, smart city infrastructure, and healthcare technology. Analysis of her 2023-2025 publications reveals dominant themes in blockchain governance (40%), security vulnerability detection/repair (35%), and AI-enhanced software engineering (25%). Key trends include empirical studies of Bitcoin consensus evolution, development of decision support systems for blockchain design patterns, and novel techniques for detecting unexploited smart contract vulnerabilities. Her work consistently bridges theoretical advances with practical industrial applications. Professor Li actively contributes to the research community through leadership roles including General Chair for FSE 2025 and EASE steering committee membership. Her grant portfolio features significant projects such as PaaSforChain (2020-2023, PI), CyberSmart (2017-2020, PI), and TRACE4EU (2023-2025, Key Scientist), demonstrating sustained funding success across blockchain, security, and AI domains. International collaborations include research visits to University College London, University of Washington, Hiroshima University, and Peking University. Her research is conducted within NTNU's Department of Computer Science, where she integrates cutting-edge industry experience with academic rigor to advance software engineering practices in security-critical and blockchain-based systems.

• Cybersecurity
• Digital Forensics
• Machine Learning
• +۳ مورد دیگر

Carl Stuart Leichter is an Adjunct Associate Professor at the Department of Computer Science , Norwegian University of Science and Technology (NTNU). With over 40 years of experience in science and technology, his career spans biomedical research, nuclear security, mathematics teaching, and machine learning applications. Current roles: Teaching Data Science for Security and Forensics at NTNU Active research: Cyber threat intelligence, digital forensics, and machine learning Leadership: Conducts seminars for Master's candidates in scientific research Research Focus: Professor Leichter's work bridges cybersecurity and data science, particularly in extracting intelligence from hacker forums using machine learning techniques. His recent publications highlight applications of Support Vector Machines, neural networks, and hybrid analytical frameworks. Outreach & Collaboration: Engaged in international cyber capacity development through INTERPOL's ASEAN project and the Research School of Computer and Information Security (COINS) Winter School.

• Artificial Intelligence
• Machine Learning
• Human-Computer Interaction
• +۵ مورد دیگر

Raju Shrestha is an Associate Professor at the Department of Information Technology , Faculty of Technology, Art and Design , Oslo Metropolitan University. His work spans artificial intelligence, human-computer interaction, and cloud computing. Recent research includes: Hybrid deep learning models for plant disease detection AI-based navigation assistants for visually impaired users Cloud infrastructure optimization via GitOps and CI/CD pipelines Analysis of voice assistant efficacy in education Computer vision applications in election ballot processing His publications (2023-2025) reflect interdisciplinary applications of AI in agriculture, healthcare, education, and social media marketing automation.

Rudolf Schlatteمشاهده پروفایل

پژوهشگر

• Formal Methods
• Computer Science
• Programming Language Semantics
• +۵ مورد دیگر

Rudolf Schlatte is a Researcher at the Department of Informatics, University of Oslo, affiliated with the Reliable Systems group. He holds a PhD from Graz University of Technology and has extensive experience in formal methods and software systems modeling. His work focuses on concurrent and distributed systems, formal languages, and digital twins. Education and Employment: Master’s degree from Graz University of Technology PhD (2010) at Graz University of Technology Postdoc researcher at Oslo University (2010-2011) Senior Engineer at the University of Oslo since 2011 Research Interests: Schlatte specializes in formal languages for distributed systems, digital twins, concurrency, and resource-aware modeling. His current focus includes correctness in self-adaptive systems and semantic reflection in digital twins. He actively contributes to the ABS modeling language and toolchain. Teaching: He teaches INF2220 (Algorithms and Data Structures) and INF3230 (Formal Modeling and Analysis of Communicating Systems). Publications: Over 40 peer-reviewed articles, primarily in formal methods, distributed systems, and digital twin applications. Recent work emphasizes digital twin reconfiguration, user journey simulation, and pandemic modeling. Lab/Team: Member of the Reliable Systems team, collaborating on projects like BedreFlyt (digital twin for healthcare resource planning) and NebulOuS (cloud computing).

Marieke Kuijjerمشاهده پروفایل

پژوهشگر

• Gene Regulatory Networks
• Cancer Genomics
• Bioinformatics
• +۴ مورد دیگر

Marieke Kuijjer is a Group Leader at the Norwegian Centre for Molecular Bioscience and Medicine, University of Oslo, leading the Computational Biology and Systems Medicine Group. Her academic focus spans gene regulatory networks, cancer genomics, bioinformatics, and systems medicine. She holds a PhD from Leiden University Medical Center (2013) and postdoctoral experience at Harvard and Dana-Farber Cancer Institute (2013–2018). Her research integrates multi-omics data to predict cancer outcomes and develops computational tools for gene network analysis. Key awards include the Charles A. King Postdoctoral Fellowship and National Cancer Institute grants. She has authored over 50 peer-reviewed articles, emphasizing tumor microenvironment dynamics, sarcoma genomics, and machine learning in immunology. Her work bridges computational methods with clinical applications, such as creating digital twins for cancer patients and improving bioinformatics software quality through collaboration. Current initiatives include studying osteosarcoma progression through longitudinal genomic analysis and leveraging single-cell transcriptomics for population-level gene regulatory insights. She collaborates internationally, including in the Fight Osteosarcoma and Euro Ewing consortia, advancing sample collection standards for rare cancers.

Kjell Ivar Øvergårdمشاهده پروفایل

استاد

• Work and Organizational Psychology
• Human-Technology Interaction
• Transportation Safety
• +۷ مورد دیگر

Professor Kjell Ivar Øvergård is a Full Professor at the University of South-Eastern Norway (USN), leading the Research Group for Health Promotion in Settings within the Department of Health, Social, and Welfare Studies. His academic roles include course responsibility for Philosophy of Science and Research Methods (MSH-VET4100), lecturing on work and organizational psychology in MSH-VAA4300 and MSH-OPP4400, and supervising master’s and PhD candidates. He also serves as Chief Scientific Officer at EBHR AS, focusing on algorithmic HR software development. Education: PhD in Psychology (Cognitive Systems Engineering) from NTNU (2008), Cand.Polit in Psychology (Ergonomics and Human Factors) from NTNU (2004), and Cand.mag from Akershus College (2001). Research Interests: Cross-disciplinary studies in work environment impacts on health/turnover, human-technology interaction, transportation safety, workplace well-being, and applied statistics. Key areas include maritime human factors, decision-making under pressure, and automation trust modeling. Notable Contributions: 2012 gift professorship from Kongsberg Maritime (4 MNOK over 5 years), leadership roles in national/international research initiatives, and 6 program accreditations in Georgia/Croatia. Language proficiency includes C2+ Norwegian, C1 English, B2 German, and A2 Croatian. Advancing interdisciplinary research through collaboration with universities, industry partners, and public sectors. Focus on actionable insights for workplace safety, organizational health, and technological adaptation in complex systems.

Shegaw Anagaw Mengisteمشاهده پروفایل

استاد

• Digital Health Systems
• IT Governance and Management
• AI and Machine Learning
• +۵ مورد دیگر

Shegaw Anagaw Mengiste is a Professor of Informatics at the University of South-East Norway (USN), affiliated with the Department of Business, History and Social Sciences within the USN School of Business. His research focuses on Digital Health Systems, AI/Machine Learning, and IT Governance in public sector organizations. He holds a PhD in Information Systems from the University of Oslo (2005–2008) and has extensive academic experience across institutions in Norway, Denmark, and Ethiopia. Education: PhD in Information Systems, University of Oslo, Norway (2005–2008) M.Sc. in Information Science, Addis Ababa University, Ethiopia (2000–2002) B.Sc. in Information Science, Addis Ababa University, Ethiopia (1996–1998) Research Interests: IS/IT innovation, digital health policy, AI-driven healthcare solutions, and governance of enterprise systems. His work emphasizes interdisciplinary approaches, with a focus on low-resource settings and public sector digitalization. Projects: Coordinated initiatives like the SEARCH (eHealth capacity building) and NURTURE (global health informatics) projects. Partnered on EU-funded BETTEReHEALTH for sustainable health systems. Teaching: Courses in Database Systems, Enterprise Architecture (TOGAF), IT Governance, and Agile Methods (Scrum). Proficient in tools like SAP, Microsoft Dynamics, and Business Intelligence platforms.

Eyvind Wærsted Axelsenمشاهده پروفایل

دانشیار

• Programming Languages
• Generics
• Generative Programming
• +۳ مورد دیگر

Eyvind Wærsted Axelsen is an Associate Professor at the University of Oslo's Department of Informatics and serves as Chief Technological Officer at Fürst Medisinsk Laboratorium. His research focuses on programming language design, software engineering methodologies, and medical informatics. His core research interests include programming languages, generics, generative programming, domain-specific languages, and the comparative analysis of dynamic vs. static typed languages. This work bridges computational theory with practical applications in medical technology and healthcare systems. Axelsen's recent publications demonstrate interdisciplinary collaboration, with research spanning COVID-19 laboratory protocols, machine learning in clinical diagnostics, and programming language design. His work frequently intersects medical science and computational innovation. He teaches courses in Programming Languages (IN3040/INF3110), Object-Oriented Programming (IN1010), and Introduction to Computer Technology (IN1020). Axelsen contributes to the Programming Technology (PT) research group and maintains collaborative medical research partnerships focusing on laboratory efficiency and diagnostic technology enhancement.

Andrea Pferscherمشاهده پروفایل

مدرس ارشد

• Digital Twins
• Formal Methods
• Computer Science
• +۳ مورد دیگر

Andrea Pferscher is a Senior Lecturer at the University of Oslo's Department of Informatics. Her research focuses on formal methods applied to digital twins, particularly in contexts like vaccination strategy modeling and environmental systems analysis. She is involved in projects such as DART (Digital Arctic Twins), a digital twin for vaccination strategies at geographic scales, and a digital twin of the Oslo Fjord. Her work bridges theoretical computer science with practical applications in system modeling and analysis. She collaborates on stochastic games, user journey strategies, and automated learning techniques for cyber-physical systems. Pferscher's research emphasizes interdisciplinary approaches, combining formal verification with machine learning and systems engineering.

Lars Tveitoمشاهده پروفایل

مدرس

• Formal Methods
• Software Engineering
• Distributed Systems
• +۳ مورد دیگر

Lars Tveito is a Lecturer in Programming Technology at the Department of Informatics, University of Oslo. His research focuses on formal methods, distributed systems, and concurrency theory, with contributions to tools like OnlineProver for teaching formal proofs. He is affiliated with the Programming Technology research group and has published widely in venues such as NIKT, OpenAccess Series in Informatics, and Lecture Notes in Computer Science. Key research interests include partial order reduction techniques, formal verification of distributed systems, and virtualized system analysis. Recent work explores reproducibility in distributed active objects and symbolic execution combined with concurrency analysis. His teaching emphasizes practical applications of formal logic and software engineering principles. Collaborations with researchers like Einar Broch Johnsen and Rudolf Schlatte highlight his involvement in advancing methodologies for system design and verification. The lack of explicit awards indicates a focus on impactful technical contributions over accolades.

Jefferson Mollériمشاهده پروفایل

دانشیار

• Software Engineering
• Computer Science
• Empirical Research Methods
• +۱۰ مورد دیگر

Jefferson Molléri is an Associate Professor at Kristiania University College's School of Economics, Innovation and Technology. He specializes in evidence-based software engineering and empirical research methods, focusing on software process improvement, AI applications in software engineering, and human factors in technology development. PhD in Software Engineering (Blekinge Institute of Technology, 2019) Postdoctoral research at Simula Metropolitan Centre for Digital Engineering Academic experience since 2014 His research emphasizes methodological rigor, ethical considerations, and participatory approaches in software engineering. He has developed empirical standards and checklists for survey research validation. Recent publications focus on DataOps integration, hybrid workplace transformations, and research quality frameworks. Jefferson teaches software engineering, information technology, and computer science courses. He advocates for critical appraisal of scientific literature and has extensive experience supervising students across undergraduate, graduate, and doctoral programs.

Øystein Haugenمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Modeling Languages
• Software Engineering
• +۷ مورد دیگر

Øystein Haugen is a Professor at the Department of Computer Science and Communication at Høgskolen i Østfold (HiØF), Norway. He specializes in Cyber-Physical Systems (CPS), Modeling Languages (e.g., UML/SysML), and Software Engineering. His work focuses on standardization efforts for modeling languages (ITU/OMG), variability modeling, and real-time systems. Haugen has led EU projects like Productive4.0 and Arrowhead Tools, emphasizing Industrial IoT and digital twin technologies. He co-chaired MODELS 2010 and currently contributes to SysML v2 development. Collaborations include SINTEF Digital, University of Oslo, and Luleå Technical University. Research Interests : Cyber-Physical Systems & IoT Model-Driven Engineering Software Product Line Engineering Formal Methods in Systems Design Standardization of Modeling Languages (SDL/MSC/UML/SysML) Industrial Applications of CPS (Manufacturing, Automation) Recent Article Trends : His 2020-2024 work emphasizes CPS applications, digital twin evolution, industrial IoT interoperability, and imitation learning in manufacturing automation. Key areas include model-based debugging, energy-efficient IoT networks, and autonomic service orchestration in industrial systems. Grants/Projects : Led EU ECSEL projects Productive4.0 (smart manufacturing) and Arrowhead Tools (IoT middleware). Active in standardization through OMG committees and ITU. Recent contributions include WP leadership in EU Horizon projects focusing on industrial digitalization. Labs/Teams : Leads the CPS Research Group at HiØF. Involved in the Arrowhead Tools consortium and Productive4.0 industrial partnerships (Jotne, Prediktor, Unger Fabrikker).

Alireza Khakpourمشاهده پروفایل

دانشیار

• Visual Analytics
• Information Systems
• Explainable AI
• +۳ مورد دیگر

Alireza Khakpour is an Associate Professor at the Department of Computer Science and Communication at Østfold University College. He holds a PhD in Computer Science from the University of Oslo (2024), focusing on Visual Analytics Modeling for Decision-Support Systems. His academic journey includes bachelor's (MSRIT, 2013) and master's degrees in Software Engineering (Azad University, 2018) and Applied Computer Science (Østfold University College, 2020). His research interests span Visual Analytics, Information Systems, Explainable AI, and Machine Learning, with a focus on applying these fields to supply chain optimization and decision support. He contributes to the DigiMat project, aiming to enhance Norway's food supply chain through smart, sustainable technologies. He teaches courses such as Big Data Processing, Business Intelligence, and interdisciplinary projects, supervising both bachelor's and master's theses. His publications emphasize frameworks for Visual Analytics, supply chain analytics, and systematic reviews on topics like Domain-Specific Languages and Gamification-Machine Learning synergies. His work bridges theoretical models with practical applications in logistics, data science, and decision-making systems. Khakpour's academic contributions include developing ModelViz, a Model-Driven Engineering tool for Visual Analytics, and exploring greenable technologies in reality systems. His research aligns with real-world challenges such as sustainable supply chains and data-driven decision support in production and retail sectors.

Mary Luz Sanchez Gordonمشاهده پروفایل

دانشیار

• Human Factors in Software Projects
• Software Project Management
• Software Process Improvement
• +۴ مورد دیگر

Mary Luz Sánchez-Gordón is an Associate Professor at the Department of Computer Science and Communication at Østfold University College. Formerly affiliated with Universidad Central del Ecuador, her research focuses on human factors in software projects, software process improvement, and cybersecurity governance. She holds a Ph.D. from Universidad Carlos III de Madrid and has extensive industry experience as a software engineer and consultant. Research Interests: Her work addresses intersectional perspectives in software engineering, diversity/inclusion in tech, DevOps/DevSecOps practices, and accessibility in virtual education. Recent studies explore stereotypes affecting indigenous software practitioners and blockchain applications in traceability systems. Publications: Over 30 peer-reviewed articles since 2018, focusing on topics like cybersecurity frameworks for critical infrastructures, software process improvement, and human-centric software engineering. Her 2025 studies on professional photo stereotypes and gender equity in tech received notable attention. Projects: Leads EU/Norway partnerships like EduTech (accessibility in virtual education) and RECYCIN (critical infrastructure cybersecurity). Active in EnCyCriS workshops on cybersecurity challenges. Affiliations: Member of the Information Systems and Software Engineering research group. Teaches courses on cybersecurity governance, software architecture, and design patterns at both Norwegian and Ecuadorian institutions.