جستجوی استاد راهنمای دانشگاهی

Leif Rune Hellevik is a Professor of Biomechanics at the Department of Structural Engineering, Faculty of Engineering at NTNU. He also serves as Vice Dean for Master Programs since 2017. His research focuses on computational biomechanics, particularly in cardiovascular systems, emphasizing uncertainty quantification and sensitivity analysis. Key projects include STARFiSh (Stochastic Arterial Flow Simulations) and MyMDT (Medical Digital Twin for hypertension management). He has extensive experience in fluid-structure interaction and numerical methods, contributing to clinical decision support systems and translational hypertension research. His teaching includes courses on numerical methods and biomechanics. Research Interests: His work spans biomechanical modeling of arterial systems, cardiovascular hemodynamics, and translational applications of computational models for personalized medicine. Recent efforts integrate machine learning and digital twins to improve hypertension treatment and prevention. Publications: Over 30 peer-reviewed articles since 2000, with recent focus on sensitivity analysis, model validation, and clinical applications in coronary artery disease. Collaborations include institutions like Linköping University, University of British Columbia, and Erasmus MC. Labs/Teams: Leads projects in computational biomechanics and vascular modeling, collaborating with multidisciplinary teams in engineering, medicine, and data science.

• Biomechanics
• Cardiovascular System Modeling
• Uncertainty Quantification
• +۵ مورد دیگر

David Palma is an Associate Professor at the Department of Information Security and Communication Technology , Faculty of Information Technology and Electrical Engineering , Norwegian University of Science and Technology (NTNU). His research focuses on next-generation networking paradigms, including intent-based networking , knowledge-driven management , and IoT device automation . Key research interests include: Human-centric Internet of Things (IoT) Ontology-based network management Cloud/Edge/Fog computing for IoT Arctic and satellite communication 5G integration in smart grids His recent publications (2024-2019) highlight trends in knowledge graphs for network compliance, XR applications in critical sectors, UAV-based emergency networks , and 5G-enabled smart grid protection . Articles also explore Arctic connectivity via satellite swarms and energy-efficient IoT management.

• Next Generation Internet
• Human-centric Networking
• Ontology and Knowledge-based Management
• +۱۳ مورد دیگر

Tor-Morten Grønli serves as Professor at the Department of Technology, School of Economics, Innovation and Technology, Kristiania University College (Norway). He is also a Visiting Research Scholar at Copenhagen Business School's Department of Information Technology Management and an affiliate of the Center of Business Data Analytics (cbsDBA). Education PhD in Computer Science from Brunel University, London (2011) Master of Technology (with distinction) from Brunel University, London (2007) Research Focus Grønli leads research in context-aware systems, mobile/pervasive computing, and Internet of Things (IoT). He founded/directs the Mobile Technology Lab at Kristiania and has co-authored 70+ publications. Core expertise includes: IoT architecture and applications Machine learning for transport systems Mobile computing frameworks Blockchain-security integration Edge-cloud computing paradigms Publication Trends Recent works (2023-2025) demonstrate strong focus on converging IoT, blockchain, and AI technologies, particularly for intelligent transport and healthcare systems. Dominant themes include federated learning implementations, privacy-preserving architectures, and sustainable edge computing solutions, with increasing emphasis on real-world applications in medical diagnostics and public infrastructure. Professional Activities Founder/Director of Mobile Technology Lab General Chair: Norwegian Conference on ICT Co-organizer: International Conference on Mobile Web Editorial Board: International Journal of Pervasive Computing, Journal of Online Information Review, Computers & Electrical Engineering TPC Member for IEEE BigData, Percom, HICSS, COMPSAC Guest Editor for special issues in Future Generation Computer Systems

• Internet of Things (IoT)
• Software Architecture
• Machine Learning
• +۴ مورد دیگر

Amir Taherkordi is a Professor in the Networks and Distributed Systems group at the Department of Informatics, University of Oslo, Norway. His research focuses on resource-efficiency, scalability, adaptability, and mobility in distributed systems for emerging technologies like IoT, Fog/Edge/Cloud Computing, and Cyber-Physical Systems (CPS). University: University of Oslo Department: Informatics Academic Rank: Professor His research spans IoT, Edge/Fog Computing, and Cyber-Physical Systems, emphasizing energy efficiency, privacy preservation, and self-adaptive architectures. Key areas include network traffic classification, computation offloading, and federated learning applications in vehicular systems. Recent publications highlight advances in latency-aware IoT data transmission , federated vehicular networks , energy-efficient wireless charging , and privacy-preserving data integration . These works often integrate machine learning with network optimization. Projects include the CPS Lab at UiO, DILUTE (Fluid Service Abstraction), and the Gemini Centre on IoT . He collaborates on initiatives like PACE for energy informatics curricula development.

• Internet of Things (IoT)
• Fog Computing
• Edge Computing
• +۱۶ مورد دیگر

Martin Marie Hubert Choux is an Associate Professor at the Department of Engineering Sciences , University of Agder, Norway. He holds dual M.Sc. degrees in Mechatronic Engineering from École Nationale Supérieure d'Art et Métiers (France) and University of Queensland (Australia), and a Ph.D. in Automatic Control from Technical University of Denmark (2011). Education: M.Sc. in Mechatronic Engineering, École Nationale Supérieure d'Art et Métiers, Paris, 2006 M.Sc. in Mechatronic Engineering, University of Queensland, Brisbane, 2006 Ph.D. in Automatic Control, Technical University of Denmark, Copenhagen, 2011 His research focuses on mechatronics , robotics , and battery recycling , with over 15 recent publications (2024–2019) on: Automated Disassembly of lithium-ion batteries Fault Diagnosis in motor drives using structural analysis and neural networks Efficiency Optimization of electric drivetrains in offshore applications Comparative Studies of hydraulic vs. electric actuation systems AI and Robotics for EV battery recycling Control Algorithms for mechanical systems His work spans robotics , automatic control , and sustainable engineering , contributing to electric vehicle and offshore technology advancements.

• Mechatronics
• Robotics
• Automatic Control
• +۴ مورد دیگر

Nils-Ole Stutzer is a Doctoral Research Fellow at the Institute of Theoretical Astrophysics , University of Oslo, specializing in Cosmology , Line Intensity Mapping , and Cosmic Microwave Background (CMB) data analysis. He contributes to major projects like COMAP COSMOGLOBE BeyondPlanck and develops computational tools in Python/C++ for mitigating systematic errors in radio telescope data. His research interests focus on Galactic and extragalactic CMB analysis Radio interferometry for molecular gas mapping Bayesian methods in cosmological parameter estimation Instrumental signal deconvolution Open science data frameworks His work addresses fundamental questions about cosmic structure formation and early universe physics. Key publication trends include: 2024 studies on 30GHz spinning dust emission in dark clouds Advanced CO power spectrum constraints at z ∼ 3 2023-2024 Bayesian reanalysis of Planck/WMAP missions LiteBIRD mission forecasts for gravitational waves Projects emphasize reproducibility and end-to-end data modeling. He teaches AST2000 project groups and collaborates across institutions on CMB&CO initiatives. Current affiliations include the Faculty of Mathematics and Natural Sciences at the University of Oslo.

• Astronomy
• Cosmology
• Line Intensity Mapping
• +۲ مورد دیگر

Per Lauvås is an Associate Professor at the Department of Computer Science, Faculty of Technology, Art and Design, Oslo Metropolitan University. His research and teaching focus on IT education, software engineering, and e-learning technologies. Key research areas include Software testing pedagogy Gamification in data modeling education Interactive web development tools Cloud computing and cybersecurity Assessment innovations in database courses Work-integrated learning for IT students Recent publications explore AI chatbots in education, employer prioritization of IT graduates, and gamified learning tools. His work emphasizes student-centered approaches and practical skill development. Contact: pelau8806@oslomet.no

• Cloud Computing
• Cybersecurity
• Software Engineering
• +۶ مورد دیگر

Bruno Dzogovic is an Assistant Professor at Oslo Metropolitan University's Faculty of Technology, Art and Design, specifically within the Department of Computer Science. His research focuses on 5G/6G networks, cybersecurity, cloud computing, and software engineering. 5G/6G mobile networks Cloud computing and virtualization Cyber defense systems Wireless communication Industrial networks Biomedical Wireless Sensor Networks His recent work explores secure network slicing, container technologies, and applications of 5G in healthcare and elderly care systems. He is an active member of the Autonomous Systems and Networks (ASN) research group, contributing to advancements in digital forensics and vulnerability assessment for modern communication systems.

• 5G/6G mobile networks
• Radio access networks
• Automation systems and autonomy
• +۱۹ مورد دیگر

Stephen Dirk Bjørn Wolthusen is a Professor at the Norwegian University of Science and Technology (NTNU) in the Department of Information Security and Communication Technology. He is based in Gjøvik, Norway, and his work focuses on cybersecurity, critical infrastructure protection, and cyber-physical systems. His research spans network topology, smart grids, formal methods, and privacy in IoT systems, with a particular emphasis on security vulnerabilities and resilience in resource-constrained environments. His recent publications address hierarchical information overlays, adversarial pathways in smart grids, and formal methods for securing cyber-physical systems. His work frequently appears in journals and conferences such as IFIP Advances in Information and Communication Technology , Lecture Notes in Computer Science (LNCS) , and IEEE conference proceedings . Topics include adversary models, queueing networks, access control, and policy enforcement in tactical and industrial contexts.

• Cybersecurity
• Critical Infrastructure Protection
• Cyber-Physical Systems
• +۴ مورد دیگر

Puneet Sharma is an Associate Professor at the Department of Automation and Process Technology, UiT The Arctic University of Norway. His primary research areas include computer vision, image analysis, machine learning, and wearables technology, with active contributions to atmospheric science data processing and maritime navigation AI applications. Current role: Associate Professor (Automation) Teaching: Industrial data communication (bachelor), Machine Vision (master) Research: Machine Learning Group member, focus on visual attention models, deep learning for PMSE segmentation, and wearable training systems Recent publications highlight his work in applying machine learning to Polar Mesospheric Summer Echoes (PMSE) analysis, noctilucent cloud classification, and biosignal-based maritime navigation studies. He participated in the Horizon 2020 WEKIT project for wearable-based industrial training.

• Computer Vision
• Image Analysis
• Machine Learning
• +۱ مورد دیگر

Haakon Bryhni is a Research Professor at Simula Research Laboratory's Center for Resilient Networks and Applications, focusing on telecommunications infrastructure and network resilience. His work spans optical fiber sensing, Cloud-RAN architecture, 5G networks, and network security. Expertise in telecommunications and network infrastructure Contributions to optical fiber sensing and AI-driven network outage classification Active in public outreach and policy analysis for ICT resilience Recent research explores Sagnac loop sensing systems , Cloud-RAN integration , and cybersecurity preparedness in Norway. Collaborations include international conferences and publications in Optics & Laser Technology , Sensors , and IEEE journals. Contact: haakonbryhni@simula.no

• Telecommunications
• Network Resilience
• Optical Fiber Sensing
• +۵ مورد دیگر

Edmund Førland Brekke is a Professor at the Department of Technical Cybernetics, Norwegian University of Science and Technology (NTNU). He leads the Autosit and Autosight projects, and serves as a work package leader in the SFI Autoship center. His research focuses on target tracking, navigation, and SLAM, with applications in collision avoidance for unmanned vessels. He co-founded the company Zeabuz for marine surface autonomy solutions. PhD in Technical Cybernetics (NTNU, 2010) MSc in Industrial Mathematics (NTNU, 2005) Research Interests: Edmund specializes in theoretical foundations of multitarget tracking, integrating target tracking with navigation/SLAM, and applying these to autonomous maritime collision avoidance. His work addresses challenges in heavy-tailed clutter, sensor fusion, and situational awareness for autonomous ferries and river barges. Publications Trends: His recent work (2018–2022) emphasizes collision avoidance algorithms, sensor fusion, and SLAM for autonomous vessels. Key areas include maritime radar tracking, trajectory prediction using AIS data, and integration of visual/Lidar sensors for navigation. Guidance: He has supervised numerous PhD candidates on topics like digital twins, multi-sensor tracking, and risk assessment for autonomous ships, including graduates from 2014–2024. Projects: Active in Autoferry (autonomous ferries), Autobarge (river barges), and the ORCAS initiative. Collaborates with the SFI Autoship center.

• Target Tracking
• Navigation
• SLAM
• +۴ مورد دیگر

Eric Bartley Jul is a Professor in the Department of Informatics at the University of Oslo, specializing in Programming Technology within the Faculty of Mathematics and Natural Sciences. His research spans multiple domains of computer science with a focus on practical applications in medical imaging, distributed systems, and mobile computing. Professor Jul's research interests encompass a broad spectrum of computer science disciplines. His expertise lies particularly in Object-Oriented Programming, Distributed Computing, and Design Patterns, with expanding work in Cloud Computing and Security. His recent publications demonstrate a significant shift toward applying computer vision and deep learning techniques to medical diagnostics and healthcare applications, particularly in microcirculation analysis and reproductive medicine. This interdisciplinary approach bridges traditional computer science with cutting-edge medical research. His recent publication record shows a strong trend toward medical applications of computer vision and mobile sensor technologies. The 2024 papers reveal sophisticated applications of AI in reproductive medicine (sperm detection) and transportation monitoring (flight detection), while the 2022 publications establish his foundational work in medical imaging systems like CapillaryNet for blood flow analysis. This trajectory demonstrates a consistent focus on applying programming technology to solve complex real-world problems, particularly at the intersection of computing and healthcare. Professor Jul leads research within the Programming Technology group at the University of Oslo and is involved in several significant projects including A Modern Approach to Teaching Classes at the University Level in Theoretical Computer Science , Leveraging Energy-Aware Programming (LEAP) , and Reliable models of computation for concurrent and distributed problems . His work demonstrates strong collaborative efforts with researchers across multiple institutions, particularly with Paulo Ferreira and other colleagues at the University of Oslo.

• Programming
• Object Oriented Programming
• Distributed Computing
• +۴ مورد دیگر

Tobias Mahler is a Professor of Law at the University of Oslo's Department of Private Law and serves as deputy director of the Center for Legal Informatics. He leads the legal innovation lab LILO and has been a visiting scholar at prestigious institutions including Stanford Law School and the Max Planck Institute for Foreign and International Criminal Law in Freiburg, Germany. Originally trained as a German lawyer, Mahler has practical experience having previously practiced as a paralegal in Norway. Professor Mahler's research spans the intersection of law and emerging technologies, with particular expertise in artificial intelligence regulation, robotics law, cybersecurity, and digital governance. His work focuses on developing legal frameworks that balance innovation with risk management and proportionality. He has published extensively on the EU AI Act, examining its risk-based approach and implementation challenges across various technological domains. His research also addresses the legal implications of healthcare robotics, cloud computing services, and domain name systems in the evolving digital landscape. Analysis of Mahler's recent publications reveals a strong focus on the regulatory challenges posed by artificial intelligence, particularly the EU's regulatory framework. His work examines both high-risk and non-high-risk AI systems, exploring compliance procedures, national implementation strategies, and the relationship between risk management and legal proportionality. He has made significant contributions to understanding how legal frameworks should address specific applications like medical AI, care robotics, and smart robotics within the EU context. His research consistently bridges technical and legal perspectives, emphasizing the need for adaptable regulatory approaches that can keep pace with technological innovation. Professor Mahler holds several important positions that demonstrate his influence in the field. He serves as a member of the Research Council's advisory expert group for the KI initiative (2023), is a board member of the Norwegian Association for Law and EDB, and participates in Standard Norway's committee on Artificial Intelligence (SN/K 586). He has led significant studies for both the Research Council of Norway on research data sharing and for the EU Commission related to the Digital Services Act. Previously, he served as program manager for the LLM in Information and Communication Technology Law. At the University of Oslo, Mahler is actively involved in research groups focused on Law and Technology (JOT) and Market, Innovation and Competition (MIK). He leads the legal innovation lab LILO and contributes to projects including Societal Security and Digital Identities (SODI) and Vulnerability in a Robot Society (VIROS), which examine the legal and societal implications of emerging technologies in security contexts and robotics.

• Artificial Intelligence Law
• Robotics Regulation
• Cybersecurity Law
• +۵ مورد دیگر

Tomasz Wiktorski is a Professor at the Faculty of Science and Technology , University of Stavanger , where he serves as Study Program Manager for MSc and PhD programs in Computer Science and Data Science. His research integrates conventional time series analysis with deep learning for applications in biomedical data (e.g., wearable devices), oil and gas drilling automation, energy systems prediction, and cloud infrastructure optimization. Education : Not explicitly detailed in the text. Research interests span data-intensive system modeling, focusing on: Biomedical time series analysis (wearables, ECG signal correction) Drilling process optimization via transfer learning and temporal models Energy systems prediction using machine learning Cloud infrastructure monitoring Curriculum development in data science education Scientific trends reveal expertise in recurrent neural networks, support vector machines, and hybrid data modeling for sensor networks across domains like health, petroleum, and cloud computing. Leadership includes designing data science programs and contributing to the EDISON Data Science Framework for global standards.

• Time Series Analysis
• Deep Learning
• Data-Intensive Systems
• +۶ مورد دیگر