جستجوی استاد راهنمای دانشگاهی

Karl-Heinz Frank Reichertمشاهده پروفایل

استاد

• Mobile Communication Systems
• E-Learning and Education Technology
• Telehealth and IoT Applications
• +۴ مورد دیگر

Frank Reichert is a Professor of Mobile Systems at the University of Agder (UiA), affiliated with the Department of Information and Communication Technology under the Faculty of Engineering & Science. He served as UiA's Rector (2016-2019) and Dean of Engineering & Science (2007-2015). With over 30 years in fixed/wireless communication systems, he has led national initiatives like the SFI Offshore Mechatronics Center (200 MNOK budget) and established UiA's Mechatronics Innovation Lab. His industry experience includes roles at Ericsson (1995-2005) and founding Ericsson Cyberlab Singapore (1999). Education : PhD in Electrical Engineering from RWTH Aachen University (Germany). Early career included research at the Royal Institute of Technology (Sweden) and Televerket Radio (Sweden). Research Interests : Focus on mobile communication, e-learning innovation, IoT-driven telehealth, and lifelong learning. His work bridges academia and industry, emphasizing user-centric design, rapid prototyping, and future education technologies. Projects include multi-touch collaborative learning systems, AI-assisted educational tools, and digital health twin architectures. Grants & Leadership : Managed EU projects (e.g., FP4-ACTS OnTheMove, PRO-COM) and served on steering boards for Norwegian and EU research bodies. Current roles include advisor to UiA's strategic initiatives and contributor to national bullying/harassment prevention (UHRMOT). Labs & Teams : Co-founded the Mechatronics Innovation Lab, leading projects in VR rehabilitation solutions and smart healthcare systems. Active in research groups like Multimedia and e-Learning, and ReSex (Research in Sexology).

• Cyber-Physical Systems
• Real-Time Systems
• Distributed Systems
• +۴ مورد دیگر

Geir Mathisen serves as a Professor within the Department of Technical Cybernetics, Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). He is an active member of the Group for Industrial Computer and Instrumentation Systems, focusing on real-time systems integration and cyber-physical applications across industrial and energy domains. His educational background includes a Civil Engineering degree and a Doctorate (PhD), both earned from NTNU's Department of Technical Cybernetics, establishing foundational expertise in control systems and technical cybernetics. Professor Mathisen's research spans cyber-physical systems, deterministic networking, and distributed real-time systems with significant applications in smart grids and industrial automation. His work pioneers magnetic field energy harvesting for railway systems, edge-based fault detection for photovoltaic panels, and multi-robot coordination in sewing automation. Current investigations focus on power system state estimation, optimal power flow in smart grids, and deterministic communication channels for latency-sensitive applications. Analysis of his 2020-2024 publications reveals a strategic convergence of real-time computing with energy systems, particularly in railway energy harvesting and photovoltaic monitoring. His research consistently bridges theoretical advances in networking protocols with practical industrial implementations, emphasizing determinism and composability in distributed cyber-physical environments. Scientific Awards: No specific awards or fellowships were documented in the provided materials. Professor Mathisen actively supervises doctoral and master's students, including Johannes Schrimpf (2013 PhD thesis on industrial robot control), and offers project assignments as noted for fall 2021. His research is conducted through Norwegian collaborative projects on flexible distribution grids and smart grid services, though specific grant mechanisms remain unspecified in the source material. He contributes significantly to the Group for Industrial Computer and Instrumentation Systems at NTNU, which develops advanced solutions for industrial control, measurement systems, and cyber-physical integration, particularly in energy and manufacturing contexts.

• Empirical Software Engineering
• Software Quality
• Requirement Engineering
• +۵ مورد دیگر

Deepti Mishra is a Professor in the Department of Computer Science at NTNU, Faculty of Information Technology and Electrical Engineering. She leads the Intelligent Systems and Analytics Research Group and the Educational Technology Laboratory. Formerly, she held positions as Associate Professor at Monash University, Malaysia, and Assistant Professor at Atilim University, Turkey. Research Interests : Focuses on Empirical Software Engineering, Human-Robot Interaction, Sustainability, and Educational Technology. Her work explores applications in healthcare robotics, AI-driven human action recognition, and software quality assurance. Key Projects : WP Lead for Collaborative Research-Based Education for Optimized Performance of Wind Farms (RCN-funded, 2022-2027) Co-lead of Mitigating Marine Plastic Pollution (NTNU Sustainability, 2022-2025) Global Collaboration on Wind Farm Efficiency (DIKU-funded, 2022-2026) Labs & Teams : Head of Educational Technology Laboratory Member of NTNU’s Team Active Aging Contributor to Excited Centre (IT Education Excellence) Publications : Over 50 peer-reviewed articles since 2013, with recent focus on human-robot interaction, edge computing, and sustainable software ecosystems. Most cited works include frameworks for software vendor selection and empirical studies on programming skills enhancement.

Andrii Shalaginovمشاهده پروفایل

استاد

• Internet of things (IoT)
• Machine learning
• Smart cities
• +۴ مورد دیگر

Andrii Shalaginov is a Professor in Cyber Security at Kristiania University of Applied Sciences, School of Economics, Innovation and Technology. He leads the Smart Security Lab with a research focus on applying artificial intelligence for cybersecurity, detection of computer viruses, network attacks and protection of Internet of Things devices. Dr. Shalaginov holds a PhD in Information Security from the Norwegian University of Science and Technology (NTNU), where he worked with digital forensics at the Center for Cyber and Information Security (CCIS). His research spans multiple critical areas of modern cybersecurity with a particular emphasis on Internet of Things security , machine learning applications for threat detection, and digital forensics . He has developed expertise in intelligent malware detection systems, network security for smart environments, and forensic analysis of IoT devices. His work bridges theoretical computer science with practical security implementations for real-world systems. Analysis of his recent publication trends (2022-2025) reveals a strong focus on AI-enabled security solutions for IoT ecosystems, vulnerability detection frameworks, and resource-efficient security mechanisms for constrained devices. His research increasingly addresses the intersection of machine learning and practical security implementations, with growing attention to energy efficiency in security protocols and international data space security frameworks. Dr. Shalaginov has received professional recognition through: Nomination as Norwegian representative in EU COST Action CA17124 "DigForAsp" Nomination as Norwegian representative in EU COST Action CA22104 "BEiNG-WISE" Membership in the "Impact of Technology" Expert Group at the European Union Intellectual Property Office Observatory As head of the Smart Security Lab, Dr. Shalaginov oversees research projects focused on developing practical security solutions for emerging technologies. His GitHub activity demonstrates active development of open-source tools for malware analysis across multiple platforms (Linux, Windows, IoT) and implementation of machine learning approaches for security applications. His research group appears to focus on bridging the gap between theoretical security models and practical implementations for real-world systems.

Roman Vitenbergمشاهده پروفایل

استاد

• Distributed Systems
• Blockchain Technology
• Privacy-Preserving Systems
• +۶ مورد دیگر

Roman Vitenberg is a Professor at the Department of Informatics, University of Oslo. His research focuses on distributed systems, blockchain, privacy, and middleware. He leads the Blockchain Lab, which runs Norway's production node in the EBSI network. Key contributions include work on fault-tolerant overlays, privacy-preserving frameworks for genomic data, and blockchain applications in healthcare. He teaches courses on distributed systems and blockchain technologies. Education: Ph.D. from Technion (Israel Institute of Technology), M.Sc. from Hebrew University of Jerusalem. Previous roles include postdoc at UC Santa Barbara and researcher at IBM. Research Interests: Distributed algorithms, blockchain systems, cloud/fog computing, dependability, and privacy-preserving techniques. Awards: Best Demo Award at ACM DEBS 2014, Best Paper Award at ACM DEBS 2016, Most Influential Paper Award (2007 paper recognized in 2017). Grants & Projects: PriTEM (privacy-preserving energy management), Conserns, Credence, and EBSI-NE (operating Norway's EBSI node). Advising: Supervised over 10 PhD and master students, including notable alumni at Spotify and Max-Planck Institute. Publications: Over 100 peer-reviewed articles in top venues like IEEE Transactions, ACM conferences, and blockchain-focused journals.

• Programming models
• Formal methods
• Distributed systems
• +۳ مورد دیگر

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.

• Robotics
• Intelligent Systems
• Reconfigurable Computing
• +۳ مورد دیگر

Alexander Wold is an Associate Professor at the University of Oslo, affiliated with the Research Group for Robotics and Intelligent Systems within the Faculty of Mathematics and Natural Sciences. His work focuses on reconfigurable computing, embedded systems, and robotics, with notable contributions to FPGA design, real-time systems, and educational technology. He holds a position at the Institute of Informatics (IFI) and can be contacted at alexawo@ifi.uio.no . Research interests include optimizing hardware-software co-design, thermal management in 3D-IC systems, and developing open-source tools like EasyPR for pattern recognition. His publications span topics such as remote cloud labs for reconfigurable logic education, network traffic management in industrial Ethernet, and constraint programming for module placement in FPGAs. Dr. Wold’s articles reflect a strong emphasis on practical applications of robotics and intelligent systems, with a focus on safety-critical industrial systems and autonomic computing. He has contributed to multi-core system design, thermal-aware FPGA architectures, and self-aware systems.

• Cloud computing
• Cybersecurity
• Software Engineering
• +۷ مورد دیگر

Paal Engelstad is a Professor at Oslo Metropolitan University's Faculty of Technology, Art and Design, Department of Computer Science. His research focuses on Cloud computing , Cybersecurity , and Software Engineering , with significant contributions to Graph Neural Networks (GNNs) and their applications in network analysis, renewable energy forecasting, and telecom systems. Research interests span Applied Artificial Intelligence and Autonomous Systems and Networks . Recent publications address spatio-temporal wind forecasting , GNN propagation schemes , and 5G network security . He contributes to advancements in renewable energy integration and telecom protocol analysis .

• Software Engineering
• Cybersecurity
• IoT and Sensor Networks
• +۳ مورد دیگر

Assoc. Prof. Tosin Daniel Oyetoyan is affiliated with the Department of Computing, Mathematics, and Physics at the Western Norway University of Applied Sciences. His academic role focuses on software engineering, cybersecurity, and marine data systems. He leads research in software architecture design, IoT security, and environmental data management. His work bridges theoretical software principles with practical applications in marine technology and agile methodologies. Research Interests: Software architecture patterns for heterogeneous systems Cybersecurity in IoT and cloud environments Data observability and quality in marine sensor networks Empirical analysis of developer security practices API specification repositories and governance His recent publications (2020-2025) emphasize software systems for marine data observatories, cybersecurity in agile teams, and formal specification of environmental monitoring platforms. Noteworthy trends include cross-disciplinary approaches combining software engineering with environmental science. Scientific contributions include frameworks for threat analysis in IoT, empirical studies on developer security competencies, and modular smart ocean observatory designs. His work on data quality requirements for marine systems has informed international standards development. Current projects focus on: Formal specification of marine data platforms Executable architectures for environmental monitoring Agile security practices in distributed teams

• Industrial Robotics
• Digital Twin Technology
• Human-Robot Collaboration
• +۶ مورد دیگر

Beibei Shu serves as an Associate Professor in the Department of Industrial Technology at UiT The Arctic University of Norway, Narvik campus. Her academic position places her within the university's engineering research ecosystem focused on advanced manufacturing technologies. Dr. Shu's research spans multiple dimensions of Industrial 4.0, with particular emphasis on industrial robotics , digital twin technology , and human-robot collaboration . Her expertise extends to virtual reality applications in manufacturing, network communication protocols, computer vision (OpenCV), and hardware circuit design. She possesses substantial technical proficiency in C/C++, Python, and JavaScript programming languages, alongside practical experience with PCB design, microcontrollers, and PLC systems. Analysis of her publication record from 2016-2024 reveals a consistent research trajectory focused on enhancing manufacturing agility through digital technologies. Her work demonstrates increasing sophistication in digital twin implementations, with recent publications addressing Industry 5.0 transition challenges for SMEs and self-reconfigurable manufacturing systems. The research shows strong interdisciplinary connections between robotics, virtual reality, and network security in industrial contexts. Dr. Shu actively contributes to academic instruction as course manager for postgraduate programs including INE-3611 Digital Twin (since 2018) and the upcoming INE-3610 CIM (from 2025). She participates in the TRINITY project focused on developing data acquisition systems for industrial robot digital twins, with research goals targeting improved human-robot interaction and manufacturing flexibility through novel programming architectures. She is a member of the ArcLog research group specializing in Intelligent Manufacturing and Logistics, operating from Campus Narvik (Room D2160). Her collaborative research network includes international partners across Europe, with frequent co-authorship patterns indicating strong institutional connections with researchers like Halldor Arnarson, Bjørn Solvang, and Gabor Sziebig.

Anders Andersenمشاهده پروفایل

استاد

• Adaptive System Architectures
• Multimedia Applications
• Mobility and Context-Sensitive Systems
• +۲ مورد دیگر

Anders Andersen is a Professor and Head of the Department of Computer Science at UiT The Arctic University of Norway. His research focuses on adaptive systems, multimedia applications, context-aware systems, security, and AI/ML. He leads projects like NUDGE (smart nudging for sustainable behavior) and NFC City (NFC-based services). He has extensive teaching experience, supervising numerous master's and PhD students. Affiliations: UiT Department of Computer Science, Open Distributed Systems (ODS) research group Education: Extensive academic background in computer science and related fields (details not explicitly listed). Research Interests: His work spans adaptive system architectures, multimedia systems, mobility/context-aware computing, privacy-preserving techniques, and AI integration. Key projects include secure distributed health data analysis (SNOOP), IoT applications for green transportation, and NFC infrastructure development. Articles Overview: Recent work emphasizes smart nudging methodologies, distributed deep learning optimization, and privacy-preserving frameworks. His publications address cross-platform multimedia systems, context-aware recommendation systems, and security in mobile and cloud environments. Grants/Projects: NUDGE, NFC City, SNOOP, PIA, and others focusing on IoT, health informatics, and adaptive middleware. Labs/Teams: Member of the ODS group, contributing to middleware for distributed applications, adaptive systems, and secure computation.

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

Andrii Shalaginov is an Associate Professor at the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU). His research focuses on cybersecurity, IoT security, machine learning for threat detection, malware analysis, and digital forensics. He has contributed to numerous publications in top-tier journals and conferences, addressing challenges in smart IoT ecosystems, vulnerability detection, and energy-efficient security solutions. Key research interests include: Cybersecurity frameworks for international data spaces Resource-efficient IoT threat detection mechanisms Machine learning applications in malware classification and forensic readiness Energy optimization in AIoT networks His work spans academic collaboration, with notable contributions to frameworks like IoTvulCode for vulnerability detection and MEML for edge-based attack detection. He frequently publishes in venues such as IEEE Access, Future Generation Computer Systems, and Sensors. Notable projects include: Development of distributed deep neural network-based middleware for IoT cyberattack detection Design of hybrid IoT cyber ranges for security training Analysis of blacklisted malicious domains in Windows environments He actively participates in academic workshops and conferences, emphasizing the integration of AI and big data analytics for cybersecurity challenges.

Guru Prasad Bhandariمشاهده پروفایل

پژوهشگر

• Software Engineering
• Cybersecurity
• Machine Learning

Guru Prasad Bhandari is a Researcher at Kristiania University College, School of Economics, Innovation and Technology. He specializes in software engineering, cybersecurity, and machine learning, with a focus on vulnerability detection and automated security solutions. His work includes contributions to projects like CVEfixes, which systematically collects vulnerability fixes from open-source software. Bhandari earned his Ph.D. in 2019 from Banaras Hindu University (India) and completed a postdoctoral fellowship at Simula Research Laboratory (Norway, 2019–2022). He has authored numerous papers on topics such as IoT security, AI-driven vulnerability detection, and distributed cyberattack mitigation. Awards: Silver Jubilee Scholarship (2015) from ICCR Key Projects: CVEfixes (automated vulnerability dataset), IoTvulCode (AI for IoT vulnerability detection)

Frank Eliassenمشاهده پروفایل

استاد بازنشسته

• Distributed systems
• Middleware
• Self-adaptive software systems
• +۵ مورد دیگر

Frank Eliassen is an Emeritus Professor at the University of Oslo's Department of Informatics, specializing in distributed systems and energy informatics. His research spans middleware, IoT, fog computing, and cyber-physical systems with applications in sustainable energy solutions. Research interests focus on: Distributed systems architecture Adaptive peer-to-peer networks Energy-efficient computing Smart grid technologies Cyber-physical system security Publications demonstrate consistent focus on energy informatics, distributed computing security, and renewable energy integration, with recent work exploring AI/ML applications in energy systems. Leads multiple research initiatives including LUCS, AirQMan CPS Lab, DILUTE, and SmartNEM projects addressing smart grid development and IoT systems.

• Information Security
• Communication Systems
• Wireless Sensor Networks
• +۳ مورد دیگر

Amirhosein Taherkordi is an Associate Professor in the Department of Information Security and Communication Technology at NTNU. His research focuses on lightweight adaptation mechanisms in wireless sensor networks (WSNs), emphasizing energy efficiency and reconfigurable component models. He has contributed to the development of adaptable middleware for context-aware systems, evaluated using the Contiki OS. His work addresses challenges in reprogramming and optimizing WSN applications for resource-constrained environments. While no specific educational background is detailed, his affiliations indicate expertise in embedded systems and networked computing. No awards or grants are mentioned in the provided texts, and he has not listed advisees. His research aligns with strategic areas in information security and communication technology at NTNU.