جست‌وجوی استاد و پژوهشگر

Kjell Gunnar Robbersmyrمشاهده پروفایل

استاد

• Mechatronics
• Machine Design
• Condition Monitoring
• +۵ مورد دیگر

Kjell Gunnar Robbersmyr is a Professor at the University of Agder's Department of Engineering Sciences and director of the Top Research Center in Mechatronics. With a Ph.D. in mechanical engineering from NTNU (1992), his career spans academic leadership, research management at Agder Research, and active contributions to IEEE. His work focuses on mechatronics, machine design, and condition monitoring, with special emphasis on fault diagnosis in electric motors and vehicle crash modeling. Senior Member of IEEE Member of Norwegian Academy of Technical Sciences Member of Agder Academy of Sciences Research interests include: Advanced fault diagnosis in electric drives using AI and signal processing Vehicle crashworthiness modeling with lumped parameter and finite element methods Optical measurement technology for machine monitoring Digital twin applications for infrastructure and wind energy systems Condition monitoring of low-speed bearings and rotating machinery Recent publications demonstrate expertise in: Deep learning for imbalanced motor fault datasets Transformer networks in power electronics diagnostics 3D reconstruction techniques for mechanical systems Multi-classifier decision fusion in power systems Dynamic operations modeling for electric vehicles Scientific contributions include: Over 50 peer-reviewed articles Leadership in the Intelligent Monitoring research group Development of novel inverter topologies Innovations in wind turbine condition monitoring Advancements in laser-based mechanical diagnostics

Linga Reddy Cenkeramaddiمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Autonomous Systems
• Robotics and Automation
• +۷ مورد دیگر

Linga Reddy Cenkeramaddi is a **Professor** in the Department of Information and Communication Technology at the University of Agder (UiA), Norway. He holds a PhD in Electrical Engineering from NTNU (Trondheim, Norway) and Master’s degrees from IIT Delhi and IIT Chennai. His research focuses on Cyber-Physical Systems (CPS), Autonomous Systems, Robotics, AI/ML, Wireless Sensor Networks, and 5G/6G-enabled technologies. He leads projects such as LUCAT (UAV communication tracking) and INCAPS (Indo-Norwegian collaboration in CPS). **Education**: PhD (NTNU), MSc in Physics (IIT Chennai), MSc in Integrated Electronics (IIT Delhi). **Research Interests**: Energy-efficient wireless communication, autonomous vehicles, edge intelligence, mmWave sensing, and smart cities. **Teaching**: Courses include embedded systems, mmWave sensing, and wireless prototyping. **Key Contributions**: Developed low-power embedded systems, contributed to UAV communication protocols, and pioneered AI-driven healthcare solutions. **Grants**: Co-PI in the INMOST offshore mechatronics project. **Labs/Teams**: Autonomous and Cyber-Physical Systems (ACPS), Electronics and IoT (E&IOT), Intelligent Mechatronics (iTron). His work bridges academia and industry, impacting healthcare, smart agriculture, and environmental monitoring. Future research includes multi-modal sensing, multi-agent systems, and 6G communication integration with AI.

• Cybersecurity
• Information Security
• Security Assurance
• +۷ مورد دیگر

Basel Cat is a Professor and Head of the Department of Information Security and Communication Technology at NTNU's Faculty of Information Technology and Electrical Engineering. His research focuses on cybersecurity, information security assurance, and innovative approaches to cyber range technologies. Key areas include vulnerability analysis, privacy protection, and AI-driven security solutions. Research Interests Cybersecurity incident triage and attack chain analysis Quantitative security evaluation models for web and cloud services Automated vulnerability injection in source code IoT security and cognitive digital twin architectures Adversarial AI applications in cybersecurity exercises Publications highlight advancements in cybersecurity education, attack-defense scenario modeling, and the integration of AI/LLMs in security frameworks. Recent work explores frameworks for evaluating cloud services and OWASP-aligned web application security standards. Collaborations involve development of hybrid IoT cyber ranges and frameworks for security assurance metrics. His research has been featured in top-tier journals like Computers & Security and Journal of Information Security and Applications .

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

Kyrre Begnum is an Associate Professor at OsloMet – Oslo Metropolitan University, affiliated with the Faculty of Technology, Art and Design through the Department of Computer Science. His research spans cloud computing, cybersecurity, and software engineering, with a focus on virtual machine management, intrusion detection, and autonomic systems. Cloud Computing Cybersecurity Software Engineering Machine Learning Data Center Management His recent publications emphasize adversarial machine learning in security, affinity-aware scheduling for cloud efficiency, and network optimization in virtualized environments. While no formal awards are documented in the provided texts, his work demonstrates technical innovation in distributed systems and educational applications of virtualization technology.

• Wireless Communication
• Signal Processing
• 6G Networks
• +۳ مورد دیگر

Arild Moldsvor is an Associate Professor at the Norwegian University of Science and Technology (NTNU), located in Gjøvik. He is affiliated with the Department of Electronic Systems, focusing on advanced wireless communication technologies, signal processing, and antenna design. His research emphasizes 6G networks, channel modeling in diverse environments (urban, industrial, and body-centric), and transceiver design innovations. He has contributed to studies on IQRF networks, GFDM modulation, and interference mitigation in dynamic settings like sports activities and indoor spaces. Teaching includes courses on wireless communication, digital signal processing, and electronics. Notable outreach includes a 2021 lecture on adversarial machine learning security for 6G mmWave beam prediction at IEEE BlackSeaCom in Bucharest.

Pekka Parviainenمشاهده پروفایل

دانشیار

• Machine Learning
• Bayesian Networks
• Graphical Models
• +۷ مورد دیگر

Pekka Parviainen is an Associate Professor in the Department of Informatics at the University of Bergen, within the Faculty of Mathematics and Natural Sciences. His research spans machine learning, probabilistic modeling, and AI theory, with a focus on Bayesian and Markov networks, adversarial robustness, fairness, and energy forecasting. He is affiliated with the Center for Data Science (CEDAS), an active research center at the university. His research interests include: Structure learning in graphical models Probabilistic forecasting using graph neural networks Adversarial robustness and defense mechanisms Fairness in clustering and machine learning Optimization and approximation in learning algorithms Applications in renewable energy and quantum sensing His recent publications (2020–2025) reflect a strong theoretical grounding combined with real-world applications, particularly in energy systems and AI safety. The works trend toward scalable and interpretable models, with increasing focus on fairness and robustness. Key themes include Bayesian network learning, metric learning, and causal graph modeling. Scientific contributions include: Development of novel adversaries (e.g., Voronoi-epsilon) for measuring robustness Scalable algorithms for learning large DAGs and Bayesian networks Integration of continuous optimization with combinatorial heuristics Applications in electricity demand forecasting and gas sensing Parviainen advises PhD students, including Hyeongji Kim (2023 thesis on distance in machine learning), and collaborates extensively with researchers in Norway and internationally. He has received computational support via Sigma2 (NN9884K) and is part of the CEDAS project, which fosters interdisciplinary data science research. While no specific grants are detailed, his involvement in funded projects and high-impact publications indicates active grant engagement. He is associated with the Center for Data Science (CEDAS), where he contributes to advancing data-driven methodologies across domains. The team emphasizes scalable, robust, and fair AI systems, aligning with national and international research priorities in trustworthy machine learning.

• Digitalization
• Control Systems
• Optimization Algorithms
• +۴ مورد دیگر

Guoyuan Li is a Professor at the Department of Ocean Operations and Civil Engineering, Faculty of Engineering, Norwegian University of Science and Technology (NTNU), Ålesund Campus. His work bridges digitalization , artificial intelligence , and maritime engineering , focusing on ship maneuvering, robotics, and human-machine interaction. Ph.D. in Computer Science, University of Hamburg (2013) M.S. & B.S. in Computer Science, Chongqing University (2009 & 2006) Research Interests: Digital twin systems for ships, adaptive locomotion control in bio-inspired robotics, trajectory prediction for marine vessels, and human visual attention analysis in maritime operations. He integrates machine learning and physics-based models to enhance safety and efficiency in marine environments. Publications highlight trends in ship motion prediction , collision avoidance , and environmental disturbance modeling , with applications in digital twin technology and remote control centers . His work spans IEEE and Springer journals. Awards include multiple Best Paper Awards at IEEE conferences (2024-2014). He serves as Associate Editor for IEEE Journal of Oceanic Engineering and IEEE Transactions on Intelligent Transportation Systems . Projects include EU’s RoboSapiens (robot adaptation), Digital Twin for Green Ship Operations (Norway), and AuReCo (remote control systems). He collaborates with the Intelligent Systems Lab at NTNU.

• Artificial Intelligence
• Machine Learning
• Signal Processing
• +۶ مورد دیگر

Anis Yazidi is an Associate Professor at the Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, where he leads research in the Research Group for Digital Signal Processing and Image Analysis. His academic profile demonstrates significant contributions to artificial intelligence, machine learning, and signal processing with over 50 publications between 2021-2025 in high-impact venues including IEEE Transactions, Frontiers journals, and AAAI proceedings. Professor Yazidi's research spans multiple interconnected domains with particular emphasis on Tsetlin Machines, deep learning for medical applications, and signal processing theory. His work bridges theoretical foundations with practical implementations, developing novel frameworks like DREAMS for EEG analysis with model card reporting and interpretable methods for ECG classification. His contributions to learning automata theory, particularly in convergence analysis of Tsetlin-based algorithms, represent significant theoretical advances. The research portfolio also extends to cybersecurity applications of AI for IoT protection, agricultural technology for plant disease detection, and renewable energy modeling for wind-speed statistics. Yazidi's publication record reveals a strong interdisciplinary approach, with collaborations across computer science, neuroscience, medical diagnostics, and engineering disciplines. His recent work shows increasing focus on trustworthy AI systems, ethical considerations in medical applications, and specialized neural architectures tailored for specific data modalities including EEG, ECG, and eye-tracking data. The research demonstrates both theoretical rigor in algorithm development and practical implementation for real-world problems. Professor Yazidi maintains an active collaboration network with researchers across the Department of Informatics at UiO, particularly with Pedro Lind, Hugo Lewi Hammer, and Paal Engelstad, while also engaging in international collaborations. His work contributes significantly to both the theoretical foundations of learning systems and their practical implementation in diverse application domains from healthcare to renewable energy.

Ahmet Soyluمشاهده پروفایل

دانشیار

• Knowledge Graphs
• Semantic Web
• Data Integration
• +۳ مورد دیگر

Ahmet Soylu is Associate Professor in Data and Knowledge Management at the University of Oslo. His research develops semantic technologies and knowledge systems for applications in healthcare, cloud computing, and industrial domains. Research Focus Creates knowledge graph systems for data integration and analysis, with applications in medical diagnostics (cancer/brain tumor classification), cloud cost optimization, and industrial monitoring systems. Develops transformer-based models for SQL recommendation and data linking. Publication Trends Recent work shows strong emphasis on healthcare AI (particularly cancer diagnostics), cloud storage optimization, knowledge graph embeddings, and industrial applications at Bosch. Increasing focus on imbalanced learning techniques for medical data. Project Leadership Developed Koala-UI for tabular data linking Semantic systems for Bosch welding quality monitoring Open energy management systems for EV charging

• Bio-inspired materials
• Nanofiber fabrication
• Acoustic microscopy
• +۷ مورد دیگر

Komal Agarwal is a researcher at UiT The Arctic University of Norway, Department of Physics and Technology, focusing on bio-inspired materials, acoustic microscopy, and biomedical applications. Her work bridges materials science, biomedical imaging, and renewable energy technologies. Research interests include: Bio-inspired materials for acoustic transducers and optical microscopy calibration Acoustic and photo-acoustic imaging for biomechanical properties Advanced materials for cancer drug screening and tissue engineering Ultrasonic wave propagation and composite design Article trends show expertise in acoustic microscopy (2024-2022), bioimaging (2023-2022), and helicoidally structured composites (2022-2020). Recent work emphasizes hydrogel calibration tools (2024) and Arctic acoustic sensing applications (2023). Scientific awards: EIC Tech to Market Pioneer Program (Cymoplive) EIC Tech to Market Venture Program (Cymolive) SUTD PhD Fellowship (2016-2021) Gold Medalist (institutional highest undergraduate GPA) Advising includes Camille Corrio (BSc intern). Secured multiple grants including Norwegian Research Council funding (2024) for optical microscopy calibration prototypes and Arctic acoustic sensing projects. Key lab affiliations: Ultrasound, Microwaves, and Optics research group at UiT.

• Cloud Computing
• Virtualization
• System Administration
• +۴ مورد دیگر

Kyrre Matthias Begnum serves as an Associate Professor at the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU). His academic career spans over two decades with significant contributions to cloud infrastructure, virtualization technologies, and system administration practices. Dr. Begnum's research focuses on several key areas within computer systems: Cloud computing and virtualization technologies Resource management and optimization in data centers Network security and intrusion detection systems System administration education and pedagogy Unikernels and lightweight virtualization approaches Application of machine learning to system management problems His publication record demonstrates consistent innovation in virtual machine management, with notable contributions including the application of stable marriage matching theory to load distribution problems and the development of Bayllocator, a proactive system using Bayesian networks for memory resource allocation. Begnum's work bridges theoretical computer science with practical infrastructure challenges, particularly in data center optimization. His recent publications show expanding interests into historical perspectives of computing, as evidenced by his 2024 book 'From EDB to KI. 40 years of information technology,' which examines the evolution of information technology over four decades. This demonstrates his ability to connect historical context with current developments in artificial intelligence and computing systems. Dr. Begnum has made substantial educational contributions through works like 'The Uptime challenge: A learning environment for value-driven operations through gamification' and his investigations into MSc program learning outcomes for Network and System Administration. His commitment to science communication is evident through public engagements like the 'Anti-IKT debatt' and 'Vitenshow: Roboten og du' presentations.

• Cyber defense
• Reverse engineering
• Malware analysis
• +۷ مورد دیگر

Geir Olav Dyrkolbotn is an Associate Professor at the Norwegian University of Science and Technology (NTNU), affiliated with the Center for Cyber and Information Security (CCIS). He leads the NTNU Malware Lab and the Cyber Defence research group. His expertise bridges academic research with military experience from over 25 years in the Norwegian Armed Forces. PhD in Information Security from Gjøvik University College MSc in Computer Science from Norwegian Institute of Technology (NTH) His research focuses on cyber defense , reverse engineering , and malware analysis , with significant work in side-channel attacks and machine learning . He has contributed to hardware security, IoT vulnerabilities, and digital forensics through publications spanning 2006–2024. Recent publications highlight trends in malware detection via low-level features , hardware reverse engineering , and IoT security , reflecting his interdisciplinary approach to cyber threats. Collaborative works with institutions like IEEE and Springer demonstrate his industry and academic impact. Geir supervises PhD student Sergii Banin , leads critical research labs, and contributes to education through courses like Reverse Engineering and Malware Analysis. His work emphasizes practical applications in military and civilian cyber infrastructure defense.

Filip Holikمشاهده پروفایل

دانشیار

• Cybersecurity
• Smart Grids
• Software-Defined Networking
• +۶ مورد دیگر

Filip Holik is an Associate Professor at the Department of Information Security and Communication Technology at Norwegian University of Science and Technology (NTNU). He works remotely at the University of Glasgow, Scotland, and is actively involved in cybersecurity research for critical infrastructure. Key research areas: eBPF-based programmable data planes, Smart Grid security, Digital Substations, Software-Defined Networking. Major projects: Multidisciplinary Research group on Privacy and data protection (MR PET) , ECoDiS - Engineering and Condition monitoring in Digital Substations , InterSecure - Security of supply in smartgrids . Publications focus on eBPF security frameworks, digital substation threat modeling, and smart grid cybersecurity. His work addresses security of supply in interconnected digital systems and develops adaptive learning mechanisms for attack detection. Technical contributions include developing simulation models for Digital Substations, serving as a Smart Grid Simulation Model developer , and Digital Security instructor for industrial network training programs.

• Cybersecurity
• Artificial Intelligence
• Knowledge Management
• +۵ مورد دیگر

Shao-Fang Wen serves as Associate Professor in the Department of Information Security and Communication Technology within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). Her academic role centers on advancing cybersecurity research and education with a focus on critical infrastructure protection. Her research interests include Artificial Intelligence security, Knowledge Management, Secure Software Development, Semantic Web Technology, Ontology, Socio-Technical Systems, and System Security Assurance. She is actively involved with the Norwegian Center for Cybersecurity in Critical Sectors, focusing on practical and theoretical aspects of security in critical infrastructure through ontological modeling and quantitative evaluation frameworks. Analysis of her recent publications (2020-2025) reveals a strong emphasis on quantitative security assurance frameworks, ontological modeling, and the integration of AI in security systems. Her work consistently addresses contextualizing security knowledge for developers and systems, evolving from open source community studies to advanced AI security frameworks with increasing technical sophistication. No scientific awards are mentioned in the available information. Details regarding student advising and research grants are not provided in the source material, though her extensive publication record indicates active research supervision and project leadership. Dr. Wen is affiliated with the Norwegian Center for Cybersecurity in Critical Sectors, a key research entity at NTNU dedicated to enhancing cybersecurity resilience in critical national infrastructure through interdisciplinary collaboration and practical security solutions.

• Cybersecurity
• Artificial Intelligence
• Cyber Ranges
• +۵ مورد دیگر

Muhammad Mudassar Yamin serves as an Associate Professor in the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU), Gjøvik campus. His academic work spans cybersecurity research, artificial intelligence applications, and cyber range development, with significant contributions to security exercise frameworks and adversarial machine learning. His research interests focus on Cybersecurity , particularly in cyber ranges, security assurance, and AI-driven threat detection. Key areas include Kill Chain analysis, adversarial machine learning for hate speech detection, and security exercise scenario generation. Recent work demonstrates increasing integration of large language models for cybersecurity training and multilingual threat detection systems. Yamin's publication trends show consistent output in top cybersecurity venues, with recent emphasis on AI applications for security (2022-2025). His work bridges theoretical frameworks and practical implementations, particularly in cyber range technologies and threat intelligence systems. Collaborations with researchers like Basel Katt and Ehtesham Hashmi appear frequently across publications. He teaches courses including IIK3100 - Ethical Hacking and Penetration Testing and TTM4175 - Introduction to Cyber Security and Data Communication, reflecting his expertise in practical security education. His doctoral thesis (2022) focused on modeling and analyzing attack-defense scenarios for cyber ranges, establishing the foundation for his current research trajectory.