جست‌وجوی استاد و پژوهشگر

• Biometrics
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Raghavendra Ramachandra is a Professor at the Department of Information Security and Communication Technology (IIK) , within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) in Gjøvik. His research focuses on biometric systems, particularly in face, fingerprint, and finger vein recognition, with emphasis on presentation attack detection, morphing attack detection, and deep learning applications. Current research projects include: SALT (2022-2026) : Developing privacy-preserving facial biometric authentication systems. OffPAD (2022-2025) : Creating cryptographic tools and presentation attack detection for fingerprint biometrics. SWAN (2015-2020) : Developing biometric countermeasures against presentation attacks. His recent publications demonstrate technical expertise in: Face morphing attack detection using vision transformers and point cloud networks Image fusion techniques for multispectral biometrics GAN-based synthetic data generation for security evaluation Explainable AI approaches for biometric verification Professor Ramachandra also supervises PhD and Master’s students, and has extensive experience in leading national and EU research initiatives.

Odd Jarl Borchمشاهده پروفایل

استاد

• Emergency Preparedness
• Crisis Management
• Arctic Security
• +۴ مورد دیگر

Professor Odd Jarl Borch is a prominent academic at Nord University specializing in emergency preparedness, crisis management, and Arctic security. His work bridges theoretical research with practical implementation through international collaborations and policy contributions. Education: Harstad Gymnasium Norwegian School of Economics Umeå University, Sweden Indiana University, USA Bodin Maritime College Professor Borch's research focuses on emergency preparedness systems in high-complexity environments, particularly in the Arctic region. His work examines civil-military cooperation, hybrid threats, and organizational management during crises. He has pioneered research on maritime safety in polar regions and developed frameworks for cross-border emergency response coordination. His approach integrates theoretical organizational models with practical crisis management applications, emphasizing the unique challenges of Arctic operations. His recent publications (2020-2024) reveal a strong trajectory toward hybrid threat analysis and collaborative security frameworks. The research consistently addresses Arctic-specific challenges while developing universally applicable emergency response models. Key themes include virtual network intelligence, civil-military coordination mechanisms, and structural adaptations for high-complexity environments. His work demonstrates increasing emphasis on digital transformation in emergency management and the evolving nature of security threats in polar regions. Professor Borch leads significant research initiatives including the NORDLAB Center for Emergency Preparedness and Cooperation and coordinates a network of 25 European researchers on civil-military preparedness. He has initiated major international collaborations such as the Arctic Safety and Security network with 22 universities and the ARCSAR innovation network. His practical impact extends to public service through membership on the Corona Commission, the Total Emergency Preparedness Commission, and the cruise industry safety investigation committee. He has supervised numerous bachelor's, master's, and PhD students in organization and management subjects related to security and crisis management. His teaching portfolio includes fisheries economics, vessel operations, financial management, and crisis management. Professor Borch's laboratory work centers on the NORDLAB emergency management facility, which conducts advanced simulation training for Arctic emergency response professionals.

Daniel Romeroمشاهده پروفایل

استاد

• UAV Communications
• Wireless Communications
• Time-Series Analysis
• +۵ مورد دیگر

**Daniel Romero** is a **Professor** in the **Department of Information and Communication Technology** at the **University of Agder**, Norway. His research focuses on UAV communications, time-series analysis using machine learning and network science, and decentralized processing for sensor networks. He holds a Ph.D. in Signal Theory and Communications from the University of Vigo (2015), an M.Sc. in Signal Theory (2011), and a Telecommunication Engineering degree (2009). **Education**: Ph.D. in Signal Theory and Communications, University of Vigo (2015) M.Sc. in Signal Theory and Communications, University of Vigo (2011) Telecommunication Engineering, University of Vigo (2009) **Research Interests**: His work spans UAV communication systems (focusing on low-latency, high-reliability networks), time-series analysis for complex systems (using ML and network science), and decentralized computation in sensor networks to improve robustness and hardware efficiency. Recent projects include radio map estimation for mmWave beam alignment, spoofing detection via graph neural networks, and aerial base station placement optimization. **Publications**: Over 30+ peer-reviewed articles in top venues like IEEE Transactions on Wireless Communications and ICC. Recent trends emphasize radio map estimation (2023–2024), UAV-enabled spectrum surveying (2022), and robust D2D communications (2022). **Advising & Grants**: Teaches PhD courses (Statistical Signal Processing, Advanced Optimization) and leads the **Advanced Signal Processing Lab (ASL)**. Collaborates with the **CIEM (Center for Integrated Emergency Management)** on crisis-related communication systems. **Labs/Teams**: Directs the Advanced Signal Processing Lab (ASL.uia.no) and contributes to CIEM, applying ML and signal processing to emergency management challenges.

Pouria Akbarighatarمشاهده پروفایل

پژوهشگر ارشد

• Responsible Data Science
• Data Studies in Information Systems
• Fuzzy Mathematics
• +۳ مورد دیگر

Pouria Akbarighatar is a PhD Research Fellow in Responsible Data Science at the Department of Information Systems , University of Agder, Norway, and a visiting PhD researcher at the Centre for Information Resilience (CIRES) , University of Queensland Business School. He holds a BSc in Industrial Engineering and an MSc in Information Systems from the University of Tehran. His research focuses on Responsible AI , including maturity models , fairness frameworks , and ethical implementation in sociotechnical systems. His work combines Fuzzy mathematics , decision science , and data science to address uncertainty and complexity in AI systems. Recent publications explore responsible AI principles in practitioner contexts, operationalizing AI ethics , and credibility assessment in online reviews . He contributes to journals like AI and Ethics , IEEE Access , and Expert Systems with Applications , alongside conferences such as ECIS , AMCIS , and PACIS . He teaches courses in Data Science Applications , Algorithmic and Data Structures , and Data Science Applications II . He is affiliated with the Human-Centered AI (HCAI) research group.

Tor Skeieمشاهده پروفایل

استاد

• High-Performance Networking
• Distributed Systems
• InfiniBand Technology
• +۲ مورد دیگر

Tor Skeie is a Professor at the University of Oslo's Department of Informatics, specializing in networks and distributed systems. His research focuses on high-performance networking, InfiniBand technologies, and adaptive routing systems. Current investigations include automated parameter tuning for reservoir simulations, adaptive routing in InfiniBand hardware, and modeling WiFi quality attenuation. His work develops efficient solutions for virtualized HPC environments and cloud computing infrastructures. Recent publications demonstrate innovations in network modeling, adaptive routing algorithms, and performance analysis of distributed systems. Research collaborations span European projects on high-performance networking infrastructures. Leads the Networks and Distributed Systems (ND) research group investigating fault-tolerant routing, network virtualization, and congestion control mechanisms.

Stefano Nicheleمشاهده پروفایل

استاد

• Artificial Life
• Neuro-Inspired Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Stefano Nichele is a Professor at the Department of Computer Science and Communication, Østfold University College, Norway. He holds additional roles as Professor II at OsloMet and has served in leading academic positions since 2014. His research focuses on Artificial Life (ALife), Neuro-Inspired AI, and Machine Learning, with a particular emphasis on cellular automata, reservoir computing, and neuro-inspired substrates. Nichele co-directs the Østfold AI (ØAI) hub and is an active member of IEEE, ELLIS, and the Norwegian AI Research Consortium (NORA). He earned his PhD in Computer Science from NTNU (2015) and completed his MSc at the University of Insubria, Italy. His work bridges computational systems and biological substrates, exploring criticality in neural networks and quantum-evolutionary algorithm interactions. He has received prestigious awards, including the Young Research Talent grant (2019) and the Distinguished Early-Career Investigator award (2024). Nichele’s research spans theoretical and applied domains, with over 50 publications on cellular automata dynamics, neuro-inspired robotics, and AI ethics. His recent projects include studying in vitro neural networks for computational capacity assessment and developing frameworks for body-brain co-evolution in soft robotics. Education: PhD in Computer Science, NTNU (2015) MSc in Computer Science, University of Insubria (2009) Awards: Young Research Talent grant (2019) Distinguished Early-Career Investigator (2024) Grants & Roles: Co-director of the Østfold AI hub Board member of NORA (Norwegian AI Research Consortium) Labs & Collaborations: Focus on neuro-inspired AI systems and unconventional computing Partnerships with institutions like Simula Metropolitan and the International Society for Artificial Life (ISAL)

• Structural Engineering
• Timber and Steel Composite Structures
• Fire Safety Engineering
• +۵ مورد دیگر

Bunji Izumi is an Assistant Professor at the Department of Architecture and Technology, Faculty of Architecture and Design, NTNU, supported by the Scandinavia-Japan Sasakawa Lectureship. He holds a Dipl.-Ing., M.Sc., and B.Eng., and is a registered architect in Japan. His career includes roles at Nikken Sekkei Ltd. (Tokyo) as Senior Computational Designer and Associate in Structural Design, and at Driendl Architects in Vienna, Austria. His research focuses on structural engineering, timber-steel composite systems, fire safety, digital design, and sustainable architecture. Key areas include optimization methods in architectural design, circular timber structures, and interdisciplinary collaboration between architects and engineers. Publications highlight work on foldable canopies, fire-resistant composites, BIM integration, and structural education reforms. He contributes to exhibitions like IASS 2019 and collaborates on projects such as the Shogakukan Building and Vienna Indoor Swimming Pool. His educational background includes postgraduate studies at TU Vienna and the University of Tokyo, emphasizing structural design and timber engineering. Current research trends emphasize sustainability, circular design, and computational workflows.

• Agent-Based Modeling
• Social Simulation
• Urban Systems
• +۳ مورد دیگر

Timo Szczepanska is a postdoctoral researcher at UiT The Arctic University of Norway , affiliated with the Norwegian College of Fishery Science . With expertise in computational modeling and social simulation, Szczepanska contributes to interdisciplinary research bridging technology, environmental science, and urban systems. Current member of the CRAFT research group Active participant in the FUTURES4Fish project Published extensively in journals like JASSS and Frontiers in Marine Science Research Focus: Szczepanska's work explores urban complexity through participatory simulations, develops agent-based models for human behavior analysis, and investigates climate change impacts on fisheries. Key methodological contributions include model reimplementations and integrating creative writing with future scenario planning. Recent Article Trends: Recent publications demonstrate a dual focus on decarbonisation strategies for urban mobility and innovative approaches to fisheries governance under climate change. Methodologically, Szczepanska combines agent-based modeling with game design and creative worldbuilding across multiple domains. Collaborative Networks: Collaborates with international researchers across institutions including Radboud University, Potsdam University of Applied Sciences, and various European research groups. Specializes in translating complex systems into interactive pedagogical tools and policy-relevant simulations. Technical Expertise: Proficient in computational platforms like NetLogo and Unity, with particular emphasis on model documentation, validation, and interdisciplinary translation of technological futures.

Solveig Bruvollمشاهده پروفایل

دانشیار

• Autonomous Systems
• Cybersecurity
• Military Technology
• +۴ مورد دیگر

Solveig Bruvoll is an Associate Professor at the University of Oslo (15% position) and holds a 100% research position at the Norwegian Defence Research Establishment (FFI). She specializes in Autonomous Systems and Cybersecurity , focusing on security in military operations and software resilience. Her work bridges engineering, mathematics, and defense applications. Research interests include autonomous vehicle security, defense simulation, and mathematical modeling. She teaches the course TEK5510 and has published extensively in conferences like IEEE CNS and journals such as Journal of Defense Modeling and Simulation . Her FFI affiliation emphasizes practical military technology and operational analysis. Publications highlight contributions to path planning algorithms, command agent modeling, and cybersecurity frameworks for autonomous systems. She collaborates on NATO projects, as seen in her work on M&S support for operational tasks. No awards are explicitly listed, but her research impacts critical defense and civilian infrastructure security domains.

• Water Infrastructure Engineering
• Sustainable Water Management
• Urban Water Transport Systems
• +۷ مورد دیگر

Abbas Roozbahani is an Associate Professor in the Department of Building and Environmental Technology at the Faculty of Science and Technology, Norwegian University of Life Sciences (NMBU). His academic expertise lies in Water Infrastructure Engineering, where he contributes to research, teaching, and project leadership in sustainable urban water systems. His research interests include: Sustainable water management Urban water transport systems (drinking water, wastewater, stormwater) Risk assessment of water infrastructure Simulation and optimization of water systems Hydroinformatics and artificial intelligence Asset management for urban water infrastructure The analysis of his recent publications (2022–2025) reveals a strong focus on integrating advanced computational methods—such as Bayesian Networks, Fault Tree Analysis, machine learning (e.g., LSTM), and multi-criteria decision-making (MCDM)—into water resources management. His work frequently addresses urban stormwater optimization, drought and climate change risk assessment, groundwater forecasting, and the water-food-energy nexus, demonstrating a consistent trend toward data-driven, risk-informed, and sustainable solutions for complex water systems. Dr. Roozbahani teaches graduate-level courses including: THT301 - Asset Management for Urban Water Infrastructure THT302 - Analysis and Design of Water Distribution Networks THT261 - Introduction to Water and Wastewater Systems (co-instructor) THT313 - Water Management in Changing Conditions (co-instructor) THT390 - Preparations for the Master's Thesis (co-instructor) He has supervised multiple MSc and PhD students and led projects funded by academic and private institutions. His collaborative research spans international institutions, with frequent co-authorship on topics related to risk modeling, AI in hydrology, and sustainable infrastructure planning.

• Ultrasound
• Medical Imaging
• Signal Processing
• +۶ مورد دیگر

Nils Sponheim is an Associate Professor at Oslo Metropolitan University (OsloMet) in the Faculty of Technology, Art and Design, Department of Mechanical, Electrical and Chemical Engineering. His research focuses on ultrasound, medical imaging, and signal processing, with particular emphasis on contrast agents, Doppler imaging, and biomedical engineering applications. He has contributed extensively to ultrasound transducer design and problem-based learning pedagogy. Academic Affiliation: OsloMet – Faculty of Technology, Art and Design Research Areas: Ultrasound physics, contrast agent development, Doppler signal analysis, medical imaging instrumentation Education Focus: Problem-Based Learning (PBL) in engineering His publications span transient ultrasonic fields, synchronization techniques for contrast agents, and clinical applications in cardiology and oncology. Key subfields include pulse shaping, frequency resolution limitations, and transducer design. Sponheim's work bridges engineering and clinical diagnostics, with collaborations in cardiology and oncology imaging. Current projects focus on pulsed ultrasonic fields and practical measurement systems.

• Power System Dynamics and Control
• Distributed Power Generation
• Optimization Methods
• +۷ مورد دیگر

Pawan Sharma is an Associate Professor at the Department of Electrical Engineering, Faculty of Engineering Science and Technology, UiT The Arctic University of Norway (Narvik Campus). He is affiliated with the Electromechanical Systems research group and the ARC research center. His research focuses on: Power system dynamics and control Distributed generation integration Microgrid optimization Smart grid technologies Reactive power control Electric vehicle-grid interaction Key research trends observed in his publications include: Hybrid microgrid control frameworks Cyber-physical co-simulation for grid applications Machine learning approaches for power optimization Integration of renewable energy sources Advanced converter control techniques Voltage stability and reactive power management He serves on the editorial boards of: International Transactions on Electrical Energy Systems Designs (MDPI) Electrical Engineering (Springer) Teaching responsibilities: Master's course: Power System Fundamentals (10 credits) Special PhD course: Distributed Energy Resources Integration (10 ECTS) Distributed Generation & Microgrids: Role and Concepts (5 credits) Research projects include: Cooperative Isolated Renewable Energy Systems (rural reliability) Hybrid Renewable Energy Micro Grid development Smart Solar PV Control Technology in Arctic regions arcICE, Arctic Energy, nICE initiatives

• Energy Harvesting
• Low-Power Electronics
• Bio-Inspired Systems
• +۳ مورد دیگر

Ali Muhtaroglu is an Associate Professor at Oslo Metropolitan University, Faculty of Technology, Art and Design, Department of Mechanical, Electronics and Chemistry. His work focuses on energy-efficient electronics and bio-inspired technologies through the ADEPT research group. Research Interests: Dr. Muhtaroglu specializes in bio-inspired spiking neural networks energy harvesting systems low-power circuit design autonomous IoT devices wearable health monitors quantum dot cellular automata His publications emphasize hardware-software co-design for sustainable microelectronics. Selected Articles (2022-2024): Recent work includes bio-inspired reinforcement learning architectures (2024), AI accelerator design (2022), and self-powered health monitoring systems (2023). Earlier publications (2019-2021) cover cochlear implant interfaces and piezoelectric energy harvesting.

• Human-Computer Interaction
• Universal Design of ICT
• Pattern Recognition
• +۴ مورد دیگر

Frode Eika Sandnes is a Professor at the Department of Information Technology , Faculty of Technology, Art and Design , Oslo Metropolitan University , focusing on Human-Computer Interaction and Universal Design of ICT . His research spans innovative interaction techniques, skill reuse, pattern recognition, image analysis, and intelligent systems. Current research trends include accessibility in digital education, lightweight deep learning models, and physical interface usability Recent publications analyze color picker efficiency, 3D-printed prosthetics, and authentication technologies His work integrates interdisciplinary approaches to enhance usability and inclusivity in technology. Notable projects involve automated readability assessments and AI applications in diverse domains like aquaculture and medical diagnostics.

Riccardo Simionatoمشاهده پروفایل

پژوهشگر ارشد

• Deep Learning
• Audio Modeling
• Sound Synthesis
• +۳ مورد دیگر

Riccardo Simionato is a Research Fellow in the Department of Musicology at the University of Oslo (UiO), affiliated with the Faculty of Humanities. He holds a MSc and BSc in Computer Science and Information Engineering from the University of Padova, Italy, and conducted research at Aalto University, Finland (2017–2018). His research focuses on nonlinear audio modeling using deep learning, particularly addressing low-latency interactive solutions for acoustic and electronic musical instruments/devices. Education: 2018: MSc in Computer Science Engineering, University of Padova 2015: BSc in Information Engineering, University of Padova Research Interests: Deep Learning , Audio Modeling , and Sound Synthesis . He explores how deep learning can approximate complex nonlinear phenomena in audio systems, balancing computational efficiency with interpretability. Recent work emphasizes hybrid neural-audio effects, time-variant systems, and physics-informed methods for piano modeling. Publications highlight advancements in optical compressor modeling, piano analysis, and tools for generating audio effect datasets. His work bridges machine learning and music technology, aiming for practical applications in real-time audio processing and electronic instrument emulation. Grants and advising: No specific grants or student advisees listed in the provided text. Collaborations include projects with Prof. Stefano Fasciani and teams at UiO’s Department of Musicology. Labs/Teams: Active within UiO’s Sound and Music Computing research group, focusing on interdisciplinary projects combining computer science and music technology.