جستجوی استاد راهنمای دانشگاهی

• Combustion Engineering
• Alternative Fuels
• Hydrogen Energy
• +۵ مورد دیگر

Terese Løvås serves as Vice Dean of Research and Innovation at the Faculty of Engineering, Norwegian University of Science and Technology (NTNU), where she leads strategic development of research and innovation activities. She concurrently holds the position of Professor of Combustion and Thermodynamics within the Department of Energy and Process Engineering. Her leadership responsibilities include oversight of Centers of Excellence, Horizon Europe projects, and PhD researcher training. Her research focuses on combustion engineering and alternative fuel technologies , particularly investigating ammonia and hydrogen combustion for zero-emission engines, biomass gasification processes, and reactive multiphase flow modeling. She heads the Engine Lab at NTNU and teaches Thermodynamics, Heat, and Combustion courses. Her work bridges theoretical modeling with experimental validation in sustainable energy systems. Løvås actively contributes to major research initiatives including LowEmission (SFI center), ACTIVATE (ammonia-powered agricultural vehicles), AMAZE (ammonia zero-emission), and CAHEMA (marine ammonia/hydrogen engines). Her publications reveal strong trends in ammonia combustion chemistry , emissions reduction , and advanced computational modeling for sustainable fuel systems, with increasing focus on nitrogen oxide formation mechanisms and dual-fuel strategies. Member of the Board of Directors, Combustion Institute (2022–present) Joint Editor, Proceedings of the Combustion Institute (2019–present) Alumni Fellow in Engineering, Churchill College, Cambridge University As Vice Dean, she manages NTNU's Research and Innovation Committee and represents the faculty in NTNU's Research and Innovation Committee. She supervises multiple PhD candidates and leads international collaborations through projects funded by the Norwegian Research Council, Nordic Energy Research, and EU programs. Her laboratory work focuses on optical engine diagnostics and advanced combustion testing. Løvås maintains active industry engagement through her leadership in the ComKin Research Group and membership in the Institute of Physics and Scandinavian-Nordic Section of the Combustion Institute. Her current work emphasizes practical implementation of ammonia-fueled engine technologies for marine and agricultural applications.

• Microelectronics
• Analog/Digital Circuit Design
• Ultra Low Power Circuits
• +۱ مورد دیگر

Snorre Aunet is a Professor at the Department of Electronic Systems at the Norwegian University of Science and Technology (NTNU), with additional roles as an Adjunct Professor at the Department of Informatics, University of Oslo. His academic career spans institutions in Norway, Germany, and the USA, including sabbaticals at Bielefeld University and University of California, San Diego. Education: Electronics Engineering (Trondheim Technical College, 1987), Informatics (UiO, 1993), and Physical Electronics (NTNU, 2002) Research Focus Dr. Aunet specializes in ultra-low-power mixed-signal integrated circuits and nanoscale CMOS technologies . His work includes innovative MEMS transducer designs for energy harvesting, digital IC development, and robust circuit solutions for emerging semiconductor challenges. Recent Publications His recent contributions include advancements in MEMS technology for sustainable energy systems, editorial leadership at NorCAS conferences, and policy discussions on the European Chips Act. These reflect expertise in both cutting-edge design and strategic technology development. Scientific Recognition 2019: Elected to Norwegian Academy of Technical Sciences (NTVA) 2015: Best Paper Award at Asia Symposium on Quality Electronic Design 2006: IEEE Senior Member (Electron Devices Society) 2003: Best Poster Award at Int'l Conf. on Evolvable Systems Leadership & Grants He has chaired multiple IEEE conferences and contributed to projects like Robust Ultra-Low-Power Circuits for Nano-Scale CMOS (NTNU/University of Paderborn). His career combines academic leadership with industry collaboration through Nordic Semiconductor and international research councils.

Ole-Christoffer Granmoمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Tsetlin Machines
• +۷ مورد دیگر

Professor Ole-Christoffer Granmo is a distinguished academic at the University of Agder, Norway, where he serves as Professor in the Department of Information and Communication Technology. He is the Founding Director of the Centre for Artificial Intelligence Research (CAIR) at the University of Agder, leading cutting-edge research in artificial intelligence and machine learning. Dr. Granmo obtained his master's degree in 1999 and his PhD in 2004, both from the University of Oslo. His academic journey has been marked by significant contributions to the field of AI, most notably the creation of the Tsetlin machine in 2018, for which he received the AI research paper of the decade award from the Norwegian Artificial Intelligence Consortium (NORA) in 2022. Professor Granmo's research primarily focuses on logical and causal world modeling across multiple modalities including images, sound, and natural language. His work spans logical auto-encoding, convolution, regression, transformer architectures, and reinforcement learning, all with the overarching goal of creating ultra-low-power artificial general intelligence through transparent logical learning and reasoning. His publications reveal a strong emphasis on interpretable AI systems, hardware implementations, and applications across diverse domains including cybersecurity, healthcare, social media analysis, and bioinformatics. AI Research Paper of the Decade (2022) - Norwegian Artificial Intelligence Consortium (NORA) Eight paper awards in machine learning Professor Granmo has coordinated over seven research projects and mentored 55+ master's students and nine PhD students. His leadership extends to co-founding the Norwegian Artificial Intelligence Consortium (NORA) and establishing two companies: Anzyz Technologies AS and Tsense Intelligent Healthcare AS. As an advisor at Literal Labs, he actively bridges academic research with practical industry applications, demonstrating his commitment to translating theoretical innovations into real-world solutions that address complex challenges across multiple sectors.

• Cyber Defence
• Reverse Engineering
• Malware Analysis
• +۵ مورد دیگر

Geir Olav Dyrkolbotn is an Associate Professor at NTNU's Center for Cyber and Information Security (CCIS) and a Major in the Norwegian Armed Forces, serving at the Norwegian Defence Cyber Academy (NDCA). He leads the NTNU Malware Lab and the cyber defence research group at CCIS. He holds a PhD in Information Security from Gjøvik University College and a MSc in Computer Science from NTNU. With over 25 years in the military, his work focuses on tactical communication systems, defensive cyber operations, and operational security. His research emphasizes cyber defence, reverse engineering, malware analysis, side-channel attacks, and machine learning applications. Education: PhD in Information Security, Gjøvik University College (HiG) MSc in Computer Science, NTNU Research Interests: Geir Olav's work bridges theoretical cybersecurity research and practical military applications. He explores innovative methods for hardware reverse engineering, malware detection/classification using low-level features, and forensic acquisition techniques. His contributions include analyzing USB power delivery vulnerabilities, NTFS cluster allocation behavior, and secure chip exploitation for digital forensics. Teaching: Courses include IIKG6500/IMT4213 Cyber-taktikk, IMT4214 Cyber-etterretning, IIKG6501 Cyber Intelligence, and IMT4116 Malware Analysis & Reversing. Labs & Teams: Heads the NTNU Malware Lab and leads the cyber defence research group at CCIS, collaborating on projects like the Digital Forensic Acquisition Kill Chain and hardware security vulnerability assessments.

• Embedded Systems
• Digital Signal Processing
• Multimedia Systems
• +۵ مورد دیگر

Per Gunnar Kjeldsberg is a Professor at the Department of Electronic Systems, Norwegian University of Science and Technology (NTNU), and currently serves as acting head of the institute. His research focuses on embedded heterogeneous multi-processor systems , particularly in multimedia and digital signal processing applications . He has led and participated in numerous national and international projects, including EU Horizon 2020 initiatives like READEX (as work package leader) and Tulipp (as principal researcher), and supervises the MSCA-IF project Palmera . Kjeldsberg is a Senior Member of IEEE and part of the European Network of Excellence HiPEAC . Education : Sivilingeniør (MSc) in Electrical Engineering (1992), PhD (2001) from Norwegian Institute of Technology (NTH)/NTNU His work spans energy-efficient computing , radiation-hardened memory design for space applications, and dynamic hardware management . Publications include co-authoring three books and over 150 peer-reviewed articles in journals and conferences. He leads the Circuit and Radio Systems group and drives a strategic NTNU initiative on Energy Efficient Computing Systems . Kjeldsberg has held visiting researcher roles at imec (Belgium), University of California, Irvine, imec Netherlands (Holst Centre), and University of New South Wales (Australia). Scientific Awards : Senior Member of IEEE Mikroelektronikkprisen (2006–2015)

• Cyber-Physical Systems
• Distributed Systems
• Internet of Things (IoT)
• +۷ مورد دیگر

Loïc Guégan is an Associate Professor in the Department of Informatics at UiT The Arctic University of Norway, affiliated with the Faculty of Science and Technology. His work is centered on energy-efficient cyber-physical systems and distributed computing, particularly in extreme and constrained environments such as the Arctic. His research focuses on cyber-physical systems (CPS) , distributed data dissemination , IoT and edge computing , and energy-efficient protocols . He actively contributes to the development of the Distributed Arctic Observatory (DAO) project and has designed tools like the ESDS simulator for evaluating distributed systems in challenging conditions. His technical work includes power monitoring using single-board computers and the design of the LoRaLitE protocol for low-energy wireless communication. The recent publications highlight a consistent trend in data dissemination strategies , simulation frameworks , and energy optimization for IoT and edge systems deployed in remote, resource-limited settings. These studies often leverage real-world Arctic deployments and epidemic-style algorithms to ensure robustness and scalability. Loïc is a member of the Cyber Physical Systems (CPS) research group and contributes to projects including The IoT-to-Extreme-Edge Infrastructure and Sustainable Distributed Systems for Sustainable Research and Education . He teaches courses such as Parallel Programming and Operating Systems . His research is supported through institutional and project-based funding, though specific grants are not detailed in the text.

• 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.

• High-performance Computing
• Energy-efficient Computing
• Machine Learning
• +۳ مورد دیگر

Dr. Ngoc Nha Vi Tran is an Associate Professor of Computer Science at UiT The Arctic University of Norway. She holds a PhD from UiT and was a visiting scholar at Rutgers University, USA. Her research focuses on high-performance and energy-efficient computing, machine learning, and bioinformatics. She is a member of the NORA.startup Steering Group and leads the Arctic Green Computing Group. Education: PhD in Computer Science (UiT), M.Sc. in Software Engineering via Erasmus Mundus (Blekinge Institute of Technology, Sweden & Technical University of Kaiserslautern, Germany). Research interests include energy-efficient algorithms, bioinformatics tools (e.g., vCOMBAT), and applications of machine learning in healthcare and robotics. She teaches courses such as INF-2200 Computer Architecture, INF-2900 Software Engineering, and INF-2202 Concurrent Programming. Her work spans computational models for antibiotic target-binding, runtime energy optimization (REOH framework), and power models for embedded systems (RTHpower/ICE). She contributed to the EXCESS project on energy-efficient computing systems. Labs/Teams: Arctic Green Computing Group, EXCESS consortium.

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

Mostafa Bakhoday Paskyabiمشاهده پروفایل

دانشیار

• Offshore Wind Energy
• Environmental Impacts of Offshore Wind Turbines
• Wind-Wave-Turbulence Interaction
• +۷ مورد دیگر

Mostafa Bakhoday Paskyabi is an Associate Professor at the Geophysical Institute , University of Bergen. His research focuses on offshore wind energy , environmental impacts of turbines , wind-wave-turbulence interaction , and climate change effects on wind parks . He employs Large Eddy Simulation (LES) and data assimilation for digital twin development. Teaching: Course responsible for ENERGI322 and ENERGI101; lecturer for ENERGI321 and ENERGI360. Supervision: Advises PhD candidates like Maria Krutova, Xu Ning, and Øystein Husevåg Døskeland, alongside master’s students including Fahim Masud Ahmed and Tord Nylan Malmei. His research explores physical oceanography (ocean mixing, Lagrangian particle tracking), air-sea interaction , and reduced-order modeling for offshore energy systems. Recent work examines swell wave impacts on turbulence and LiDAR-based data assimilation for transient event forecasting. Projects include LESWIND , WindSys , HIPERWIND , and Wind3D , addressing offshore wind design, ecosystem impacts, and climate operability. Collaborations span institutions like NTNU, NORCE, and IMR.

Pardhasaradhi Bethiمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Deep Learning
• Signal Processing
• +۷ مورد دیگر

Pardhasaradhi Bethi is a Research Fellow at the Department of Information and Communication Technology , University of Agder , specializing in lightweight deep learning models for edge computing and radar signal processing. Focus areas include object classification, sound recognition, and drone surveillance Collaborates with colleagues like Linga Reddy Cenkeramaddi and Srihari Pathipati Research Interests encompass edge AI , radar-communication convergence , and real-time IoT integration . His work emphasizes optimizing neural networks for low-power devices and improving tracking frameworks. Publication Trends show a strong focus on automotive radar , drone detection , and human activity analysis using deep learning techniques.

Hoai Phuong Haمشاهده پروفایل

استاد

• Green and energy-efficient computing
• Parallel and distributed computing systems
• Cyber-physical systems
• +۳ مورد دیگر

Professor Hoai Phuong Ha is affiliated with UiT The Arctic University of Norway's Department of Computer Science. A leading expert in green computing and cyber-physical systems, they contribute to Arctic research through the Distributed Arctic Observatory (DAO) and Arctic Green Computing (AGC) group. Founded ARC (Arctic Center for Sustainable Energy) PI in EU FP7 EXCESS and H2020 TAILOR projects WP-leader in EEA POLNOR HAPADS and RCN PREAPP projects Their research focuses on energy-efficient computing, including IoT systems, edge computing, and parallel algorithms. Recent work addresses wireless charging trajectories (eU2U, 2025), smart grid networks (GridWatch, 2024), and pollution monitoring (2024). Publications span cyber-physical observatories, sensor calibration, and distributed systems optimization. Key trends in their 15 most recent articles (2017-2025) include: energy-aware data structures, Arctic-adapted IoT deployments, and sustainable computing methods. Collaborations span EU and Norwegian grants with applications in smart grids, environmental sensing, and high-performance computing. Co-founder of Arctic Center for Sustainable Energy (2017) Active in EEA POLNOR (2019-2023) and RCN eX3 infrastructure project Their lab (Realfagbygget A237) develops systems for Arctic tundra monitoring, including UAV-powered networks and energy-harvesting protocols. Students include researchers from multiple international collaborations.

• Cryptography
• Blockchain Technology
• Network Security
• +۷ مورد دیگر

Danilo Gligoroski is a Professor at the Department of Information Security and Communication Technology at NTNU. His research focuses on cryptography, blockchain technology, network security, and 5G systems. He has collaborated extensively on projects involving decentralized ledgers, cybersecurity in healthcare, and hardware implementations of cryptographic algorithms. Key contributions include work on blockchain-based trust systems, secure network slicing, and privacy-preserving protocols. Affiliations: NTNU, Department of Information Security and Communication Technology Primary Research Areas: Cryptography, Blockchain, 5G Networks, Cybersecurity Notable Projects: GRAND Parallel Decoding Framework, GDPR-compliant healthcare blockchain Research interests span cryptographic protocol design, distributed ledger technologies, and their applications in healthcare, telecommunications, and IoT. His work often addresses scalability, privacy, and compliance challenges in decentralized systems. Publications highlight trends in blockchain consensus mechanisms, cryptographic hardware optimization, and network security for next-gen communication systems. Collaborations with industry and academic partners emphasize practical implementations and real-world use cases. Advising and grants include supervision of interdisciplinary projects and contributions to EU-funded cybersecurity initiatives. Active in open-source software development for network slicing and blockchain frameworks.

• Computational Neuroscience
• Mathematical Neuroscience
• Brain Physics
• +۱۲ مورد دیگر

Gaute Einevoll is a Professor in the Department of Physics at the Norwegian University of Life Sciences (NMBU), Faculty of Science and Technology. His academic work bridges the disciplines of physics and neuroscience, with a strong focus on computational and mathematical modeling of brain function. Position: Professor of Physics Institution: Norwegian University of Life Sciences (NMBU) Department: Department of Physics Research Focus: Brain Physics, Computational Neuroscience His research interests lie at the intersection of physics and neuroscience, particularly in understanding the biophysical mechanisms underlying neural signals such as local field potentials (LFPs), EEG, and spike trains. He develops and applies mathematical models to interpret experimental data from multielectrode arrays and laminar recordings. His work includes modeling cortical circuits, thalamocortical networks, and the transition from grid cells to place cells in spatial navigation. He also investigates the biophysical basis of signal propagation and filtering in neural tissue. The 15 most recent publications reflect a consistent focus on computational modeling of neural activity, with strong emphasis on biophysical realism, data analysis methods, and tool development. Articles span topics from single-neuron contributions to EEG, astrocytic ion dynamics, and large-scale neural recordings. Keywords across these works include Computational Neuroscience, Biophysics, Neural Modeling, and Electrophysiology, with subfields covering LFPs, spike-train analysis, cortical circuits, and network dynamics. A recurring theme is the development of analytical and computational tools to bridge experimental data with theoretical understanding. No scientific awards are mentioned in the provided text. Gaute Einevoll has supervised research and taught courses such as FYS388/488 Computational Neuroscience and FYS102 Thermal Physics and Electromagnetism. He has contributed to major collaborative efforts like the Human Brain Project. While specific grants are not listed, his extensive publication record in high-impact journals suggests sustained research funding. He has also authored educational materials, including a textbook on physics and an edited volume on natural sciences. He is associated with research groups focused on computational neuroscience and brain physics. He has developed the LFPy tool for simulating extracellular potentials, indicating leadership in neuroinformatics tool development. His team likely involves interdisciplinary collaboration between physicists, neuroscientists, and computational biologists working on modeling neural systems.

Øyvind Ytrehusمشاهده پروفایل

استاد

• Coding Theory
• Error-Correcting Codes
• Information Theory
• +۷ مورد دیگر

Øyvind Ytrehus is a Professor at the Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Bergen (UiB), Norway. He is actively engaged in research and academic supervision, with a focus on coding theory and its applications in communication systems. Research Interests: His primary research areas include Coding Theory , Error-Correcting Codes , Information Theory , Network Coding , Cryptography , and RFID Communication . His work bridges theoretical foundations with practical implementations in wireless and networked systems. The recent publications (2024–2008) reflect a consistent trajectory in coding for communication security, RFID systems, and iterative decoding. Key trends include the use of formally unimodular lattices for secrecy gain, LDPC and turbo codes for erasure channels, and network coding for multicast and delay optimization. His work frequently intersects with physical-layer security and energy-efficient communication. Scientific Contributions: Co-edited special issues on coding theory and applications. Authored foundational work on convolutional codes, stopping sets, and generalized Hamming weights. Contributed to RFID and inductively coupled channel modeling. Advising and Grants: He has supervised several PhD candidates, including Bjørn Møller Greve, Christian W. Otterstad, and Mohsen Toorani. While specific grants are not listed, his extensive publication record and editorial roles suggest active grant involvement in coding and communication research. Labs and Teams: While no specific lab name is mentioned, his collaborations with researchers at Simula UiB, University of Valladolid, and Lancaster University indicate participation in interdisciplinary research networks focused on coding and communication systems.