جست‌وجوی استاد و پژوهشگر

• Bigdata Cybernetics
• Hybrid Analytics / Modeling
• Artificial Intelligence and Machine Learning
• +۱۰ مورد دیگر

Professor Adil Rasheed is affiliated with the Department of Engineering Cybernetics at the Faculty of Information Technology and Electrical Engineering , Norwegian University of Science and Technology (NTNU). His work focuses on integrating data-driven methods with physics-based modeling to create reliable hybrid systems for high-stakes applications. Research Interests : Bigdata Cybernetics, Hybrid Analytics / Modeling, Artificial Intelligence, Reduced Order Modeling, Computational Fluid Dynamics, Wind Energy, Autonomous Vessels, and Safe Reinforcement Learning. Digital Twin Applications : Professor Rasheed leads projects in Digital Twin technology for wind energy and smart greenhouses. His work includes autonomous marine navigation, federated learning for Industrial IoT, and predictive maintenance in offshore wind turbines using integrated data-driven models. Collaborative Efforts : He collaborates with industry partners on digital twin syncing for autonomous vessels, thermal zoning algorithms for building control, and anomaly detection in multivariate time series. His publications highlight the use of transformers, federated transfer learning, and corrective source terms in hybrid modeling.

• 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)

• Scanning Transmission Electron Microscopy (4D-STEM)
• Open Source Scientific Software Development
• Big Data Processing in Electron Microscopy
• +۴ مورد دیگر

Magnus Nord is an Associate Professor in the Department of Physics, Faculty of Natural Sciences at Norwegian University of Science and Technology (NTNU). His research focuses on advanced electron microscopy techniques and computational tools for materials characterization. Research Interests : Scanning Transmission Electron Microscopy (4D-STEM), Open Source Scientific Software Development (Python), Big Data Processing, Magnetic/Electric Field Imaging, Structural Characterization using Higher Order Laue Zones. Publications span cutting-edge applications in functional materials, nanomagnets, and perovskite thin films, with emphasis on machine learning and precession-enhanced imaging. Key keywords include Materials Science , Electron Microscopy , and Computational Imaging . Software Development : Lead developer of Atomap and pyxem , contributing to HyperSpy and merlin_interface for electron microscopy data analysis. Current Research Funding : InCoMa (Research Council of Norway) IMPRESS (Horizon EU Program)

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.

Colin Harry LaMontمشاهده پروفایل

پژوهشگر ارشد

• Precision Immunotherapy
• Spatial Biology
• Bioinformatics
• +۲ مورد دیگر

Colin Harry LaMont serves as a Postdoctoral Fellow at the PRIMA - Precision Immunotherapy Alliance within the Faculty of Medicine at the University of Oslo, conducting research at the Radium Hospital facility (Ullernchausséen 70, Building K, Room K02.059). His work bridges computational methodologies with cutting-edge immunotherapy applications. His research centers on developing integrated computational pipelines for spatial biology data analysis, with a focus on advancing precision immunotherapy through bioinformatics innovation. By leveraging spatial transcriptomics and single-cell analysis techniques, he addresses critical challenges in cancer treatment personalization and immune response mapping, contributing to Oslo's leadership in precision medicine. His 2024 publication demonstrates significant progress in creating flexible analytical frameworks for complex spatial biology datasets, establishing foundational tools for the immunotherapy research community. This work exemplifies PRIMA's mission to translate computational advances into clinical immunotherapy applications. Affiliated with the University of Oslo's medical research ecosystem, Dr. LaMont operates within the PRIMA center's collaborative framework at Radium Hospital, where interdisciplinary teams accelerate immunotherapy development through data-driven approaches.

Runar Hilleren Lieمشاهده پروفایل

پژوهشگر ارشد

• International Investment Law
• Computational Legal Studies
• International Economic Law
• +۷ مورد دیگر

Runar Hilleren Lie is a Postdoctoral Research Fellow at the Department of Public and International Law, Faculty of Law, University of Oslo. He is actively engaged in interdisciplinary research at the intersection of law, technology, and international relations, contributing to major projects such as COPIID, NoRDASIL, and CLEANUP. His research interests span International Investment Law , Computational Legal Studies , International Economic Law , Energy Law , and Legal Technology . He employs data-driven and computational methodologies to analyze legal texts, arbitrator behavior, treaty development, and institutional dynamics in international dispute settlement. The most recent publications reveal a strong trend toward empirical and computational analysis of international investment law, particularly focusing on influence networks, authorship prediction, compliance politics, and the evolving role of legal actors in arbitration. His work bridges traditional legal scholarship with cutting-edge data science techniques. He teaches JUS5080 – Programming for Lawyers and JUS5671 – Legal Technology: Artificial Intelligence and Law , reflecting his commitment to integrating technological literacy into legal education. Email: r.h.lie@jus.uio.no, rhlie@jus.uio.no Phone: +47 22859431 Visiting Address: Domus Juridica, 7th floor, Kristian Augusts gate 17, 0164 Oslo Postal Address: Postboks 6706 St. Olavs plass, 0130 Oslo He is affiliated with the Law and Technology (JOT) research group and the Research Group on International Law . His current research projects include: COPIID : Compliance Politics and International Investment Disputes NoRDASIL : Advancing Data Science in Migration Law (NORDFORSK) CLEANUP : Machine Learning for the Anonymisation of Unstructured Personal Data (Research Council of Norway, 2020–2023)

Fedor Fominمشاهده پروفایل

استاد

• Theoretical Computer Science
• Graph Algorithms
• Parameterized Complexity
• +۳ مورد دیگر

Fedor Fomin is a Professor in the Department of Informatics at the University of Bergen. His research focuses on Theoretical Computer Science, including Graph Algorithms, Parameterized Complexity, Combinatorics, and Combinatorial Games. He is affiliated with the Norwegian Academy of Science and Letters, the Norwegian Academy of Technological Sciences, and the Academia Europaea, and holds fellowships from ACM and EATCS. His work has been recognized with the EATCS Nerode Prize in 2015 and 2017. Dr. Fomin has authored influential books such as Kernelization: Theory of Parameterized Preprocessing and Parameterized Algorithms , which are foundational in the field of algorithm design. His recent publications explore cutting-edge topics in parameterized complexity, graph theory, and distributed computing, with contributions to approximation algorithms, kernelization, and combinatorial optimization. His awards and honors reflect his significant impact on theoretical computer science. Fomin has been awarded an ERC Advanced Grant and has mentored numerous researchers, contributing to the advancement of algorithmic techniques and their applications.

Pinar Heggernesمشاهده پروفایل

استاد

• Algorithms
• Graph Theory
• Combinatorics
• +۳ مورد دیگر

Pinar Heggernes is a Professor at the Department of Informatics at the University of Bergen , specializing in algorithms and graph theory . Her research focuses on solving NP-hard graph problems through polynomial-time and fixed parameter tractable algorithms , particularly on chordal , split , and outerplanar graphs . She served as the elected deputy rector of the University of Bergen (2021–2025) with responsibility for education and digital knowledge, and previously as head of the Department of Informatics until 2021. Her career spans leadership in externally funded projects, editorial roles in international journals, and active participation in national research policy, including co-founding the Norwegian Artificial Intelligence Research Consortium (NORA). Education: PhD in Informatics from the University of Bergen. Research Interests: Algorithms for graph classes, computational complexity, parameterized algorithms, and combinatorial optimization. Collaborations: Extensive partnerships with academia, businesses, and public administration, including advisory roles in the Bergen Chamber of Commerce and the Norwegian Cognitive Center . Grants: Project leader for four Research Council of Norway FRIPRO grants (CLASSIS, SCOPE, MIST, and earlier projects) and participant in EU, Trond Mohn Foundation, and National Security Authority grants. Students: Supervised Paloma T. Lima (PhD, 2019) and co-supervised numerous advisees through collaborative projects. Labs/Teams: Coordinated interdisciplinary ICT research and education initiatives at UiB, with international collaborations in the USA, France, and Turkey.

• 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.

• Computational Physics
• Density Functional Theory (DFT)
• Atomistic Simulations
• +۹ مورد دیگر

Jaakko Akola is a Professor in the Department of Physics at the Norwegian University of Science and Technology (NTNU). His research focuses on computational materials science, particularly density functional theory (DFT) and atomistic simulations of materials, nanoparticles, molecules, and interfaces. He leads significant projects such as "SIDI" (inoculation in cast iron), "Infinity-RETIS" (chemical rare events), and "AllDesign" (rational alloy design), alongside coordinating EU-funded initiatives like "CritCat" for catalyst development. The Materials Theory group under Akola employs DFT, molecular mechanics, and Monte Carlo methods to explore atomic-scale structures and functions in technological applications. Key research areas include platinum-free catalysts for hydrogen energy, amorphous semiconductors for memory devices, noble metal nanoparticles in biological environments, and alloy design for cast iron and aluminum. Recent work integrates machine learning to advance theory-driven material design, reducing reliance on experimental trial-and-error. Akola's publications highlight advancements in hydrogen evolution catalysis, phase-change memory materials, and alloy precipitation. His projects often involve interdisciplinary collaborations with experimental teams. He teaches Quantum Physics 1 (FY2045) and Computational Physics (TFY4235) at NTNU, reflecting his commitment to education alongside research.

Ajit Jhaمشاهده پروفایل

دانشیار

• Photonic sensing
• Robotics
• Machine Learning
• +۶ مورد دیگر

Ajit Jha is an Associate Professor at the Department of Engineering Sciences , University of Agder , Norway, with research expertise in photonic sensing, robotics, machine learning, and sensor fusion. His work bridges theoretical advancements with real-world applications in autonomous systems, industrial automation, and biomedical imaging. Research Areas: Photonic sensing, Robotics, Machine Learning, Computer Vision, Sensor Fusion, Mechatronics Recent Publications demonstrate innovative applications of deep learning to thermal imaging (gesture recognition), reinforcement learning for drone landing, and sensor fusion techniques for autonomous navigation. His interdisciplinary approach combines photonics, radar systems, and AI to solve complex engineering problems.

• Distributed Systems
• Cybersecurity
• Sports Technology
• +۷ مورد دیگر

Dag Johansen is a Professor in the Department of Informatics at UiT The Arctic University of Norway, Tromso campus. His work spans multiple research areas at the intersection of computer science, sports science, medicine, health technology, and nutrition science. He leads the interdisciplinary "Corpore Sano" research center and is actively involved in several research groups including the Cyber Security Group (CSG) and Crime Control and Security Law. Professor Johansen's research focuses on developing fundamental software solutions for secure and error-free data processing in heterogeneous distributed systems, ranging from lightweight "Internet of Things" devices and mobile phones to large-scale cloud solutions. His work particularly emphasizes applications in sports technology, edge computing, and compliance technology. His research interests include distributed systems, cybersecurity, sports technology, edge computing, data privacy, AI for sports analytics, multimedia forensics, and compliance technology. His recent publication trends show a strong focus on AI applications for sports video analysis, particularly in soccer and ice hockey, where his team has developed AI-based cropping systems for social media representations. He also has significant work in data privacy and GDPR compliance, especially regarding the "third country problem," as well as applications of AI in sustainable fishing practices. His 2024-2025 publications demonstrate continued work in self-healing microservices, lightweight encryption for video feeds, and virtual reality training environments. Professor Johansen is actively involved in mentoring students and research collaborators, as evidenced by his extensive publication record with numerous co-authors including doctoral students and postdoctoral researchers. His work has received funding through various research projects focused on data analytics, privacy technology, cybersecurity, and sports technology applications. He leads the interdisciplinary "Corpore Sano" center, which brings together researchers from computer science, sports science, medicine, health technology, and nutrition science. His work also involves collaboration with the "Njord" project focused on sustainable fishing through AI applications, and he's involved in developing the "Áika" distributed edge system for AI inference.

• Condensed Matter Physics
• Quantum Transport
• Superconductivity
• +۵ مورد دیگر

Asle Sudbø is a Professor and Center Director of the SFF QuSpin at the Norwegian University of Science and Technology (NTNU), Faculty of Natural Sciences, Department of Physics. He holds a PhD from Brown University (1990). His research focuses on quantum phenomena in condensed matter systems, including superconductivity, quantum criticality, topological materials, and strongly correlated systems. He has advised numerous PhD students and contributes to cutting-edge theoretical studies of low-dimensional systems and topological phases. His work integrates advanced computational methods and explores systems like graphene, topological insulators, and Bose-Einstein condensates. Education: PhD in Physics, Brown University, 1990 Research Interests: Condensed matter physics at quantum regime Quantum transport of spin/charge Topological superconductivity and phase transitions Unconventional superconductors (graphene, pnictides) Bose-Einstein condensates and superfluids Quantum critical phenomena and Monte-Carlo simulations Publications Trends: Recent work emphasizes topological effects in superconductors, magnon-mediated mechanisms, and quantum criticality in 2D systems. Key themes include breaking symmetry limits in superconductors and exploring topological signatures in magnetic heterostructures. Grants & Labs: Leads the QuSpin Center (SFF), focusing on quantum spin systems. Collaborates extensively on projects involving topological materials and low-temperature physics.

• 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.

Tor-Morten Grønliمشاهده پروفایل

استاد

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

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