Find Academic Supervisors

• Ancient Greek Religion
• Contemporary Paganism
• Reception Studies
• +3 more

Stian Sundell Torjussen is an Associate Professor at the University of Innlandet , affiliated with the Department of Social Sciences, Religion and Ethics within the Faculty of Education . His primary research interests focus on ancient Greek religion, contemporary Paganism, reception studies, and the role of religion in popular culture. He actively contributes to teacher education programs in religion, philosophy, and ethics. Dr. Torjussen leads the Research Group Formation, Values and Cultural Heritage and serves as the Subject Manager for "Classical religion" at the Great Norwegian Encyclopedia . His work bridges classical religious studies with modern cultural phenomena, such as analyzing ancient myths in video games (e.g., Dungeons & Dragons: Mythic Odysseys of Theros ) and exploring contemporary Hellenic polytheistic practices in North America. His publications span over 15 years, addressing topics like Orphic gold tablets, Etruscan tomb iconography, and the reception of classical motifs in modern media. Recent work includes studies on teacher education ethics and transnational research collaboration through the TRANSPEER project. Though no formal awards are listed, his extensive scholarly output underscores his academic influence in religious and classical studies. Dr. Torjussen’s advising and grants focus on fostering interdisciplinary research and pedagogical innovation. He collaborates internationally, evident in projects like EMERGE (a European university alliance). His academic presence extends to platforms like Cristin , Academia.edu , and ResearchGate .

Luca FredianiView profile

Professor

• Theoretical and Computational Chemistry
• Density Functional Theory (DFT)
• Multiwavelet Methods
• +4 more

Luca Frediani is a Professor in Theoretical and Computational Chemistry at the Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway. His research focuses on advanced quantum chemistry methods, including density functional theory, multiwavelet basis sets, and solvation modeling. He actively develops computational tools like MRChem and VAMPyR for molecular electronic structure calculations. Current affiliation: UiT The Arctic University of Norway Research group: Theoretical and Computational Chemistry Teaching: KJE-2001 Theoretical Chemistry and Spectroscopy His work spans relativistic quantum chemistry, numerical methods for response properties, and benchmarking of basis set limits. Publications emphasize eliminating basis set errors, multiwavelet applications, and polarizable continuum models for solvation. He collaborates extensively on software development for quantum chemistry. Recent articles highlight multiwavelet-based DFT at the basis set limit, noise-tolerant force calculations, and relativistic effects in electronic structure. Sub-fields include scalar relativity, cavity-free solvation, and metal-ligand interaction accuracy.

• Cyber-Physical Systems
• Distributed Systems
• Internet of Things (IoT)
• +7 more

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.

Peter Scharff SmithView profile

Professor

• Penal Reform
• Human Rights in Criminal Justice
• War Crimes and Holocaust Studies
• +5 more

Peter Scharff Smith is a Professor at the Department of Criminology and Sociology of Law , University of Oslo. His career spans interdisciplinary research in penology, sociology of law, human rights , and war crimes , with a focus on solitary confinement, prisoner-family dynamics, and Holocaust-related legal practices. Current affiliation: University of Oslo Past affiliations: University of Copenhagen, Cambridge University, New York University Research interests include: Punishment & Human Rights : Solitary confinement effects, women in prison, children of prisoners Legal Consciousness : Public justice sentiments, marginalized groups' legal experiences War Crimes : Waffen-SS legal frameworks, techniques of Othering Key article trends reveal sustained focus on prison reform , scandals in isolation , and historical parallels between Holocaust studies and incarceration . His work bridges empirical research and advocacy, particularly for international soft-law prison standards . Scientific awards : Danish Labour History Award (1994) Carlsberg Clare Hall Fellowship (2003) Methodological approach combines historical analysis, comparative Nordic studies, and practical reform projects in Danish and Norwegian corrections systems.

Giuliano D'AmicoView profile

Professor

• Nordic Literature
• Ibsen Studies
• Reception Studies
• +6 more

Giuliano D'Amico is a Professor of Nordic Literature and Center Director at the University of Oslo . He has held academic positions at NTNU and Volda University College between 2012-2023, with earlier roles as Lecturer at University of Milan and University of Turin . His career includes a Ph.D. in General Literature (2008-2010) and research stays at Ca' Foscari University , University of Strasbourg , and others. Education: Ph.D. in General Literature, University of Oslo (2008-2010) Research stays at University of Turin (2008-2010), University of Palermo (2010), and other institutions His research focuses on Nordic literature (1800-present) , particularly Henrik Ibsen , examined through international reception studies , translation analysis , and copyright history . He has pioneered the integration of Western esotericism as a literary analytical category, with 2020 monograph on Nordic retrogardism and Håkan Sandell's poetry. Current projects include a book on spectrality in Ibsen's plays . His publications span 15+ years , covering Ibsen's Peer Gynt through occult and conspiracy lens, Hamsun's forgery themes, and comparative analysis of Nordic authors' reception in Italy, France, Germany, and Scotland . Articles appear in European Journal of Scandinavian Studies , Correspondences , and Cambridge University Press publications. As academic leader: Head of Center for Ibsen Studies (2023-2027) Co-editor of Ibsen Studies journal since 2018 Secretary of International Ibsen Committee (2018-2020, 2023-2027) Teaching coordinator for Center for Ibsen studies (2018-2020) He teaches Ibsen Studies (master's program) with courses on text-performance analysis, modern drama, and practical Ibsen studies. Research groups: Book history and reception group Founding member of ESOSTETICS (Esotericism and Aesthetics in Nordic countries) Projects: Co-investigator in Made Abroad: Producing Norwegian World Literature in a Time of Rupture, 1900-50 (National Library of Norway) Participant in NORNE (Norwegian Romantic Nationalisms research)

• Polar Science
• Arctic Marine Ecology
• Fisheries Management
• +3 more

Ole Arve Misund serves as a Professor at the Norwegian Fisheries College within UiT The Arctic University of Norway, Tromsø. His research spans polar science, Arctic marine ecology, fisheries management, and international relations in polar regions, with particular focus on Norway-Russia scientific cooperation dynamics following geopolitical shifts in 2022. His research interests center on climate change impacts on Arctic marine ecosystems, acoustic monitoring of marine organisms, and the geopolitical dimensions of polar research. Recent work examines boreal species migration into the Central Arctic Ocean, machine learning applications for backscatter analysis, and management frameworks for the Central Arctic Ocean. Analysis of his recent publications reveals strong interdisciplinary trends, integrating marine ecology with political science through studies of Russian-Norwegian scientific collaboration under sanctions, illegal fishing enforcement, and policy-relevant polar research. His work consistently bridges academic research with practical fisheries management and geopolitical considerations. Misund actively engages in science communication through Norwegian media outlets like Nordlys and Fiskeribladet, addressing topics from climate policy contradictions to Antarctic hydrological changes. His expeditionary work includes North Pole 2022 aboard the "Kronprins Haakon" research vessel. Professional activities demonstrate significant leadership in polar research infrastructure development and international scientific collaboration, particularly through the Norwegian Polar Institute where he contributes to strategic planning and policy advice. His work emphasizes evidence-based approaches to Arctic governance amid evolving geopolitical landscapes.

• High-performance Computing
• Energy-efficient Computing
• Machine Learning
• +3 more

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.

• Optimization methods
• Metaheuristics
• Heuristics
• +12 more

Mina Mirhosseini is a Research Fellow at the Faculty of Logistics, Molde University College, Norway. She holds a PhD in Computer Science from Shahid Beheshti University of Tehran, Iran, and has prior academic experience as a faculty member and lecturer in Iran and as a remote teaching assistant at the University of Hertfordshire, UK. Her primary research interests include Optimization Methods, Metaheuristics, Heuristics, Linear Integer Programming, Parallel Processing, Machine Learning, Artificial Intelligence, and Logistics. She has made significant contributions to solving complex computational problems such as the n-similarity problem and Mixed Integer Linear Programming (MILP) models using hybrid and parallel algorithms, particularly in the context of high-level synthesis and wireless sensor networks. The analysis of her recent publications reveals a strong focus on developing and applying advanced optimization techniques, especially quantum-inspired gravitational search algorithms and parallel genetic algorithms, to real-world engineering and computational challenges. Her work consistently emphasizes performance improvement, scalability, and load balancing in distributed and heterogeneous computing environments. Mina Mirhosseini has an extensive publication record in high-impact journals such as IEEE Transactions on Parallel and Distributed Systems, Journal of Parallel and Distributed Computing, Journal of Supercomputing, and Computers and Electrical Engineering. Her research has been published across a range of venues, reflecting interdisciplinary work at the intersection of computer science, electrical engineering, and applied optimization. She has actively contributed to the academic community through roles such as program committee member and executive committee member for conferences on fuzzy systems, swarm intelligence, and evolutionary computation. Her academic journey includes teaching and research roles in Iran, demonstrating a sustained commitment to higher education and scientific inquiry. Mina Mirhosseini is part of the research group focused on Planning, Optimization and Decision Support at Molde University College. Her current work continues to advance the state-of-the-art in parallel and metaheuristic optimization methods, with applications in logistics, synthesis, and sensor network design.

• Programming Theory
• Algebraic Methods in Software Development
• Programming Language Design
• +12 more

Magne Haveraaen is a Professor in the Department of Informatics at the University of Bergen, where he leads the Bergen Language Design Laboratory (BLDL). He is actively engaged in research on programming theory, formal methods, language design, and high-integrity systems. His work centers on algebraic specifications, generic programming, domain engineering, and the design of the Magnolia programming language. He has been a long-standing instructor of key courses such as INF220 (Program Specification) and INF222 (Programming Languages), and contributes to national and international academic forums. University: University of Bergen School: Faculty of Mathematics and Natural Sciences Department: Department of Informatics Academic Rank: Professor Email: magne.haveraaen@uib.no His research interests include programming language design, formal specifications, generic and mouldable programming, multicore and GPU computing, and algebraic methods in software development. He emphasizes correctness, reuse, and high-integrity software through theoretical and practical innovations. He has contributed extensively to the literature on algebraic reasoning, array programming, and domain-specific abstractions. The recent publications highlight a consistent focus on algebraic semantics, language design (especially Magnolia), array programming, and formal verification. Themes across these works include correctness by design, specification-driven development, and adapting programming models for modern architectures. His involvement in workshops like ARRAY, WGP, and CALCO underscores his leadership in programming language theory. No scientific awards are listed in the provided texts. He advises students and welcomes collaboration in programming theory, language design, and formal methods. He has led funded projects such as MoSIS and SHIP and is involved in the High Integrity Systems Forum. He organizes and participates in key conferences including NWPT, GPCE, and SCAM. He leads the Bergen Language Design Laboratory (BLDL), which focuses on experimental language design, and contributes to the SAGA initiative on scientific computing with algebraic abstractions. His work integrates theory with practical tooling and language implementation.

Irina GribkovskaiaView profile

Professor

• Offshore Logistics
• Vehicle Routing and Scheduling
• Mathematical Modelling and Optimization
• +4 more

Irina Gribkovskaia is a Professor at the Faculty of Logistics, Molde University College (Norway). Her research focuses on offshore energy logistics, vehicle routing and scheduling, mathematical optimization for logistics planning, and decision support systems under uncertainty. She leads the Energy Logistics Research Group (EneLog) and has collaborated on projects such as the Norwegian-Russian Arctic Logistics initiative. Her work addresses challenges in offshore oil/gas and renewable energy sectors, including supply vessel planning, helicopter transportation safety, and emissions reduction. Notable contributions include robust scheduling methods, fleet sizing strategies, and simulation-based optimization tools. Key projects include analyzing transit shipping via the Northeast Passage and tactical helicopter planning for offshore personnel. She has authored over 50 peer-reviewed articles in journals like Transportation Research and Omega , focusing on logistics optimization under uncertainty. Irina is a core member of multidisciplinary programs, including a Norwegian-Belarusian MSc in Logistics Analytics. Her research integrates operations research with real-world maritime and energy logistics systems.

Hoai Phuong HaView profile

Professor

• Green and energy-efficient computing
• Parallel and distributed computing systems
• Cyber-physical systems
• +3 more

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.

• Applied Mathematics
• Numerical Analysis
• Parallel Computing
• +7 more

André Brodtkorb is a Professor and Head of the Department of Information Technology at Oslo Metropolitan University. His research spans applied mathematics, numerical analysis, and computational science, focusing on physics simulations and GPU computing. He advocates for open and reproducible research and is actively involved in education and societal engagement through the Academy of Young Researchers (2024-2028). Research Interests: His work integrates applied mathematics and computer science to develop high-performance simulations for environmental phenomena, including ocean currents, volcanic ash dispersion, and coastal flooding. He specializes in GPU-accelerated parallel computing, finite-volume methods, and Python-based scientific programming. Publication Trends: Recent articles highlight advancements in GPU computing efficiency, ocean modeling, and inverse ash transport modeling for volcanic plume forecasting. His research bridges computational methods with real-world environmental challenges. Scientific Awards: Member of the Academy of Young Researchers (2024-2028) Contact Information: Office: Pilestredet 35, 0166 Oslo Phone: +47 456 19 070 (Mobile), +47 672 35 924 (Office) Email: andre.brodtkorb@oslomet.no

• Numerical Solution of Partial Differential Equations
• Spectral Element Methods
• Reduced Basis Methods
• +3 more

Einar Malvin Rønquist is a Professor and Head of the Department of Mathematical Sciences at NTNU since August 2013. He holds a MSc from NTNU (1980) and a PhD from MIT (1988). His research focuses on numerical solutions of partial differential equations, spectral element methods, reduced basis methods, and computational fluid dynamics. He has been a leader in several research initiatives, including the Computational Science and Visualization program at NTNU (2003–2011). Rønquist is a member of prestigious academies: NTVA (since 2005) and DNKVS (since 2010). He has supervised 8 PhD students and 25 MSc students. His work spans computational science, with notable contributions to parametric modeling, parallel computing, and fluid dynamics simulation. His administrative roles include Vice President of R&D at Nektonics, Inc. (1991–1999) and Deputy Head of NTNU’s Department of Mathematical Sciences (Fall 2012). His publications highlight advancements in numerical methods for PDEs, including spectral element techniques, reduced basis approaches, and high-order approximations for complex geometries.

• Smart Wireless Systems
• Internet of Things (IoT)
• Information Security
• +8 more

Mohammad Derawi is a Professor in the Department of Electronic Systems at the Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU), Gjøvik campus. He leads the Smart Wireless Systems (SWS) research group and serves as the scientific leader of the IoT Lab at NTNU Gjøvik. Educational Background: PhD in Information Security from NISLab (Norway) and CASED (Germany) BSc and MSc in Informatics from DTU (Denmark) His research interests span smart wireless systems, Internet of Things (IoT), information security with a focus on biometric authentication, digital electronics, applied machine learning for activity recognition, and e-learning technologies. His work integrates cybersecurity, embedded systems, and data science to develop secure and intelligent IoT solutions for real-world applications. The recent publications highlight a strong trend in mmWave-based sensing for unmanned aerial systems, RF fingerprinting for secure identification, IoT security frameworks, and machine learning applications in education and human resource analytics. His research bridges theoretical innovation with practical implementation, particularly in smart cities, healthcare, and transportation. Scientific Awards and Recognition: Invitation to the Crown Prince and Princess's 50th birthday celebration, 2023 Study Quality Award, NTNU, 2017 Norway’s Youngest Professor Award, 2016 Denmark’s youngest M.Sc. engineering award, 2009 IEEE Commendation for Young Professionals Volunteer, 2011 Multiple best paper awards from IEEE, ACM, and Springer Mohammad Derawi has been involved in several funded research and development projects, including IoT Safetraffic (RFF Inland), Ambulance Drone (NTNU Vice-Rector), Wireless ECG (Innovation Norway), biometric handgun security (RFF Innlandet), and the EU Framework 7 TURBINE project. He mentors students and collaborates with international researchers, contributing significantly to both academic and applied domains. His leadership in the SWS group and IoT Lab fosters innovation in wireless and secure embedded systems. He is actively engaged in laboratory and team-based research, particularly through the Smart Wireless Systems group and the IoT Lab, focusing on developing secure, intelligent, and scalable solutions for next-generation wireless applications.

Fredrik ManneView profile

Professor

• Parallel Computing
• Distributed Computing
• Graph Algorithms
• +3 more

Fredrik Manne is a Professor at the Department of Informatics, University of Bergen, Norway. His work focuses on parallel and distributed computing, particularly in combinatorial scientific computing and self-stabilizing algorithms. He has contributed extensively to graph algorithms, including matching, coloring, and clustering, with applications in high-performance computing, numerical optimization, and wireless networks. His research involves designing algorithms for parallel architectures, including multi-core and GPU-based systems. He has co-authored numerous publications on topics such as spanning forests, vertex cover heuristics, and b-matching. His work often integrates theoretical and applied approaches, addressing challenges in sparse matrix computations and wireless mesh network communication. The recent articles highlight his exploration of graph neural networks for parallel coloring, efficient multithreaded matching algorithms, and GPU-accelerated clustering methods. These studies emphasize scalability, optimization, and real-world applications in computational science.