Find Academic Supervisors

• Interaction between light and matter
• Quantum theory
• Climate modeling
• +5 more

Per Kristen Jakobsen is a Professor at the Department of Mathematics and Statistics , UiT The Arctic University of Norway. His work spans interdisciplinary research in nonlinear optics , quantum field theory , and climate modeling , with a focus on mathematical and computational approaches to complex systems. Teaches graduate courses in partial differential equations (Mat-3200), nonlinear waves (Mat-3202), and climate dynamics (Mat-3213). A member of the Complex Systems Modeling (CoSMo) research group, addressing phenomena from optical pulse propagation to Arctic sea ice loss. Recent research highlights include: Climate modeling predictions for Arctic summer sea ice loss (Environmental Research Letters, 2024). Boundary integral methods for nonlinear scattering and extreme nonlinear optics (Physical Review A, 2019–2020). Studies on gain media and superoscillatory functions in electromagnetic theory (Optical Review, 2021). His methodological expertise includes quantum resonant-state expansions , leaky-mode analysis , and stochastic entropy models . He is based at Realfagbygget A217, Tromso.

Anja Marie WestramView profile

Researcher

• Evolutionary Biology
• Population Genetics
• Genomics
• +5 more

Anja Marie Westram is a researcher at Nord University, specializing in evolutionary biology and population genetics. Her work focuses on hybrid zones, reproductive isolation, and the genomic basis of adaptive divergence. University : Nord University Academic Rank : Researcher Westram's research explores how chromosomal rearrangements and polymorphic inversions contribute to speciation. She has extensively studied the intertidal snail Littorina saxatilis to understand phenotypic divergence and reproductive isolation mechanisms. Her recent work includes demographic modeling of marine speciation, the role of chromosomal inversions in adaptive divergence, and hybridization dynamics in Darevskia lizards. Publications span topics from molecular ecology to theoretical speciation frameworks. Scientific Awards : Molecular Ecology Prize 2022

Sijing ShenView profile

Associate Professor

• Numerical Simulations of Galaxy Formation and Evolution
• Galaxy-Intergalactic Medium Interactions
• Galactic Winds
• +9 more

Dr. Sijing Shen is an Associate Professor at the Institute of Theoretical Astrophysics, University of Oslo . She specializes in numerical simulations of galaxy formation and evolution, focusing on interactions between galaxies and the intergalactic medium, galactic winds, and the physics of the interstellar medium. PhD in Astrophysics (McMaster University, 2010) Postdoctoral Fellow (University of California, Santa Cruz, 2010-2014) Research Associate (University of Cambridge, 2014-2016) Associate Professor (University of Oslo, 2017-present) Her research employs high-performance computing and numerical magnetohydrodynamics to model the co-evolution of supermassive black holes and galaxies, the origins of galactic magnetic fields, and observational signatures of high-redshift galaxies. She develops and utilizes massively parallel magneto-hydrodynamic codes to create virtual universes for comparison with observational data. Recent publications highlight her work on dwarf galaxies, circumgalactic medium physics, and spectral diagnostics for next-generation telescopes like AtLAST. Key themes include feedback mechanisms, dark matter interactions, and computational methods in astrophysics. Young Research Talents Grant, Research Council of Norway Shen supervises 2 PhD students and 1 postdoctoral fellow. Her work bridges theoretical modeling with observational predictions, particularly in galaxy formation and evolution processes.

• Artificial Intelligence
• Computer Science
• Cellular Automata
• +3 more

Tom Glover is an Assistant Professor in the Department of Computer Science within the Faculty of Technology, Art and Design at Oslo Metropolitan University. His office is located at Stensberggata 29, 0170 Oslo (Office number: SG204) with contact information including mobile: +47 975 38 894 and office: +47 672 37 712. Dr. Glover's research focuses on the intersection of cellular automata, artificial intelligence, and complex systems. His work spans theoretical computer science, artificial life, and practical applications in reservoir computing and control systems. His research group is part of the Innovation, Digital Transformation and Sustainability Research groups within the Department of Computer Science. Analysis of his publications reveals a consistent focus on cellular automata as computational models, with particular emphasis on their application in reservoir computing, network dynamics, and self-organizing systems. His work demonstrates how simple computational rules can generate complex behaviors with applications across multiple domains including control systems and biologically inspired computing. As an active researcher, Glover has published in reputable venues including the International Journal of Parallel, Emergent and Distributed Systems, Complex Systems, and proceedings from the Artificial Life Conference series. His recent work (2023-2024) shows continued development in sensitivity analysis of cellular automata and network topologies.

• Wind Energy
• Offshore Wind Turbine Technology
• Structural Optimization
• +6 more

Michael Muskulus is a Professor at the Department of Civil and Environmental Engineering at NTNU. His research focuses on offshore wind energy systems, structural optimization, and fatigue monitoring for wind turbines. He leads the Offshore Wind Turbine Technology research group, supervising 3 PhD students. Key projects include X-ROTOR (EU Horizon 2020), FLOAWER (MSCA ITN), and DSF ABYSS. He has held leadership roles at the European Academy of Wind Energy and serves on editorial boards for Wind Energy Science and Journal of Ocean and Wave Energy . His work spans advanced simulation techniques, support structure design, and operational optimization of wind farms. Education and Professional Activities: Extensive international collaboration across 16 PhD defenses as external examiner. Competencies include finite element methods, supercomputing, and stochastic dynamics analysis. Active in 8+ international funding programs and 30+ journal reviews. Research Interests: Disruptive offshore wind turbine concepts (e.g., X-shaped rotors, floating systems) Fatigue lifetime extension strategies Massively parallel simulation frameworks Optimization of operations & maintenance (O&M) workflows Recent Publications Trends: Focus on structural reliability, machine learning applications in hydrodynamics, and novel load extrapolation algorithms. Over 50 peer-reviewed articles since 2015, emphasizing interdisciplinary approaches to wind energy challenges. Grants & Labs: Active in EU-funded initiatives like TWEED (2024-), managing research teams in advanced analysis methods and offshore wind system integration.

Tor FlåView profile

Professor

• Mathematical Chemistry
• Bioinformatics
• Plasma Physics
• +3 more

Tor Flå is a Professor at the Department of Mathematics and Statistics, UiT The Arctic University of Norway. His research spans mathematical modeling in biology and physics, with a focus on quantum chemistry, cancer dynamics, and bioinformatics. He leads projects in computational biology, plasma physics, and protein adaptation studies. Key contributions include developing the DeltaProt software for comparative genomics and advancing multiwavelet-based methods for electronic structure calculations. His work on leukemia stem cell dynamics and cold-adapted enzymes bridges mathematics and life sciences. Flå collaborates with international teams on nonlinear systems and has been affiliated with research groups like CoSMo (Complex Systems Modeling). Flå’s publications span journals like Journal of Mathematical Chemistry , PLOS ONE , and BMC Bioinformatics . He has advised interdisciplinary projects but no specific student names are listed. His research emphasizes computational methods, statistical analysis of biological sequences, and theoretical frameworks for complex systems.

• Computer Architecture
• Processor Microarchitecture
• Memory Systems
• +4 more

Rakesh Kumar is an Associate Professor in the Department of Computer Science at NTNU, affiliated with the Computer Architecture Lab (CAL). He received his PhD from UPC Barcelona in 2014 and previously worked at Uppsala University, the University of Edinburgh, and Intel Barcelona Research Center. His research focuses on improving datacenter efficiency through microarchitecture and memory systems, hardware/software co-design, and dynamic code translation. Education: PhD in Computer Architecture, UPC Barcelona (2014) MEng in Microelectronics, BITS Pilani (2008) BTech in Electronics and Communications, Kurukshetra University (2005) Research Interests: His work emphasizes processor microarchitecture, memory systems, and energy-efficient designs. Key areas include hardware/software co-design (e.g., Nvidia Denver alternatives), dynamic vectorization, and server optimization. Recent projects target server front-end bottlenecks, address translation efficiency, and BTB organization for data centers. Publications: Recent work includes contributions to IEEE/ACM MICRO, HPCA, and ISCA, focusing on topics like uneven block size instruction caches, address translation optimizations, and server architecture improvements. Awards: Intel Spontaneous Level II/Excellence Award (2014) Distinguished Artifact Award at IEEE/ACM MICRO 2023 Teaching & Advising: Teaches courses like TDT4258 Low Level Programming and advises students on projects such as vector unit design and microarchitecture optimization. Active in mentoring PhD candidates and leading the Computer Architecture Lab. Labs/Teams: Affiliated with the Computer Architecture Lab (CAL) and collaborates on projects like DARCO, an infrastructure for HW/SW co-designed virtual machines.

Lars Ailo BongoView profile

Professor

• Operating Systems
• Concurrent Programming
• Data-intensive Computing
• +5 more

Lars Ailo Bongo is a Professor at the Department of Computer Science, UiT The Arctic University of Norway. His research interests span operating systems, concurrent programming, data-intensive computing, and applications of machine learning in healthcare and bioinformatics. He has been actively involved in teaching courses such as Operating Systems, Concurrent Programming, and Algorithms, emphasizing open-access educational materials. Notably, three of his master’s students received awards for their theses: Nina Angelvik (2018), Bjørn Fjukstad (2014), and Martin Ernstsen (2013). He also advises students like Johan Ravn, whose master’s project led to a startup. Bongo’s work includes developing scalable bioinformatics pipelines (e.g., NeLS infrastructure), optimizing genomics workflows, and advancing tools for medical image analysis. He pioneered open-access course repositories on GitHub and contributed to visualization frameworks like GeneNet VR. His research bridges computer science with healthcare, focusing on tumor infiltration lymphocyte analysis, AI-driven diagnostics, and ethical AI applications in mental health. He has held roles as a postdoc at Princeton and TA at the University of Tromsø. His scientific contributions span over 50 peer-reviewed articles, covering topics from parallel computing to synthetic health data interoperability. He emphasizes reproducibility and transparency in data management, exemplified by projects like Occode for historical data transcription and MORTAL language for cross-paradigm computing. In education, Bongo advocates for accessible teaching materials and has designed courses like INF-2202 Concurrent Programming, which utilize modern tools (e.g., Go language) and GitHub repositories. His teaching philosophy integrates practical coding with theoretical foundations, fostering student innovation and open-source collaboration.

Atle GrønnView profile

Professor

• Russian Linguistics
• Ukrainian Linguistics
• Formal Semantics
• +4 more

Professor Atle Grønn holds a position at the University of Oslo's Department of Literature, Area Studies and European Languages, within the Faculty of Humanities. His expertise spans Russian and Ukrainian linguistics, formal semantics, pragmatics, contrastive linguistics, and corpus linguistics, with a notable focus on the history of the Soviet chess school. He is actively involved in research projects such as Oslo Studies in Language (as editor-in-chief) and the RuN corpus-based initiative. Grønn’s research emphasizes TAM (tense, aspect, mood) categories, particularly in Slavic languages. Recent work includes studies on relative tense shifts in Russian, non-complement clauses in English and Ukrainian, and tense dynamics in Slavic languages. His publications also intersect with chess historiography, including books like Sjakk eller livet (2016) and Sjakken som var (2023, translated as Games and Goals in 2024). He has contributed to academic journals such as Theoretical Linguistics , Scando-Slavica , and Language and Linguistics Compass . His collaborative projects with Arnim von Stechow explore tense theories in Russian and cross-linguistic syntax-semantics interfaces. Grønn’s work bridges formal linguistic analysis with cultural-historical studies, particularly in the context of chess and language evolution.

• High-Performance Computing
• Graph Algorithms
• Social Network Analysis
• +3 more

Johannes Langguth is an Associate Professor at the Department of Informatics, University of Bergen. His work focuses on high-performance computing, graph algorithms, and social network analysis. He has contributed to GPU acceleration techniques for cardiac simulations and graph processing on manycore architectures. Langguth's research intersects computational science with societal challenges, including misinformation detection in social media and conspiracy theory analysis. He leads projects on temporal interaction networks and has developed datasets like COCO and GECO to study pandemic-related disinformation. His interdisciplinary approach combines computer science with psychology and public health, addressing both technical and human aspects of information dissemination. Notable contributions include optimizing breadth-first search on Graphcore IPUs and applying graph neural networks for combinatorial problems. Langguth collaborates widely, with affiliations at Simula Research Laboratory and BI Norwegian School of Business. His work is funded by institutions like the Research Council of Norway and the EU, reflecting its applied and impactful nature in both academia and industry.

• Medical Imaging
• Ultrasonics
• Biomedical Engineering
• +3 more

Bjørn Atle Johan Angelsen is a Professor affiliated with the Norwegian University of Science and Technology (NTNU), based at AHL-senteret (Prinsesse Kristinas gate 3, Øya). His research focuses on medical ultrasound imaging, nonlinear acoustics, and biomedical engineering, with emphasis on applications in drug delivery, tissue characterization, and contrast agent detection. He has supervised multiple PhD students, including Ola Finneng Myhre, Jochen Rau, and Rune Hansen. His work frequently appears in journals like the Journal of the Acoustical Society of America and IEEE Transactions on Ultrasonics . Angelsen's research interests include dual-frequency ultrasound technologies, acoustic radiation force mechanisms, and the development of advanced imaging techniques for clinical diagnostics. His studies often involve collaborations on nanoparticle transport in biological tissues and the optimization of transducer designs to reduce scattering and enhance image clarity. His recent articles highlight advancements in nonlinear elasticity imaging, ultrasound-enhanced drug delivery, and the exploitation of acoustic properties for tissue classification. These contributions bridge fundamental physics with translational biomedical applications. While no specific awards are noted in the text, his extensive publication record and role as a supervisor at NTNU underscore his significant contributions to the field.

• Cryptology
• Intrusion Detection Systems
• Wireless Communication Security

Slobodan Petrovic is a Professor at the Norwegian University of Science and Technology (NTNU) in the Department of Information Security and Communication Technology (IIK), part of the Faculty of Information Technology and Electrical Engineering. His research focuses on Cryptology, Intrusion Detection Systems, and Wireless Communication Security. He teaches Cryptology and Intrusion Detection and Prevention in NTNU's Master in Information Security (MIS) and PhD programs. He is a member of the Cryptology Research Group (Norwegian Applied Crypto Lab - NaCl Lab). His research interests span cryptographic algorithm design, cybersecurity threats in autonomous systems and 5G networks, and secure communication protocols. Recent work includes frameworks for nonlinear combiners in ternary logic, dynamic LFSR analysis, and physical-layer security in MIMO OFDM systems. Publications highlight trends in cybersecurity applications of computational intelligence, intrusion detection systems, and cryptographic analysis. Notable contributions include countermeasures for unmanned vehicles and secure guidance systems. He has been actively involved in developing algorithms for efficient data analysis in digital forensics and cybersecurity analytics. His lab, the NaCl Lab at NTNU, focuses on applied cryptographic solutions. He collaborates on projects related to secure network communication, biometric security, and true random number generation.

• Smart Wireless Systems (IoT)
• Information Security (Biometric Systems)
• Digital Electronics
• +2 more

About Mohammad Derawi Mohammad Derawi is a Professor at NTNU's Department of Electronic Systems, part of the Faculty of Information Technology and Electrical Engineering. He leads the Smart Wireless Systems (SWS) Research Group and directs the IoT-Lab at NTNU Gjøvik. His academic journey includes a PhD from NISLab (Norway) and CASED (Germany), alongside BSc/MSc degrees in Informatics from DTU (Denmark). Research Interests Derawi specializes in Smart Wireless Systems (IoT), Information Security (Biometric Systems), Digital Electronics, and Machine Learning applications in activity recognition and e-learning. His work bridges theoretical advancements with practical implementations, emphasizing secure and efficient IoT solutions. Research Projects Notable projects include IoT-Safetraffic (RFF Innlandet), Ambulance Drone (NTNU), Wireless ECG (Innovation Norway), and the EU-funded TURBINE project. These projects focus on IoT security, healthcare applications, and smart transportation systems. Awards & Recognition Recipient of NTNU's Quality in Education Award (2017) Honored as Norway's Youngest Professor (2016) Received multiple best paper awards from IEEE/ACM/Springer Invited to the Crown Prince Couple's 50th Birthday Celebration (2023) Grants & Leadership Led multi-institutional initiatives funded by RFF Innlandet, Innovation Norway, and EU grants. His research group collaborates with industry partners to develop cutting-edge IoT and wireless communication solutions. Labs & Teams Scientific Director of NTNU's IoT-Lab, fostering innovation in IoT ecosystems and smart city technologies. Active in mentoring students and industry professionals through workshops and conferences.

• Cryptography
• Blockchain Technology
• 5G Network Security
• +7 more

Professor Danilo Gligoroski is affiliated with the Norwegian University of Science and Technology (NTNU) under the Department of Information Security and Communication Technology. His work bridges cryptography, blockchain technology, and 5G network security, with a focus on decentralized systems and privacy-preserving protocols. Key research trends in his recent publications include blockchain applications in healthcare and reseller markets, verifiable delay functions for consensus mechanisms, and cryptographic frameworks for chat-based systems. He explores data integrity, network coding, and scalable storage solutions for blockchain ecosystems. Major collaborations include co-authors like Mayank Raikwar, Katina Kralevska, and Anton Karl Oskar Hasselgren. His work often intersects with GDPR compliance, network slice isolation, and secure service implementation in modern telecommunications.

• Computational mechanics
• Contact mechanics
• Coupled problems
• +12 more

Kjell Magne Mathisen is a Professor in the Department of Structural Engineering at the Norwegian University of Science and Technology (NTNU), specializing in computational mechanics and numerical methods. His work bridges advanced engineering computation with practical applications in structural analysis, contact mechanics, and fluid-structure interaction. Research Focus: Computational mechanics, Isogeometric analysis, Finite Element Method, Nonlinear structural analysis, Fluid-structure interaction, Error estimation. Affiliation: NTNU, Department of Structural Engineering. His recent publications (2019-2024) emphasize wind-resistant bridge design using ALE-VMS and Isogeometric methods, machine learning applications in additive manufacturing, and adaptive refinement techniques for thin plates. Collaborations with leading researchers like Yuri Bazilevs and Trond Kvamsdal highlight cross-institutional efforts. Professor Mathisen's technical competencies include software architecture for engineering computations, parallel processing, and multiscale modeling, with historical contributions to shell analysis, sparse matrix methods, and contact problem simulations.