Find Academic Supervisors

• Aquaculture Engineering
• Recirculating Aquaculture Systems (RAS)
• Feed Technology
• +5 more

Odd Ivar Lekang is a Professor at the Department of Mechanical Engineering and Technology Management, Norwegian University of Life Sciences (NMBU). His work spans aquaculture engineering, environmental sustainability, and feed technology, with a focus on recirculating aquaculture systems (RAS), sustainable protein sources, and wastewater treatment. He has extensively researched fish health management, feed formulation, and automation in aquaculture systems. Research interests include optimizing RAS for salmon farming, developing alternative feed ingredients (e.g., torula yeast and microalgae), and enhancing wastewater treatment efficiency in small-scale aquaculture. His contributions also extend to vehicle classification technologies and human-robot collaboration in food processing. Key publications explore nutrient accumulation in RAS, enzymatic treatments for feed processing, and biodiesel production from Jatropha curcas. His work emphasizes sustainable practices and technological innovation in aquaculture infrastructure. Dr. Lekang collaborates with industry partners like Noraker Rakfisk AS and contributes to EU programs such as AQUA-TNET. His expertise bridges mechanical engineering, environmental science, and marine biology, addressing challenges in both land-based and sea-based aquaculture systems.

• Forest Inventory
• Remote Sensing
• Biomass Estimation
• +2 more

Ole Martin Bollandsås is a Professor at the Norwegian University of Life Sciences (NMBU) in the Faculty of Environmental Sciences and Natural Resource Management, specifically within the Forestry and Renewable Energy Section. His research focuses on forest inventory methodologies, remote sensing applications, and ecosystem dynamics. Primary research interests include forest biomass estimation, treeline ecotone dynamics, and the integration of airborne laser scanning (LiDAR) with traditional forest inventory techniques. His work spans Norwegian alpine environments and tropical forests, with emphasis on climate change impacts and carbon cycle interactions. Research demonstrates strong expertise in geospatial analysis, statistical modeling of forest attributes, and validation of remote sensing products using field data. Recent work examines latitudinal gradients in carbon storage and advanced disturbance detection methods. Dr. Bollandsås maintains active international collaborations with research in Tanzania and Norway. His publication record reflects extensive work with TanDEM-X, GEDI, and UAV-based remote sensing platforms.

• Cryptography
• Cryptographic Voting Systems
• Key Exchange Protocols
• +4 more

Kristian Gjøsteen is a Professor at the Department of Mathematical Sciences, Norwegian University of Science and Technology (NTNU). He holds a MSc and PhD from NTNU and is part of the Algebra Group. His research focuses on cryptographic systems, including voting protocols, key exchange mechanisms, cloud security, and formal verification of cryptographic proofs. Gjøsteen has contributed to Norwegian government projects on electronic voting (2009-2013) and electronic identification systems. He served on the Norwegian Government’s Committee on Digital Vulnerabilities (Lysne-utvalget). Research interests include cryptographic voting systems, key exchange protocols (with a focus on forward secrecy and tight security proofs), privacy-preserving technologies in blockchain and cloud environments, and formal methods for verifying security protocols. Notable work includes development of coercion-resistant voting systems, lattice-based cryptographic schemes for voting, and machine-checked proofs of accountability. Publications highlight advancements in secure voting systems, post-quantum cryptography, and protocols for constrained networks. Collaborations span international researchers in cryptography and security. His textbook Practical Mathematical Cryptography (2022) provides foundational insights into applied cryptographic techniques. Professional activities include advising on national cybersecurity initiatives and contributing to the design of secure electronic voting infrastructure. Current projects emphasize privacy-preserving blockchain systems and formal verification of cryptographic protocols.

Harald BorgebundView profile

Associate Professor

• Democratic Theory
• Political Philosophy
• Liberalism
• +5 more

Harald Borgebund is an Associate Professor of Political Science at Østfold University College, Department of Information Technology and Communication. He holds a PhD from the University of York (UK), completed in 2009. His academic interests focus on democratic theory, democratic education, and liberal political philosophy. He teaches courses including Political Communication I, Contemporary Political Theory, and Political Communication II. He leads the Digital Communication (DIGICOM) research group and serves on HiØ's Complaint and Disciplinary Committee. Research: Explores normative justifications for democracy, democratic education's role in modern democracies, and the institutional implications of liberal theories of justice. Key Projects: Investigates the welfare state’s relationship with liberalism, judicial review, and plural voting systems. Publications span topics like digital democracy, citizenship education, and algorithmic governance. Recent works include articles on trust in digital societies and the challenges of global citizenship post-Ukraine. Engages frequently with media (NRK, Dagsavisen) on political events and democratic issues in Norway. Media Appearances: Over 20 TV/radio interviews on local and national politics, elections, and democratic processes. Leadership: Directs the DIGICOM research group, contributing to interdisciplinary studies on digital communication and democracy.

• Artificial Intelligence
• Computational Physics
• Machine Learning
• +4 more

Anders Malthe-Sørenssen is a Professor at the University of Oslo’s Center for Computing in Science Education within the Faculty of Mathematics and Natural Sciences. His research integrates artificial intelligence (AI) with neuroscience to develop advanced machine learning techniques and study brain-inspired AI systems. He also focuses on computational methods in materials science, particularly in frictional dynamics and nanoscale processes, alongside computational education research to enhance science teaching. Malthe-Sørenssen teaches courses including Fys1120 (Electromagnetics), HON1000 (Interdisciplinary Honors), and Fys4460 (Disordered Systems and Percolation), emphasizing active learning and technology integration. His past industrial experience includes tech startups and large-scale industry-funded projects, leading to patented technologies. His research interests span computational physics, machine learning, neuroscience, and education innovation. Notable projects include studies on neural circuitry, AI robustness, and material fracture mechanics. He has received awards such as the HMK Gold Medal (1999), Nansen Prize (2001), and multiple teaching excellence prizes (2011–2015). Malthe-Sørenssen leads initiatives like the CO2Basalt project for carbon storage and contributes to international collaborations. His work bridges AI, materials science, and education, fostering interdisciplinary innovation.

Øystein HaugenView profile

Professor

• Cyber-Physical Systems
• Modeling Languages
• Software Engineering
• +7 more

Øystein Haugen is a Professor at the Department of Computer Science and Communication at Høgskolen i Østfold (HiØF), Norway. He specializes in Cyber-Physical Systems (CPS), Modeling Languages (e.g., UML/SysML), and Software Engineering. His work focuses on standardization efforts for modeling languages (ITU/OMG), variability modeling, and real-time systems. Haugen has led EU projects like Productive4.0 and Arrowhead Tools, emphasizing Industrial IoT and digital twin technologies. He co-chaired MODELS 2010 and currently contributes to SysML v2 development. Collaborations include SINTEF Digital, University of Oslo, and Luleå Technical University. Research Interests : Cyber-Physical Systems & IoT Model-Driven Engineering Software Product Line Engineering Formal Methods in Systems Design Standardization of Modeling Languages (SDL/MSC/UML/SysML) Industrial Applications of CPS (Manufacturing, Automation) Recent Article Trends : His 2020-2024 work emphasizes CPS applications, digital twin evolution, industrial IoT interoperability, and imitation learning in manufacturing automation. Key areas include model-based debugging, energy-efficient IoT networks, and autonomic service orchestration in industrial systems. Grants/Projects : Led EU ECSEL projects Productive4.0 (smart manufacturing) and Arrowhead Tools (IoT middleware). Active in standardization through OMG committees and ITU. Recent contributions include WP leadership in EU Horizon projects focusing on industrial digitalization. Labs/Teams : Leads the CPS Research Group at HiØF. Involved in the Arrowhead Tools consortium and Productive4.0 industrial partnerships (Jotne, Prediktor, Unger Fabrikker).

Roland OlssonView profile

Associate Professor

• Machine Learning
• Automatic Programming
• Artificial Neural Networks
• +3 more

Roland Olsson is an Associate Professor at the Department of Computer Science and Communication, Oslo and Akershus University College of Applied Sciences (HIOF). He holds a doctorate from the University of Oslo (UiO) and previously served as an Associate Professor at Chalmers University of Technology in Gothenburg, Sweden. His research focuses on machine learning, automatic programming, and algorithm design through large-scale combinatorial search, particularly via his ADATE system. Olsson’s work emphasizes meta-machine learning, including the automatic design of neural network architectures. His research group explores applications in image processing, symbolic regression, and optimization. Key areas include improving algorithms for edge detection, oil well event prediction, and real-time CNC machine control through imitation learning. Publications span domains like evolutionary computation, industrial informatics, and smart grids. His work frequently appears in journals like IEEE Open Journal of the Industrial Electronics Society and conferences such as IEEE International Conference on Big Data and Smart Computing. Though no specific awards are listed, his contributions to automatic programming and machine learning algorithms are widely recognized in the academic community. Olsson’s advising and grant involvement is implied through collaborative projects with industry partners (e.g., CNC machine operators, oil well monitoring). He leads the Machine Learning group at HIOF and teaches courses in machine learning. His research extends to interdisciplinary applications, including IoT architectures for smart grids and healthcare activity recognition.

Erlend Sand AasView profile

Assistant Professor

• Economics
• Finance
• Financial Technology
• +3 more

Erlend Sand Aas is an Assistant Professor at the Department of Economics, Innovation and Society, Høyskolen i Østfold. His academic roles include teaching courses such as Financing and Investment, Mathematics for Economists, and Technology Management. He specializes in financial markets, housing economics, and digital transformation in finance. His research focuses on topics like mortgage financing risks, cryptocurrency evolution, portfolio optimization using machine learning, and signaling effects of corporate buybacks. Recent work includes analysis of non-linear mortgage supply dynamics and the psychological drivers of cryptocurrency market behavior. Publications span peer-reviewed journals like Journal of Housing Research and platforms like SSRN, demonstrating expertise in both theoretical and applied economics. No specific awards were mentioned in the provided texts. Erlend has held his position since at least 2019 and maintains active research collaborations, particularly with Trond Arne Borgersen on housing finance and financial market dynamics. His teaching spans economics, mathematics, and technology management across undergraduate and graduate programs.

• Sustainable Energy Systems
• Chemical Process Design
• CO2 Capture and Utilization
• +7 more

Thomas Alan Adams II is a Professor at the Norwegian University of Science and Technology (NTNU) within the Department of Energy and Process Engineering. His research focuses on sustainable energy systems, chemical process design, and eco-techno-economic assessments. He leads the Adams Research Group, which addresses global challenges in energy and chemical systems, including carbon capture, hydrogen technologies, nuclear energy, and waste-to-energy conversion. His work integrates advanced process modeling, simulation, and optimization, often collaborating with industry and government to develop practical solutions. Key areas include flexible polygeneration systems, exergy analysis, and risk assessments of emerging green technologies. He is a leader in developing ISO standards for eco-techno-economic analysis (eTEA). Notable achievements include the Editor’s Choice Award in the Canadian Journal of Chemical Engineering (2023) for proposing a Trans-Atlantic Energy Bridge to enhance European energy security. His recent publications span topics like chemical recycling of plastics, hydrogen production on LNG carriers, and risk quantification for CO2-avoiding technologies. He advises multiple PhD students and contributes to open-access resources like Exergy Tables and Aspen Plus tutorials.

• Artificial Intelligence
• Health Informatics
• Internet of Things (IoT)
• +3 more

Randi Karlsen is a Professor at the Department of Informatics, UiT The Arctic University of Norway. She is affiliated with the Open Distributed Systems (ODS) research group and participates in projects such as the Nudge Project and Better Balance in Informatics (BBI). Her research focuses on AI-driven solutions for health promotion, smart nudging, IoT applications, and personalized recommendations. She has contributed to advancements in wearable technology integration, digital twin systems, and context-aware health interventions. Her recent work emphasizes leveraging AI and IoT for behavioral change, such as promoting physical activity through smart nudges and health monitoring via wearable devices. She also explores privacy-preserving techniques in complex ecosystems and decentralized communication systems for mobile devices. Key Projects: Nudge Project, Better Balance in Informatics (BBI) Labs/Teams: Open Distributed Systems (ODS) research group Randi’s publications span topics like multi-agent systems, health video retrieval, and incremental information retrieval. Her work bridges technical innovation with societal impact, particularly in healthcare and sustainable transportation.

• Railway Engineering
• Structural Engineering
• Transportation Systems
• +3 more

Albert Lau is an Associate Professor at the Department of Civil and Environmental Engineering, Norwegian University of Science and Technology (NTNU), within the Faculty of Engineering. His research focuses on railway engineering, structural dynamics, and transportation systems. He coordinates the Master’s program in Road, Railway, and Transportation Engineering and leads the MeTinT (Measurement with Train in Regular Traffic) and FutuRe (Innovative Rail Services) research groups. Education: PhD in Civil Engineering from NTNU (2018), MSc Structural Engineering from University of Leeds (2013), BEng in Civil and Structural Engineering from University of Leeds (2010). Research interests include railway track design, train-track dynamic modeling, infrastructure monitoring, and sustainable transportation systems. Recent work emphasizes digital twin applications, machine learning for infrastructure analysis, and PS-InSAR techniques for ground displacement monitoring. His publications span over 30 peer-reviewed articles, covering topics like automated train operations, remote driving systems, and railway catenary condition monitoring. Teaching includes courses such as TBA4225 Railway Engineering, BA6054 Fundamental Railway Maintenance, and supervising over 20 master/PhD students. He has coordinated Norway-China collaboration projects and led village learning programs in railway engineering education.

• Structural Dynamics
• Railway Engineering
• Structural Health Monitoring
• +7 more

Anders Rønnquist is a Professor and Head of the Department of Structural Engineering at NTNU's Faculty of Engineering. His research focuses on structural dynamics, railway infrastructure, and timber structures, with emphasis on reliability, safety, and innovative monitoring techniques. Collaborations include KTH Stockholm, University of Porto, and industry partners like Elektromotus and Vilnius-based entities. Research Interests Dynamic behavior of railway catenary systems and bridges Structural health monitoring using advanced sensors and machine learning Timber frame dynamics and connection stiffness modeling Wind-structure interaction in long-span bridges Conceptual form-finding in architectural engineering Recent Research Trends Recent work emphasizes data-driven approaches: Kalman filters for crosswind load estimation, deep learning for structural defect detection, and surrogate models for pantograph-catenary systems. Studies also address long-term monitoring of timber buildings and fatigue reliability of railway bridges under evolving traffic conditions. Education & Teaching Coordinates the Teknostart Master's program in Civil & Environmental Engineering. Teaches advanced courses in structural dynamics, steel structures, and railway catenary systems at NTNU. Active in interdisciplinary education bridging structural engineering and architecture. Research Groups Structural Dynamics Group Conceptual Structural Design Group

• Emergency Medicine
• Pre-hospital Critical Care
• Healthcare Quality Improvement
• +4 more

Andreas Jørstad Krüger is an Associate Professor at NTNU's Institute of Circulation and Medical Imaging within the Faculty of Medicine and Health Sciences. He is also a consultant anaesthetist and air ambulance physician. His roles emphasize bridging clinical practice with academic research in pre-hospital and emergency care. University: Norwegian University of Science and Technology (NTNU) Faculty: Faculty of Medicine and Health Sciences Department: Institute of Circulation and Medical Imaging Research interests focus on improving healthcare quality through data-driven approaches, optimizing pre-hospital critical care systems, and advancing resuscitation techniques. Key topics include physician-staffed emergency medical services (EMS), trauma management, and the application of technology in emergency response. His work spans quality indicator development, simulation-based studies, and clinical trials evaluating interventions like resuscitative endovascular balloon occlusion (REBOA). Recent articles highlight his contributions to optimizing ambulance response times, evaluating dispatch precision in helicopter EMS, and refining protocols for airway management and cardiac arrest interventions. Collaborations involve Nordic institutions and emphasize multicenter studies. No scientific awards are explicitly listed, but his extensive publication record reflects sustained academic engagement. His work contributes to both clinical practice improvements and foundational research in emergency medicine systems.

• Real Estate Finance
• Real Estate Economics
• Housing Market
• +6 more

Are Oust serves as Professor in Financial Economics at NTNU Business School (Faculty of Economics and Management) at the Norwegian University of Science and Technology (NTNU). He also holds an adjunct professor position at the Norwegian School of Economics. Oust is deputy head at both the NTNU Center for Real Estate and Environmental Economics and the NTNU Business School with responsibility for research and PhD programs. His educational background includes a PhD in Economics from NTNU (2013) with the thesis "Four Essays on Prices of Housing Services: Evidence from Oslo," a Master in Audit and Accounting from NHH (2007), and dual Master's degrees in Economics and as a siviløkonom from NHH (2005). Oust's primary research focuses on real estate finance and economics, with specific expertise in environmental risk fundamentals in real estate, automatic valuation models (AI-AVMs), auctions and behavioral finance, real estate bubbles, and rent control. His work bridges traditional economic theory with emerging technological applications in property valuation. His research demonstrates consistent exploration of how market dynamics, regulatory frameworks, and technological innovations interact in the housing sector. His publication record shows a clear progression from foundational work on housing bubbles and rent control toward increasingly sophisticated applications of AI and machine learning in property valuation. The 15 most recent articles reveal a strong emphasis on automated valuation models, auction dynamics, and the integration of environmental factors into real estate economics. Two international awards for his research Oust actively engages with both academic and public discourse, regularly contributing to Norway's largest business newspaper, Dagens Næringsliv. His teaching portfolio includes courses in finance and investments, valuation, personal finance, and sustainability in finance. He has demonstrated significant outreach through numerous media interviews and popular scientific lectures, particularly on topics related to housing markets, personal finance for young adults, and the application of AI in finance.

• Marine Systems Design
• Deep Sea Mining
• Aquaculture Logistics
• +5 more

Bjørn Egil Asbjørnslett is a Professor of Marine Systems Design at the Department of Marine Technology, Norwegian University of Science and Technology (NTNU). He serves as Director of NTNU Ocean and Coast, a strategic research area focusing on marine innovation. Additionally, he manages the Bachelor in Engineering (Aquaculture) and Minor in Aquaculture programs. His research spans deep-sea mining systems , ship design complexity , Arctic shipping , and resilient maritime logistics . He leads projects on vessel design for offshore mining, emergency response optimization, and aquaculture logistics. His recent work emphasizes technology transfer from oil/gas to deep-sea mining , multi-stakeholder design solutions , and analytical methods for vessel performance prediction . He has received no explicitly stated awards but is actively engaged in cross-disciplinary collaborations with industry and academia. His advising focuses on doctoral students in marine systems engineering and design methodologies.