Find Academic Supervisors

• Biometrics
• Face Recognition
• Face Morphing Attacks
• +3 more

Haoyu Zhang is a Researcher at the Department of Information Security and Communication Technology, Norwegian University of Science and Technology (NTNU), Gjøvik. His primary research focuses on biometric security with specialization in face recognition systems and countermeasures against morphing attacks. His research program centers on synthetic data generation for biometric security, including techniques like SynMorph for creating morphed face datasets and MIPGAN for identity-prior-driven attack generation. He investigates deep learning architectures such as Vision Transformers and diffusion models for morphing attack detection, while also exploring synthetic ethnicity alteration to address dataset bias and remote photoplethysmography for liveness detection. His work bridges theoretical generative models with practical security applications in face recognition pipelines. Publication analysis from 2021-2025 reveals a cohesive research trajectory advancing morphing attack methodologies through three interconnected strands: attack generation (e.g., MIPGAN, SynMorph), detection frameworks (e.g., Vision Transformer-based detectors), and dataset enhancement (e.g., synthetic ethnicity alteration). His 2025 doctoral dissertation synthesizes these contributions into a comprehensive framework for morphing attack generation, data augmentation, and detection. The work demonstrates consistent collaboration with Ramachandra, Raja, and Busch across IEEE and Springer venues, establishing him as a contributor to biometric security standardization efforts.

• Network Architecture
• SDN/NFV Performance Evaluation
• QoE-Centric Network Management
• +4 more

Thomas Erich Zinner is a Professor at the Department of Information Security and Communication Technology (IIK) at the Norwegian University of Science and Technology (NTNU). He leads the Networking Group@IIK and has held roles including Head of the FG INET at TU Berlin and Head of the Next Generation Networks group at the University of Würzburg. He earned his diploma (2006) and PhD (2012) from the University of Würzburg. His research focuses on network eco-systems, performance evaluation of SDN/NFV architectures, QoE-centric management, and 5G/6G innovations. Key projects include TeraFlow, aiming to revolutionize SDN traffic management in beyond 5G networks. His work bridges network technologies, applications, and protocols, emphasizing optimization for emerging paradigms like software-based networking and adaptive video streaming. Recent publications address AI integration in 6G, 5G NR performance, and QoE-aware network slicing. He collaborates internationally, publishing in venues like IEEE Transactions and CNSM. His research addresses challenges in network determinism, inter-domain connectivity, and geo-distributed analytics.

• Instrumentation
• Model based measuring and control
• Process control
• +13 more

Tor Onshus is a Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU) since 1987. He holds a MSc and PhD in Electrical Engineering from NTNU. His professional roles include serving as Dean and Head of Department of Engineering Cybernetics (1989–1996), and Scientific Advisor at SINTEF. Education: MSc in Engineering Cybernetics, NTNU PhD in Electrical Engineering, NTNU Research Interests: Focus on instrumentation, process control, safety systems, and industrial automation. Specializes in IEC standards (61508/11), HIPPS systems, fault tolerance, and safety of machinery in oil/gas production. His work integrates theoretical models with practical industrial applications. Professional Activities: Member of Scientific Board for Norwegian National Metrology Laboratory (1997–2003) Chairman of Norsk forening for automatisering (1995–2004) Advisory roles in PDS-Forum, DeLab, and SINTEF Awards: 2005 Honorary membership in Norsk forening for automatisering 2002 IFEA's highest distinction Grants & Projects: Extensive industrial collaboration through consulting and accident investigations (e.g., Åsta train accident, Njord A drilling accidents). Advised governmental bodies like NPD on Y2K preparations and safety guidelines (OLF-070). Labs/Teams: Leads research on HIPPS systems validation for offshore installations (Åsgård, Troll, Kårstø) and subsea safety technologies.

• Bioinformatics
• Proteomics
• Biocuration
• +3 more

Sandra Orchard is a Team Leader at EMBL-EBI, specializing in Protein Function Content. Her role involves leading a team responsible for curating the UniProt database and annotating the Gene Ontology. She plays a key role in advancing protein data standards and resources, including the Complex Portal and Enzyme Portal. As a member and Treasurer of the International Society for Biocuration, she actively contributes to biocuration practices and standards. Her research focuses on integrating molecular interaction data, enhancing protein annotation methodologies, and developing tools for exploring protein function. She has co-authored numerous papers on topics such as proteomics, data integration, and the impact of biological data resources. Her work spans collaborations with global initiatives like HUPO and IMEx, emphasizing data sharing and standardization. Sandra's team develops value-added interfaces for protein data exploration and supports training in bioinformatics resources. Her contributions include advancing the Complex Portal for macromolecular complexes and improving the accessibility of molecular interaction data through standardized formats like PSI-MI. She advocates for open science and reproducible research practices.

Rune LødengView profile

Researcher

• Catalysis
• Catalytic Reactors
• Catalytic Processes for Energy and Chemicals
• +3 more

Rune Lødeng is a Senior Researcher at SINTEF Industry, Department of Process Technology, in Trondheim, Norway. He has been with SINTEF since 1984, specializing in catalysis R&D including materials, chemistry, catalytic reactors, and processes. He is affiliated with the Kinetics and Catalysis research team, part of the Gemini Center KinCat in collaboration with NTNU's Department of Chemical Engineering. His educational background includes: Master of Science in Engineering (Siv. ing.) from the Norwegian Institute of Technology (NTH), 1980-1984 Doctor of Engineering (Dr. ing.) from NTH, 1988-1991 Postdoctoral research at Ghent University, Belgium, 1997-1998 Lødeng's research centers on catalysis for energy and chemical production, with core expertise in kinetic measurements and modeling , performance testing , and material characterization . His work spans silver-catalyzed methanol oxidation, hydrodeoxygenation of bio-oils, catalytic oxidation for nitric acid production, and flue gas treatment. He integrates fundamental catalyst science with industrial process development, emphasizing reactor design and in situ analytical techniques. Analysis of his 2018-2023 publications reveals consistent focus on sustainable catalytic processes for hydrogen production, biofuel upgrading, and emission control. Key themes include catalyst structure-activity relationships, competitive adsorption effects, and advanced reactor configurations like annular systems. His research bridges experimental kinetics with theoretical modeling to optimize catalytic performance in energy-intensive industries. No major scientific awards were mentioned in the available information. There is no information provided regarding student advising or specific research grants. Lødeng operates within the Kinetics and Catalysis team at SINTEF's Perleporten facility (formerly Chemistry Hall D), leveraging Gemini Center KinCat's collaborative framework with NTNU. This environment supports end-to-end research from molecular-level catalyst studies to pilot-scale process validation, with recent work featuring innovations like the in situ mass analyzer (ISMA) for real-time reactor monitoring.

• Ethics of Science and Technology
• Research Ethics
• Integration of Ethics in Research Programs
• +6 more

Rune Nydal is an Associate Professor at the Programme for Applied Ethics within the Department of Philosophy and Religious Studies at NTNU. His work focuses on ethics of science and technology, research ethics, and integrating ethics into large-scale research initiatives. He holds MAs in atomic physics and philosophy from the University of Bergen and a PhD from NTNU on the philosophical rationale of ELSA/RRI initiatives, particularly in genomics and nanotechnology. Current roles include leading the Crossover research project on knowledge commons and coordinating the ELSA Norway network. Past projects include leadership in the Crossover (2010-2014) and ELSA Norway (2013-2019) programs. He teaches research ethics and serves on the National Committee for Research Ethics in Science and Technology (NENT). His research explores ethical integration in science, socio-technical systems, and the governance of emerging technologies such as nanotechnology and biotechnology. Key publications address techno-fix legitimacy in climate resilience, ethical challenges in big data, and the evolution of ELSA research. Nydal emphasizes collaborative approaches to ethics, advocating for proactive ethical engagement in scientific innovation. His work bridges philosophy, science policy, and practical ethics, contributing to both academic discourse and institutional frameworks.

• Digital Twin Technology
• Artificial Intelligence
• Machine Learning
• +7 more

Adil Rasheed is a Professor in the Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU), within the Faculty of Information Technology and Electrical Engineering. His research focuses on digital twin technology, artificial intelligence (AI), machine learning (ML), physics-based modeling, and hybrid analysis methodologies. He leads projects such as the work package on Digital Twin and Asset Management, collaborating with major industry partners to advance digital twin capabilities. His interdisciplinary work bridges AI-driven approaches with traditional physics-based models for applications in wind energy, autonomous vessels, smart greenhouses, and aquaculture. Notable contributions include developing a VR-enabled smart greenhouse digital twin and the PoroTwin framework for porous media flow analysis. His recent publications span topics like safe marine navigation using reinforcement learning, federated learning for industrial IoT anomaly detection, and predictive maintenance in offshore wind turbines. Rasheed actively engages in academic outreach and serves as an advisor to research initiatives in hybrid modeling and autonomous systems. Research Interests Creation and application of digital twins for physical systems optimization Integration of AI/ML with physics-based models for hybrid systems Autonomous systems navigation and safety (vessels, drones) Wind energy systems and offshore renewable energy Condition monitoring and predictive maintenance Data-driven solutions for aquaculture and urban mobility challenges Key Projects Smart Greenhouse: AI-driven digital twin for autonomous plant growth monitoring via VR PoroTwin: Digital twin for porous media flow analysis in oil and gas Hybrid Analysis and Modeling (HAM) framework combining knowledge-based and data-driven methods NorthWind Project: Digital twin advancements for wind energy systems Publications Trends Rasheed's recent work emphasizes digital twin applications in energy systems (wind turbines), autonomous maritime navigation, and industrial IoT security. He explores federated learning techniques for decentralized anomaly detection and integrates reinforcement learning for safety-critical control systems. Collaborations with industry partners highlight practical implementations in offshore infrastructure, aquaculture, and urban mobility. Grants & Partnerships Active collaborations with industry leaders in renewable energy, maritime robotics, and smart agriculture ensure his research addresses real-world challenges. His work is supported by interdisciplinary projects combining academia-industry expertise. Labs & Teams Leads the Digital Twin and Asset Management team at NTNU, coordinating with research groups in computational engineering, autonomous systems, and renewable energy technology.

• Recommender Systems
• Privacy Issues in AI
• Fake News Detection
• +3 more

Özlem Özgöbek is an associate professor at the Department of Computer Science at NTNU, focusing on recommender systems, privacy in AI, and fake news detection. She holds a part-time role as a program manager at the Norwegian Research Center for AI Innovation (NorwAI) since November 2023. She coordinates the International Work-Integrated-Learning in Artificial Intelligence (IWIL AI) project and actively participates in organizing committees such as the INRA Workshop Series and the Norwegian Big Data Symposium (NOBIDS). She collaborates with the Center for Excellent IT Education (Excited) center, contributing to advancements in semantic web technologies and machine learning applications in education. Her research bridges academic and industrial challenges, emphasizing ethical AI deployment and user-centric systems. Key contributions include multimodal fake news detection frameworks, educational technology innovations, and sustainable wardrobe recommendation systems leveraging Linked Open Data. She has organized multiple international workshops (e.g., INRA 2021–2023) and contributed to benchmarking initiatives like MediaEval’s news image analysis tasks. Her academic work spans over 30 peer-reviewed publications since 2014, including studies on classroom interaction tools, privacy perceptions in recommender systems, and the Adressa news dataset for evaluation purposes. She maintains strong ties with collaborative projects such as the IWIL AI initiative, fostering international education-industry partnerships in AI.

• Materials Science
• Energy Storage Materials
• Nanothermodynamics
• +4 more

Sondre Kvalvåg Schnell is a Professor at the Department of Materials Science and Engineering, Norwegian University of Science and Technology (NTNU), affiliated with the Faculty of Natural Sciences. His research focuses on atomistic simulations of nano-systems and materials for energy storage, with expertise in computational methods and nano-thermodynamics. Education background includes a Master of Science in Technology from NTNU (2009) and a Ph.D. from Delft University of Technology (2013). He has been associated with NTNU since 2016, initially as an Associate Professor. Key competencies include molecular dynamics, Monte Carlo simulations, and computational tools development. He has contributed to over 50 peer-reviewed articles and co-authored a book on nanothermodynamics. His GitHub repositories (e.g., pykbi, sa-CNA) highlight open-source contributions to simulation methodologies. No specific scientific awards or grants are explicitly mentioned in the provided texts. Research interests emphasize bridging microscopic structure and macroscopic properties of materials, particularly through Kirkwood-Buff integrals and finite-size effect corrections in molecular simulations.

• Information Security
• Cybersecurity
• System Administration
• +3 more

Erik Hjelmås is an Associate Professor at the Department of Information Security and Communication Technology, NTNU. He has been a faculty member since 1996, contributing to teaching and research in information security, system administration, and cybersecurity. His roles include study programme director for the B.Sc. in Digital Infrastructure and Cyber Security. He holds a Cand.mag in computer science and mathematics, M.Sc. in information science (University of Pittsburgh), and Dr. scient. in computer science (University of Oslo). His research focuses on face recognition, system administration, and cybersecurity education. He pioneered the cybersecurity group at NTNU Gjøvik and has published widely in journals like Nordic Journal of STEM Education and Computer Vision and Image Understanding. His work bridges technical cybersecurity challenges with educational program development. Teaching includes courses like Operating Systems and Infrastructure: Secure Core Services, along with contributions to conferences like NIKT and MNT. He emphasizes automation, scripting, and information security best practices in both teaching and research.

• Bio-Inspired Artificial Intelligence
• Evolutionary Algorithms
• Artificial Neural Networks
• +5 more

Keith L. Downing is a Professor in the Department of Computer Science at NTNU, affiliated with the Faculty of Information Technology and Electrical Engineering. His research focuses on bio-inspired artificial intelligence, including evolutionary algorithms, artificial neural networks, and computational neuroscience. He has authored two MIT Press books: *Intelligence Emerging* (2015) and *Gradient Expectations* (2023). His work bridges AI, artificial life, and cognitive science, emphasizing the emergence of intelligence in both natural and artificial systems. Teaching responsibilities include Introductory AI, AI Programming, Cognitive Architectures, and Deep Learning courses at NTNU. He also engages in public outreach, such as a 2015 TV appearance on *Schrødingers katt: Kunstig Intelligens*. His research spans predictive neural mechanisms, evolutionary computation, and the societal implications of AI, as seen in his 2014 feature article in *Aftenposten*. Key publications include foundational work on the Baldwin Effect (2004), neural predictive models (2013), and computational neuroscience (2009). He actively promotes interdisciplinary approaches to AI, blending technical innovation with biological plausibility.

• Medical Image Processing
• Volumetric Visualization
• Image Registration
• +2 more

Gabriel Hanssen Kiss is an Associate Professor at NTNU's Department of Computer Science and a senior engineer at St Olavs Hospital's Operating Room of the Future. His expertise spans medical image processing, visualization, extended reality, and ultrasound technology. His research focuses on volumetric data visualization, image registration/fusion, and XR applications for medical contexts. With a PhD in Engineering from KU Leuven focused on visualization and automated polyp detection in virtual colonoscopy, Kiss bridges computer science with clinical applications to advance medical technology.

Zhirong YangView profile

Professor

• Machine Learning
• Information Visualization
• Data Representation Learning
• +6 more

Zhirong Yang is a Professor at the Department of Computer Science at the Norwegian University of Science and Technology (NTNU). He is affiliated with the Norwegian Open AI Lab and focuses on machine learning, information visualization, and data representation learning. His work integrates techniques like neural attention models, nonnegative matrix factorization, and dimensionality reduction algorithms such as Neighbor Embedding (NE) for visualization. Yang's research has applications in bioinformatics, medical imaging, and engineering systems. His educational background includes advanced studies in pattern recognition and computational methods, though specific details are not provided. Research collaborations span institutions globally, including work on bacterial population genomics and chromosome classification. Key contributions include scalable optimization frameworks for visualization (NE) and novel clustering algorithms using graph random walks and low-rank matrix decompositions. Yang has developed software tools like ChordMixer for sequence processing and HSSNE for robust data visualization. His recent publications emphasize advancements in attention mechanisms, sparse factorization, and medical diagnostics. He actively contributes to open-source projects and collaborates with industry on applications like subsea pipeline inspection and energy scheduling systems.

• Machine Learning
• 3D Imaging
• Image and Video Processing
• +7 more

Faouzi Alaya Cheikh is a Professor of Computer Science at NTNU, affiliated with the Faculty of Information Technology and Electrical Engineering. He holds a BSc in Electronics (ENIT, Tunisia, 1992), MSc in Signal Processing (TUT, 1997), and a Dr. Tech. in Signal Processing (TUT, 2004). His career includes roles as an Associate Professor at Gjøvik University College (2006–2015), researcher at TUT (1994–2006), and Electronics Engineer at Société Tunisienne de l'Éléctricité et du Gaz (1992–1993). He leads the Intelligent Systems and Analytics (ISA) research group at NTNU. His research focuses on machine learning, 3D imaging, video surveillance, biometrics, and healthcare applications. Notable projects include Alameda , HiPerNav , and INID . Key areas of innovation include liver surgery visualization, polyp segmentation, facial expression recognition, and IoT-driven healthcare solutions. His work bridges computer vision, medical imaging, and biomedical signal processing. Publications span 2018–2025, emphasizing biomedical applications, autonomous systems, and deep learning frameworks. Recent contributions include real-time liver resection planning, polyp segmentation networks, and emotion recognition for neurological care. Collaborations span industries and institutions globally, addressing challenges in healthcare technology, surgical navigation, and smart cities.

• Control Systems
• Mechanical Engineering
• Offshore Engineering
• +5 more

Christian Holden is an Associate Professor at the Department of Mechanical Engineering and Manufacturing, Faculty of Engineering, Norwegian University of Science and Technology (NTNU). His research focuses on control systems, mechanical engineering, and offshore engineering with applications in robotics, fluid dynamics, and marine systems. He holds a PhD in Modeling and Control of Parametric Roll Resonance (2011). Key research areas include adaptive control systems, drill-string dynamics, riser-tensioner systems, and hydrocyclone optimization. His work combines theoretical modeling with practical applications in offshore operations, robotics, and energy systems. Collaborations with industry and academia have yielded solutions for challenges in subsea engineering, drilling dynamics, and automation. Publications emphasize advanced control methodologies, simulation frameworks, and experimental validation. His recent work explores AI-driven trajectory planning for robotics and control-oriented models for industrial separation processes. Holden's contributions bridge mechanical engineering principles with cutting-edge control theory for real-world engineering systems.