Find Academic Supervisors

Michail GiannakosView profile

Professor

• Human-Computer Interaction
• Educational Technology
• Learning Analytics
• +5 more

Michail (Michalis) Giannakos is a Professor at the Department of Computer Science, Norwegian University of Science and Technology (NTNU) and an Adjunct Professor at the Department of Information Systems, University of Agder (UiA) . He serves as Head of the Learner-Computer Interaction Lab at NTNU. His career spans multiple institutions, including roles as EAISI Visiting Professor (TU/e, Netherlands), Honorary Professor (UCL, UK), Associate Professor, Senior Lecturer, and Assistant Professor. Giannakos' research focuses on emerging technologies in online/hybrid education , with emphasis on student/instructor experiences, gamification , STEM learning , augmented reality , and multimodal learning analytics . His recent publications explore generative AI for educational feedback , embodied mathematics , and AR applications for autistic children . 2024–present: Adjunct Professor, UiA 2020–present: Professor/Head, NTNU 2023–2024: EAISI Visiting Professor, TU/e 2022–2023: Honorary Professor, UCL He has received prestigious awards, including the RCN Young Research Talents grant , ERCIM Fellowship , and Outstanding Academic Award (NTNU) . His funded projects include AutoTRUST (Horizon Europe), COMnPLAY-Science (Horizon 2020), and Surrounded by Science (Horizon 2020). Giannakos serves as Editor-in-Chief for the International Journal of Child-Computer Interaction and sits on editorial boards of IEEE Transactions on Learning Technologies , Behaviour & Information Technology , and others. He has reviewed for the European Commission and US-NSF .

Vanja KljajevicView profile

Associate Professor

• Neurolinguistics
• Cognitive Neuroscience
• Clinical Linguistics
• +3 more

Vanja Kljajevic is an Associate Professor at the Department of Special Education, University of Oslo. Her research focuses on neurolinguistics, cognitive neuroscience, and clinical applications of language processing. She leads projects on figurative language comprehension and verbal memory decline in aging. Key areas include proverb interpretation in dementia diagnosis, aphasia rehabilitation via virtual reality, and neurodevelopmental disorders in children. Research Projects: Comprehension of Figurative Language Verbal Memory Decline in Healthy Cognitive Aging Key Contributions: Pioneering corpus-based methods for proverb analysis, developing VR tools for stroke rehabilitation, and investigating sex differences in verbal learning through population studies. Awards: None listed. Advising & Grants: No explicit student advising details provided. Active in interdisciplinary collaborations within the ComPros research group. Labs/Teams: Member of the Communicative Processes (ComPros) research group at UiO, focusing on language and cognition interfaces.

• Artificial Intelligence
• Machine Learning
• Signal Processing
• +6 more

Anis Yazidi is an Associate Professor at the Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, where he leads research in the Research Group for Digital Signal Processing and Image Analysis. His academic profile demonstrates significant contributions to artificial intelligence, machine learning, and signal processing with over 50 publications between 2021-2025 in high-impact venues including IEEE Transactions, Frontiers journals, and AAAI proceedings. Professor Yazidi's research spans multiple interconnected domains with particular emphasis on Tsetlin Machines, deep learning for medical applications, and signal processing theory. His work bridges theoretical foundations with practical implementations, developing novel frameworks like DREAMS for EEG analysis with model card reporting and interpretable methods for ECG classification. His contributions to learning automata theory, particularly in convergence analysis of Tsetlin-based algorithms, represent significant theoretical advances. The research portfolio also extends to cybersecurity applications of AI for IoT protection, agricultural technology for plant disease detection, and renewable energy modeling for wind-speed statistics. Yazidi's publication record reveals a strong interdisciplinary approach, with collaborations across computer science, neuroscience, medical diagnostics, and engineering disciplines. His recent work shows increasing focus on trustworthy AI systems, ethical considerations in medical applications, and specialized neural architectures tailored for specific data modalities including EEG, ECG, and eye-tracking data. The research demonstrates both theoretical rigor in algorithm development and practical implementation for real-world problems. Professor Yazidi maintains an active collaboration network with researchers across the Department of Informatics at UiO, particularly with Pedro Lind, Hugo Lewi Hammer, and Paal Engelstad, while also engaging in international collaborations. His work contributes significantly to both the theoretical foundations of learning systems and their practical implementation in diverse application domains from healthcare to renewable energy.

• Cognitive Science
• Neurolinguistics
• Psycholinguistics
• +4 more

Giosuè Baggio is a Professor of Psycholinguistics at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Language and Literature within the Faculty of Humanities. His research focuses on cognitive science, neurolinguistics, and the neural mechanisms underlying language processing, including semantics, syntax, and compositionality. He is the author of influential works such as Meaning in the Brain and Neurolinguistics , published by MIT Press. Baggio teaches courses such as Language and Cognition , Semantics and Pragmatics , and Research Methods in Linguistics . His work bridges experimental psychology, neuroscience, and computational models, with a particular interest in how language is represented in the brain and the implications for artificial intelligence. He actively engages in science communication, contributing to media outlets like Nature , The Guardian , and Norwegian public radio (NRK), discussing topics ranging from AI ethics to university policies. His research has explored the cultural transmission of symbolic systems, the neural basis of deductive reasoning, and the role of computational complexity in quantifier processing. Baggio is a vocal advocate for rigorous scientific methodology, emphasizing preregistration and theory development. He collaborates internationally, including roles at the Embodied Cognitive Science Unit (OIST, Okinawa) and the Sydney Music, Mind, and Body Lab. His recent work includes organizing conferences like the 2025 Linguistic Association of Finland Symposium on 'Meaning in Language, Machines, and Humans.'

Ahmet SoyluView profile

Associate Professor

• Knowledge Graphs
• Semantic Web
• Data Integration
• +3 more

Ahmet Soylu is Associate Professor in Data and Knowledge Management at the University of Oslo. His research develops semantic technologies and knowledge systems for applications in healthcare, cloud computing, and industrial domains. Research Focus Creates knowledge graph systems for data integration and analysis, with applications in medical diagnostics (cancer/brain tumor classification), cloud cost optimization, and industrial monitoring systems. Develops transformer-based models for SQL recommendation and data linking. Publication Trends Recent work shows strong emphasis on healthcare AI (particularly cancer diagnostics), cloud storage optimization, knowledge graph embeddings, and industrial applications at Bosch. Increasing focus on imbalanced learning techniques for medical data. Project Leadership Developed Koala-UI for tabular data linking Semantic systems for Bosch welding quality monitoring Open energy management systems for EV charging

• Neuroscience
• Biomedical Engineering
• Brain-Computer Interfaces
• +3 more

Haroon Khan is an Associate Professor at Oslo Metropolitan University, Faculty of Technology, Art and Design, Department of Mechanical, Electronics and Chemistry. His research focuses on neuroscience, biomedical engineering, and brain-computer interfaces, particularly studying brain activity during human locomotion and balance using functional near-infrared spectroscopy (fNIRS). Research Interests Investigating cortical activation patterns during walking and balance tasks Developing fNIRS-based brain-computer interfaces Studying neural connectivity in different footwear/ground conditions Hybrid biomedical signal processing techniques (fNIRS, sEMG, EEG) Publications Recent work demonstrates increasing application of machine learning to fNIRS data analysis, with focus on movement classification for prosthetics and rehabilitation. Key themes include motor cortex activation, neural signal processing, and medical device development. Labs & Teams Active member of the ADvanced hEalth intelligence and brain-insPired Technologies (ADEPT) research group.

• Scientific Computing
• Applied mathematics
• Numerical methods
• +2 more

Marie E. Rognes is a Chief Research Scientist at Simula Research Laboratory's Numerical Analysis and Scientific Computing department. She specializes in computational mathematics and biomedical modeling, particularly focusing on cerebral fluid dynamics, electrodiffusion, and poroelasticity. Her work bridges advanced numerical methods with clinical applications in neuroscience. Research Pillars: Brain waterscape modeling, finite element methods, and biophysical simulations Software Leadership: Key contributor to FEniCS and Dolfin-adjoint projects Application Domains: Neurodegenerative diseases, cardiac electrophysiology, and personalized medicine Recent publications reveal methodological innovations in perivascular flow modeling , ionic transport simulations , and multi-scale brain mechanics . Her work on glymphatic system dynamics and cardiac tissue modeling demonstrates cross-disciplinary impact. While no explicit awards are listed, her extensive publication record in top-tier computational journals (SIAM, PLOS, Nature Computational Science) and invited talks at premier conferences (SIAM, ECCOMAS, FEniCS workshops) establish her as a leading figure in biomedical computing.

• Computational Neuroscience
• Biophysics
• Neural Networks
• +6 more

Professor Gaute T. Einevoll is affiliated with the Department of Physics at both the University of Oslo and the Norwegian University of Life Sciences (NMBU) . His research focuses on computational neuroscience , integrating methods from physics, mathematics, and computer science to understand neural mechanisms underlying biological intelligence. Key areas: Neural network modeling , brain signal analysis (EEG, MEG, LFP), computational psychiatry Leadership roles: Co-leader of Norwegian node of INCF since 2007; Partner in EU Human Brain Project since 2013 His recent work explores topological neural representations , GABAB receptor signaling , and ultra-high density electrode technology , as evidenced by publications in 2024-2025. He also develops open-source tools like LFPy and Uncertainpy for biophysical modeling. Active in science communication, he hosts the podcast "Vett og vitenskap med Gaute Einevoll" , discussing neuroscience and related disciplines.

Alejandro Omar BlenkmannView profile

Researcher

• Predictive Processing in Neuroscience
• Auditory Sensory Domain
• Neuronal Network Modeling
• +4 more

Alejandro Omar Blenkmann is a Researcher at the RITMO Centre for Interdisciplinary Research on Rhythm, Time and Movement , Department of Psychology, University of Oslo. His work focuses on brain prediction mechanisms, auditory sensory processing, and intracranial electrode localization. He holds a PhD in Engineering (2012) from the National University of La Plata, Argentina, and has academic affiliations with institutions in Norway, Argentina, and the United Kingdom. Education: PhD in Engineering (2012) - National University of La Plata MSc in Biomedical Engineering (2007) - Favaloro University BSc in Engineering (2004) - Favaloro University Research Interests: Neuronal networks in auditory prediction Intracranial recordings (ECoG/SEEG) Frontal lobe role in prediction iElectrodes open-source toolbox development Collaborations: University of Cambridge University of California, Berkeley International Biomedical Cooperation Network

Hanne StensolaView profile

Associate Professor

• Neuroscience
• Cognitive Neuroscience
• Neural Representations
• +3 more

Hanne Stensola is an Associate Professor in the Department of Psychosocial Health at the University of Agder (UiA). She holds a Dr.Philos in Neuroscience from NTNU’s Kavli Institute and has conducted postdoctoral research at the Champalimaud Centre for the Unknown. Her research focuses on neural representations of space and sensory integration, particularly exploring the interplay between internal cognitive maps (like grid cells) and external sensory inputs. She co-leads a neuroscience lab at UiA studying olfactory systems and higher-order brain regions like the hippocampus and orbitofrontal cortex. Education: BSc Biology (University of Gothenburg), BSc Neuroscience (University of Otago), MSc Neuroscience (University of Oxford), Dr.Philos (NTNU). Research Themes: Grid cells, olfactory neuroscience, internal vs. external representations, neural circuits, sensory-motor integration.

• Artificial Intelligence
• Machine Learning
• Graph Neural Networks
• +5 more

Gustavo Borges Moreno e Mello is an Associate Professor in the Department of Computer Science at Oslo Metropolitan University's Faculty of Technology, Art and Design. Based in office SG209 at Stensberggata 29, Oslo, he actively contributes to the Applied Artificial Intelligence research group with focus on cutting-edge computational methodologies. His research spans artificial intelligence with emphases on graph neural networks, multilingual NLP, reinforcement learning, and medical imaging. Key interests include developing propagation schemes for GNNs, cross-lingual BERT adaptations, rodent fMRI analysis, and empathy assessment in human-computer interaction systems. His work bridges theoretical AI with practical healthcare and communication applications. Analysis of his 2020-2024 publications reveals strong thematic continuity in neural architecture design, particularly HITS-GNN variants for graph analytics and time-representation models. Recent work increasingly integrates neuroscience principles with reinforcement learning while maintaining Nordic language processing applications, notably in English-Norwegian BERT alignment. No information regarding graduate student supervision or research grants was found in the provided materials. He maintains active collaboration within OsloMet's Applied Artificial Intelligence research group, focusing on interdisciplinary projects that connect computer vision, natural language processing, and neuro-inspired computing with real-world healthcare and communication challenges.

• Robotics
• Artificial Intelligence
• Evolutionary Computing
• +12 more

Kyrre Harald Glette is a Professor in the Department for Informatics at the University of Oslo , affiliated with the Robotics and Intelligent Systems Research Group and the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion . His research focuses on the co-design of robot morphology and control using evolutionary and bio-inspired artificial intelligence methods. Research Interests: Robotics and Intelligent Systems Evolutionary Robotics and Co-Design of Morphology and Control Artificial Intelligence and Machine Learning Evolvable Hardware and Embodied Computation Computational Creativity and Music-AI Interaction Human-Robot Interaction and Swarm Robotics His recent publications (2023–2025) reflect a strong interdisciplinary trend, combining robotics, evolutionary computation, and music technology. Key themes include evolutionary design of modular robots , real-time adaptation in bio-inspired systems , interactive sonification , and AI-driven music generation . His work often involves the DyRET robotic platform, emphasizing real-world evolution and embodied learning. Scientific Contributions: Extensive publications in top venues like Frontiers in Robotics and AI , IEEE ICRA , GECCO , and Nature Machine Intelligence . Development of open-source robotic platforms and frameworks for evolutionary robotics. Interdisciplinary work bridging AI, neuroscience, and music. Advising and Projects: He supervises MSc students in evolutionary robotics, robot locomotion, and musical robot swarms. He is involved in several research projects including Predictive and Intuitive Robot Companion (PIRC) , Modeling and Robots , Multimodal Elderly Care Systems (MECS) , Musical Human-Machine Interaction , and Neurophysiological Mechanisms of Human Auditory Predictions (AudioPred) . Labs and Research Groups: He is a key member of the Robotics and Intelligent Systems (ROBIN) group, the RITMO Centre of Excellence , and the Creative Computing Hub Oslo (C2HO) . These groups support interdisciplinary research in AI, robotics, music, and human interaction.

• Cognitive Psychology
• Neuropsychology
• Stroke Rehabilitation
• +3 more

Jan Egil Nordvik serves as Head of Department at the Department of Behavioural Science within the Faculty of Health Sciences at Oslo Metropolitan University. His research focuses on cognitive psychology and neuropsychology with particular emphasis on stroke rehabilitation and cognitive training. Based in Oslo at Pilestredet 38, he maintains an active research profile with numerous publications spanning clinical neuroscience and rehabilitation science. Nordvik's research interests center on cognitive rehabilitation following neurological injury, particularly stroke. His work investigates the relationships between physical activity, cognitive performance, and computerized cognitive training in chronic stroke patients. He has made significant contributions to understanding cerebral blood flow dynamics in aging populations and has explored innovative rehabilitation approaches including high-intensity gait training for post-COVID recovery. His research bridges clinical practice and neuroscience through rigorous methodologies including neuroimaging, randomized controlled trials, and large-scale collaborative studies. Analysis of Nordvik's publication record reveals a strong focus on stroke rehabilitation and cognitive neuroscience. His work spans clinical trials, neuroimaging studies, and implementation research with consistent emphasis on translating scientific findings into clinical practice. Key thematic areas include cognitive training efficacy, neurorehabilitation techniques, cerebral blood flow dynamics, and patient-reported outcomes in rehabilitation settings. His collaborative approach is evident through numerous multi-institutional publications addressing complex neurological conditions. Nordvik's research leadership extends to knowledge translation initiatives aimed at bridging the gap between research findings and clinical practice in rehabilitation settings. His work on implementing evidence-based practice in master's degree teaching demonstrates commitment to educational innovation. While specific grant details aren't provided in the source material, his extensive publication record in high-impact journals suggests successful acquisition of research funding to support his investigations in cognitive rehabilitation and stroke recovery. As Head of Department for Behavioural Science, Nordvik leads research and educational activities within his department. His work appears to involve collaboration with multiple research groups focusing on stroke rehabilitation, cognitive neuroscience, and clinical implementation science. The department's research environment appears to support both fundamental neuroscience investigations and applied clinical research with direct patient impact.

• Artificial Intelligence
• Robotics
• Evolutionary Computing
• +4 more

Kyrre Glette is a Professor at the University of Oslo's Department for Informatics, affiliated with the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion and the Robotics and Intelligent Systems (ROBIN) research group. His work focuses on co-designing robot bodies and behaviors using AI methods, particularly through the open-source robotic platform DyRET. Research interests include evolutionary robotics, bio-inspired computing, and embodied AI. Research Groups: Robotics and Intelligent Systems (ROBIN) RITMO Centre of Excellence fourMs Lab Projects: COCOMO: Co-evolution of Control and Morphologies Multimodal Elderly Care Systems (MECS) Predictive and Intuitive Robot Companion (PIRC) His publications explore topics like evolutionary algorithms for morphological adaptation, embodied music interfaces, and neural mechanisms of auditory prediction. Advising focuses on MSc projects in evolutionary robotics and modular robot control.

• Signal Analysis
• Biomedical Engineering
• Power Systems
• +7 more

Marta Molinas is a Professor in the Department of Engineering Cybernetics at NTNU, affiliated with the Faculty of Information Technology and Electrical Engineering. She holds dual professorships in Industrial Electrotechnics and Power Electronics for Power Systems. She is also an affiliated scientist at the AMOS Center of Excellence. Her research focuses on non-linear/non-stationary signal analysis in both biological systems (EEG) and electrical grids, emphasizing synchronization mechanisms. Key projects include the 'David & Goliath' initiative and 'The Girl Effect' (2019-2020). Education: Dr. Eng. from Tokyo Institute of Technology (2000), Master of Engineering from University of the Ryukyus (1997). Teaching includes courses like TTK4240 Industrial Electrotechnics and TTK7 Adaptive Data Analysis. She supervises numerous PhD students and postdocs in areas like EEG signal analysis and grid stability. Research interests span EEG-based brain-computer interfaces, grid stability, and biomarker identification. Notable experiments include translating EEG signals into drone control and developing low-density EEG systems. Awards: Not explicitly listed, but recognized through prolific publications and grants.