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Ane Kristine EspesethView profile

Research Fellow

• Cognitive Science
• Artificial Intelligence
• Large Language Models
• +3 more

Ane Kristine Espeseth is a Research Fellow at the Center for Computing in Science Education (CCSE), University of Oslo, where she conducts doctoral research at the intersection of cognitive science and artificial intelligence. Her work focuses on developing interpretation frameworks for large language models to understand cognitive processes in both biological and artificial systems, while actively serving as student representative for the International Society for Artificial Life. Her academic foundation includes: Bachelor of Arts (Honours) in Computer Science from the University of Cambridge, United Kingdom Master of Science in Cognitive Science from Seoul National University, South Korea Dr. Espeseth's research employs concept-based and mechanistic approaches—including contextual embeddings and neural circuit analysis—to decode how large language models process information, drawing parallels between artificial systems and human cognition. Her methodology spans language acquisition modeling in children, evolutionary algorithms for socially adaptive chatbots, bio-inspired computing paradigms, and abstract mathematics, reflecting a deeply interdisciplinary approach to cognitive-AI convergence. Her scientific recognition features: First place at the European Contest for Young Scientists (2016) She maintains active research collaborations through the Human Factors Lab and BioIntelligence Lab at Seoul National University, while currently advancing computational science education initiatives at the University of Oslo's CCSE, where she also instructs HON2200 – Data-driven projects for the spring 2025 semester.

• Cybersecurity
• Privacy and Data Protection
• GDPR Compliance
• +7 more

Mohamed Abomhara is a Senior Researcher and Head of Department at the Department of Information Security and Communication Technology, Norwegian University of Science and Technology (NTNU) , Faculty of Information Technology and Electrical Engineering. He serves as Discipline Leader for the MRI PET (Multidisciplinary Research group on Privacy and data protEcTion) research group. Research Interests His expertise includes: GDPR compliance and privacy-by-design Risk assessment and secure system design AI ethics and social-cyber risk mitigation Healthcare digital transformation security Border control technology ethics Recent Publications His 2024-2025 research focuses on multilingual hate speech detection , border control technology acceptance , and privacy protections in national identification systems , bridging AI ethics, cybersecurity, and regulatory compliance. Earlier work (2016-2022) addresses: Cybersecurity in digital substation infrastructure Secure collaborative healthcare information sharing Blockchain-based GDPR compliance AI-driven social media analysis

• Signal Processing
• Machine Learning
• Statistical Signal Processing
• +3 more

Emilio Ruiz Moreno is a Postdoctoral Fellow at Simula Metropolitan's Department of Signal and Information Processing for Intelligent Systems. His work focuses on signal processing, machine learning, and real-time data analysis. Current Affiliation: Simula Metropolitan Center, Oslo, Norway Academic Role: Research Fellow (Signal Processing & Machine Learning) Research Interests: Emilio specializes in trajectory prediction, kernel regression, and zero-delay signal reconstruction. His work addresses challenges in motion-capture sensor data analysis, quantized signal tracking, and multivariate time-series processing for intelligent systems. Key applications include human-computer interaction and biomedical signal modeling. Publications (2021-2025): His research spans statistical signal processing (vector autoregressive models, kriging), adaptive kernel regression, and parallelizable learning frameworks. Technical reports and journal papers emphasize real-time performance and mathematical rigor. Laboratory Affiliation: Works within Simula Metropolitan's Signal and Information Processing for Intelligent Systems department, collaborating on interdisciplinary projects involving artificial intelligence and sensor technology.

Kent-Andre MardalView profile

Professor

• Computational Mechanics
• Biomechanical Applications in Medicine
• Brain Clearance During Sleep
• +5 more

Kent-Andre Mardal is a Professor at the Department of Mathematics , University of Oslo . He specializes in computational mechanics with a strong focus on biomechanical applications in medicine , particularly in modeling brain clearance mechanisms during sleep. His work integrates multi-physics modeling , fluid-structure interaction , and poroelastic couplings to advance understanding of the glymphatic system and cerebrospinal fluid dynamics. Education: PhD (2002) – Simula Research Laboratory Research Interests: Mardal's research spans a wide range of disciplines including: Computational Mechanics – developing robust numerical algorithms for complex physical systems Biomechanical Applications – particularly in neuroscience and medical imaging Brain Clearance During Sleep – modeling the glymphatic system and CSF flow dynamics Multi-Physics Modeling – integrating fluid dynamics, elasticity, and neural networks Finite Element Methods – for accurate and efficient simulations Neural Networks in Scientific Computing – exploring physics-informed neural networks Research Trends from Publications: Mardal's recent publications (2022–2025) demonstrate a clear focus on brain fluid dynamics , particularly the glymphatic system , CSF circulation , and neurodegenerative disease modeling . He employs advanced numerical techniques such as isogeometric analysis , physics-informed neural networks , and parameter-robust preconditioning to solve complex multi-physics problems. His work bridges medical imaging (MRI) with computational modeling to provide insights into brain clearance mechanisms and their impairment in diseases like Alzheimer's. Scientific Awards: No specific awards are mentioned in the provided text. Grants and Projects: Currently, Mardal is the Principal Investigator (PI) of three active research projects: Alzheimer's Physics – exploring the role of fluid dynamics in neurodegeneration Scientific Machine Learning – advancing numerical methods with AI Computational Hydrology – modeling subsurface fluid flow Affiliations and Teams: Mardal was previously a group leader at the Centre of Excellence “Biomedical Computing” at the Simula Research Laboratory. He has authored over 100 papers and several books, and his research homepage is available at https://kent-and.github.io/ .

• Reproductive Biology
• Fish Genetics
• Aquaculture Biotechnology
• +3 more

Igor Szczepan Babiak is a Professor at Nord University specializing in reproductive biology, genetics, and biotechnology of fish. His research focuses on molecular regulation of early development and germline development in fish, control of fish reproduction, and regulatory RNAs. Dr. Babiak has extensive supervision experience with 11 PhD students, 19 MSc students, 5 BSc students, and 10 postdoctoral researchers. He teaches courses including BI228F Biotechnology, BI210F Molecular Cell Biology, and BI132F Biochemistry and Cell Biology, demonstrating his commitment to education in molecular and cellular biology. His research centers on understanding how parental instruction contained in gametes executes into a complex multicellular organism, investigating the regulatory network consisting of genome, transcriptome and proteome. His work spans molecular developmental biology with applications in aquaculture and fisheries management, particularly using zebrafish, Atlantic cod, and Atlantic salmon as model organisms. Recent publications reveal strong focus on non-coding RNA functions, proteomics of embryonic development, and molecular tools for genomic analysis. Dr. Babiak has been actively involved in significant research projects including the NorthCod transnational project for sustainable development of cod farming, demonstrating his commitment to applied research with practical implications for the aquaculture industry. His work on egg quality indicators, sperm cryopreservation, and environmental effects on early development has direct applications for improving fish farming practices.

Karim TamssaouetView profile

Associate Professor

• Scheduling
• Inventory-Transportation Integration
• Operations Research
• +3 more

Karim Tamssaouet is an Associate Professor at BI Norwegian Business School's Department of Accounting, Auditing and Business Economics. His academic trajectory includes positions as Assistant Professor at BI (2020-2024), Postdoctoral Researcher at École des Mines de Saint-Étienne (2019-2020), and R&D Engineer at STMicroelectronics (2016-2019). He holds a PhD from École des Mines de Saint-Étienne, with additional graduate degrees from Université Paris Dauphine and Ecole Nationale Polytechnique. His research specializes in optimization methodologies for industrial challenges, with core interests in: Scheduling algorithms for job-shop and flexible manufacturing systems Integrated inventory-transportation modeling Metaheuristic design (scatter search, neighborhood structures) Dynamic lot-sizing with logistics constraints Bayesian network learning for decision optimization Publication analysis reveals consistent focus on operational efficiency in manufacturing and supply chains, with recent expansions into machine learning applications for optimization. Methodological contributions include novel neighborhood frameworks for scheduling problems and multi-objective approaches for semiconductor production. He currently teaches Business Optimization and Supply Chain Analytics, bridging theoretical operations research with business applications. No research lab affiliations, scientific awards, or supervised students are documented.