Molly Maleckar is a Research Professor at the Computational Physiology Department of Simula Research Laboratory , Oslo, Norway. Her work bridges computational modeling, cardiac electrophysiology, and biomedical applications, with a focus on arrhythmia mechanisms, fibrosis modeling, and machine learning integration in cardiac risk prediction. Research Interests include: Computational Cardiology Ion Channel Dynamics Machine Learning in Medicine Excitable Tissue Modeling Cardiac Fibrosis Analysis Biomedical Simulation Scientific Contributions span 15+ publications (2018-2024) addressing atrial fibrillation, calcium handling, and AI-driven ECG analysis. Key collaborative projects involve patient-specific ventricular modeling and educational initiatives like the Simula Summer School in Computational Physiology .
Hans Bihs is a Professor in the Department of Civil and Environmental Engineering, Faculty of Engineering. His research focuses on computational fluid dynamics (CFD), wave hydrodynamics, and wave-structure interaction using the open-source framework REEF3D. Key Research Areas: CFD simulations, wave modeling, floating body dynamics, ocean wave energy, aquaculture hydrodynamics, sediment transport, and high-performance computing. Projects: ERC Consolidator Grant PARTRES (2023-2028), EEA Grants Portugal SurfWave (2023), NFR KPN IPIRIS (2021-2025), EEA Baltic SolidShore (2021-2024), NTNU's MAPLE (2022-2025), and DigiCoast (2021-2024). Email: hans.bihs@ntnu.no His recent publications (2025-2020) analyze fluid-structure interaction, ship-induced waves, floating offshore wind turbines, submerged vegetation, and coastal structures using advanced CFD techniques. Topics include wave hydrodynamics, turbulence, and numerical modeling for marine and aquaculture systems.
Ronny Scherer is Center Director and Professor at CEMO (Center for Educational Measurement) and Deputy Director at CREATE (Center for Research on Equality in Education) at the University of Oslo's Faculty of Educational Sciences. His work bridges educational measurement, assessment, and evaluation with a focus on research syntheses and complex sampling surveys. Dr. Scherer's research spans two interconnected domains: substantive areas including digital divides, equity and equality in education, and measurement of complex cognitive skills (such as complex problem solving, adaptability, computational thinking, and executive functioning); and methodological areas focusing on advanced meta-analytic techniques, multilevel structural equation modeling, and spatial analysis of complex survey data. His work frequently utilizes international large-scale assessment data from PISA, ICILS, TIMSS, PIRLS, PIAAC, and TALIS. His publication record demonstrates a clear trajectory toward increasingly sophisticated meta-analytic approaches, with recent work focusing on second-order meta-analyses, AI-assisted screening methods, and advanced techniques for handling complex survey data. His research consistently addresses critical educational challenges related to equity, digital literacy, and measurement of 21st century skills. Dr. Scherer has secured significant research funding for projects including ARISE (Academic resilience in mathematics and science among vulnerable students), DiDiRes (Digital inequalities in education), and ADAPT21 (Educational assessments of the 21st century: Measuring and understanding students' adaptability in complex problem solving situations). Co-director of CREATE (Centre for Research on Equality in Education) since 2023 Professor of Educational Assessment and Measurement at CEMO since 2019 Extensive experience with international large-scale assessments including ICILS, TALIS, and PIAAC As an educator, Dr. Scherer teaches advanced courses in measurement models, multilevel models, meta-analysis, and equity in education. He actively supervises graduate students interested in his research areas and has developed numerous workshops on structural equation modeling and meta-analytic methods for international audiences.
Johannes Skaar is a Professor at the Department of Physics, University of Oslo (UiO). He holds a 100% position there since 2017, previously at NTNU. His research focuses on quantum field theory, quantum optics, electromagnetics, metamaterials, photonics, and quantum information. He teaches advanced courses such as FYS4170 Relativistic Quantum Field Theory and FYS1005 Classical Mechanics. His work spans theoretical physics with notable contributions to single-photon states, metamaterial properties, and quantum cryptography security. Skaar’s research integrates foundational physics with applied technologies like metamaterials and quantum communication systems. His studies on Fresnel equations and magnetic permeability have advanced electromagnetic theory. He frequently publishes in top journals like Physical Review A and Physical Review Letters . Research groups: Theoretical Physics at UiO.
Elena Celledoni is a Professor in the Department of Mathematical Sciences at the Norwegian University of Science and Technology (NTNU). She has been employed at NTNU since 2004 and has held the position of professor since 2009. She is a member of the Differential Equations and Numerical Analysis Group at the Department of Mathematical Sciences and serves as its leader. Her educational background includes: Master's degree in Mathematics from the University of Trieste (1993) Ph.D. in Computational Mathematics from the University of Padua, Italy (1997) Elena Celledoni's research focuses on numerical analysis, particularly structure preserving algorithms for differential equations and geometric numerical integration. Her work bridges theoretical mathematics with practical computational methods, developing algorithms that maintain the geometric properties of the systems they approximate. She has made significant contributions to Lie group integrators, energy-preserving methods, and the application of these techniques to mechanical systems and shape analysis. In recent years, her research has expanded to include the intersection of numerical methods with machine learning, exploring how structure-preserving approaches can enhance neural networks and data-driven modeling. Her publications demonstrate a clear trend toward integrating traditional numerical analysis with modern machine learning techniques while maintaining a strong foundation in geometric integration and structure preservation. This interdisciplinary approach has led to innovations in neural ODEs, structure-preserving neural networks, and physics-informed machine learning models that respect the underlying mathematical structures of the systems they model. Elena Celledoni has received recognition for her work through the following honors: Member of the Royal Norwegian Society of Sciences and Letters Member of the European Consortium of Mathematics in Industry Council Member of the board of the International Council of Mathematics in Industry and Applications Editorial board member for SIAM Review, Journal of Computational Dynamics, Journal of Geometric Mechanics, Calcolo, and Networks and Heterogeneous Media As an advisor, she has mentored several students including Torbjørn Ringholm who completed his doctoral dissertation on 'Discrete gradient methods in image processing and partial differential equations on moving meshes.' Her research has been supported by various grants enabling her to lead projects on geometric numerical integration, collaborate internationally, and organize significant academic events such as the special semester at Isaac Newton Institute of MS in 2019 on 'Geometry, compatibility and structure preservation.' She leads the Differential Equations and Numerical Analysis Group at NTNU, which focuses on developing and analyzing numerical methods that preserve the geometric structure of differential equations. The group maintains active collaborations with researchers worldwide and has made substantial contributions to advancing the field of geometric numerical integration and its applications to real-world problems.
Luca Frediani is a Professor in Theoretical and Computational Chemistry at the Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway. His research focuses on advanced quantum chemistry methods, including density functional theory, multiwavelet basis sets, and solvation modeling. He actively develops computational tools like MRChem and VAMPyR for molecular electronic structure calculations. Current affiliation: UiT The Arctic University of Norway Research group: Theoretical and Computational Chemistry Teaching: KJE-2001 Theoretical Chemistry and Spectroscopy His work spans relativistic quantum chemistry, numerical methods for response properties, and benchmarking of basis set limits. Publications emphasize eliminating basis set errors, multiwavelet applications, and polarizable continuum models for solvation. He collaborates extensively on software development for quantum chemistry. Recent articles highlight multiwavelet-based DFT at the basis set limit, noise-tolerant force calculations, and relativistic effects in electronic structure. Sub-fields include scalar relativity, cavity-free solvation, and metal-ligand interaction accuracy.
Are Oust is a Professor of Financial Economics at the Norwegian University of Science and Technology (NTNU School of Economics) and a Professor II at the Norwegian School of Economics. He specializes in housing market dynamics, real estate economics, and tax policy. His research focuses on housing bubbles, property valuation, and the impact of regulation on real estate markets. Affiliations: NTNU School of Economics (Professor) Norwegian School of Economics (Professor II) Deputy Head of Research at NTNU School of Economics (2021–present) Deputy Director of NTNU Center for Housing and Environmental Economics (2016–present) Education: PhD in Economics, NTNU (2013) Master’s in Accounting and Auditing, Economics, and Business Administration from NHH (Norwegian School of Economics) Bachelor of Science in Economics, NTNU Research Interests: Dr. Oust’s work emphasizes automated valuation models, housing market regulation, energy labeling in real estate, and the interplay between taxation and home ownership. His research has been published in journals such as Quantitative Finance , Journal of Real Estate Research , and Energy Policy . Key Contributions: His studies on housing bubbles, rental market dynamics, and the application of AI in real estate valuation have shaped policy debates. Recent work explores the role of adverse selection in iBuyer models and the predictive power of dwelling conditions in automated valuations. Grants & Leadership: He advises on real estate policy and serves on multiple boards, including the NTNU Center for Housing and Environmental Economics, and private real estate firms like Strinda Eiendom AS. His teaching focuses on personal finance, investment strategies, and tax planning.
Marte Cecilie Wilhelmsen Solheim is Professor of Innovation and Vice-Rector for Innovation and Society at the University of Stavanger (UiS), Norway. She is affiliated with the UiS Business School’s Department of Innovation, Management and Marketing and serves on the steering committee of UiS Smart Cities and the national Research Network for Smart Sustainable Cities. Education: PhD in Innovation Studies, University of Stavanger, defended January 2017 with the thesis Innovation, Space, and Diversity . Opponents: Prof Ron Boschma & Assoc Prof Abigail Cooke. Supervisors: Prof Rune Dahl Fitjar & Prof Ragnar Tveterås. Research Interests: Solheim’s research sits at the intersection of innovation studies, economic geography and organisational theory . She investigates how workforce diversity —spanning migration background, gender, education and work experience— drives innovation, export performance and regional development . Specific themes include: Foreign-born workers as catalysts for innovation and international market access. Combinatorial innovation arising from diverse knowledge pools. Gendered and geographical variations in diversity–innovation links. Smart cities, responsible innovation and digital transformation in times of crisis. Publication Trends: Across more than 40 peer-reviewed works since 2016, Solheim has advanced large-scale quantitative analyses of Norwegian employer–employee data, qualitative case studies of energy-sector transformation and conceptual pieces on migration and innovation policy. Recent strands explore post-COVID digitalisation, eco-innovation geography, immigrant entrepreneurship and gender bias in venture-capital decisions , consistently emphasising inclusive innovation. Scientific Awards & Recognition: 2021 Competence Sharing Prize – Stavanger-region Chamber of Commerce, for outstanding dissemination of research to business and society. Member, Academy of Young Researchers in Norway . Regional Studies Association (RSA) Ambassador to Norway . Advising & Funding: Solheim presently supervises two PhD candidates— Xiangyu Quan (Smart Cities, Innovation & Policy) and Alina Meloyan (Universities & Regional Development). She has led or partnered in numerous national and international research and consultancy projects, frequently serving as expert advisor to Norwegian ministries, the Confederation of Norwegian Enterprise (NHO) and regional development agencies. Labs & Teams: She is an active member of the Research Network for Smart Sustainable Cities and sits on the steering committee for Smart Cities initiatives at UiS , fostering cross-disciplinary collaboration between business, engineering and social-science scholars.
Anders Skrondal is a Professor II at the University of Oslo's Faculty of Educational Sciences, affiliated with the Centre for Educational Measurement (CEMO). He also serves as a Senior Scientist at CEFH (Research Council of Norway Centre of Excellence) at the Norwegian Institute of Public Health and Co-Principal Investigator at CREATE, another Norwegian Centre of Excellence. His academic journey includes roles as Head of the Biostatistics Group at the Norwegian Institute of Public Health and Professor of Statistics at the London School of Economics (LSE), where he directed the Methodology Institute. Skrondal's research focuses on psychometrics, statistics, biostatistics, and econometrics, with a major contribution being the development of the GLLAMM framework. He has authored 14 books and over 200 peer-reviewed papers, achieving an h-index of 63 and 30,000+ citations. His awards include the 1997 Psychometric Society Dissertation Prize and leadership roles in prestigious organizations like the Psychometric Society and Royal Statistical Society. Research Interests: Skrondal specializes in statistical methodologies including latent variable modeling, multilevel modeling, and missing data analysis. His work bridges theoretical advancements and practical applications in medicine, psychology, and social sciences. He is renowned for integrating latent variable and mixed model frameworks to address complex data structures. Recent trends in his publications emphasize methodological solutions for missing data, non-ignorable mechanisms, and psychometric model validation. His articles span statistical theory, medical applications, and educational measurement. Awards: President, Psychometric Society (2016–2017) Elected Member, International Statistical Institute Outstanding Academic Title for 'The Cambridge Dictionary of Statistics' (2011) Fulbright Professor at UC Berkeley (2013–2014) Advising & Grants: Skrondal has led major research initiatives such as CEFH and CREATE, funded by the Research Council of Norway. While no specific advisee list is provided, his collaborations span international institutions. His work on GLLAMM software is used in over 750 journals, reflecting widespread academic impact. Labs/Teams: Active in CEMO and CEFH, he contributes to interdisciplinary teams advancing educational measurement and public health research. His involvement in CREATE focuses on equality in education through statistical innovations.
Lars Enok Engvik is an Associate Professor at the Faculty of Logistics, Molde University College (HiMolde). His research focuses on quantum mechanics, fluid mechanics, thermodynamics, numerical simulations, and environmental modeling. He holds a PhD in Nuclear Physics from the University of Oslo (1999). Education: PhD in Nuclear Physics, University of Oslo (1999) Research Interests: His work spans fluid dynamics in geophysical contexts, including submarine landslides, debris flow mechanics, and numerical modeling of geological processes. He also investigates thermodynamic systems and pollutant dispersion modeling with applications in environmental science. Publications Overview: Recent works address fluid infiltration in magmatic veins, submarine debris flow dynamics, and hydroplaning phenomena. Earlier studies include neutron star properties and glacially influenced submarine mass-wasting processes. Labs/Teams: Affiliated with the Faculty of Logistics’ applied research teams focusing on logistics optimization and environmental modeling systems.
Henk Keers is an Associate Professor at the Department of Geosciences of the University of Bergen (UiB). His research focuses on geophysical modeling, seismology, and ocean acoustics, with contributions to seismic wave analysis, teleseismic tomography, and educational innovations in sedimentology. He actively collaborates on projects such as SEDucate, promoting active learning in geoscience education. Key research themes include: Body wave modeling for regional seismology Acoustic inversion techniques for ocean turbulence Tomographic imaging of crustal structures Development of efficient numerical methods for geophysical problems Recent work includes presentations at events like the AdriaArray Workshop (2023) and Nordic Seismology Seminar (2022) , addressing topics such as elastic isotropic modeling and waveform inversion. His research has been funded by institutions including the Research Council of Norway.
Asle Sudbø is a Professor and Center Director of the SFF QuSpin at the Norwegian University of Science and Technology (NTNU), Faculty of Natural Sciences, Department of Physics. He holds a PhD from Brown University (1990). His research focuses on quantum phenomena in condensed matter systems, including superconductivity, quantum criticality, topological materials, and strongly correlated systems. He has advised numerous PhD students and contributes to cutting-edge theoretical studies of low-dimensional systems and topological phases. His work integrates advanced computational methods and explores systems like graphene, topological insulators, and Bose-Einstein condensates. Education: PhD in Physics, Brown University, 1990 Research Interests: Condensed matter physics at quantum regime Quantum transport of spin/charge Topological superconductivity and phase transitions Unconventional superconductors (graphene, pnictides) Bose-Einstein condensates and superfluids Quantum critical phenomena and Monte-Carlo simulations Publications Trends: Recent work emphasizes topological effects in superconductors, magnon-mediated mechanisms, and quantum criticality in 2D systems. Key themes include breaking symmetry limits in superconductors and exploring topological signatures in magnetic heterostructures. Grants & Labs: Leads the QuSpin Center (SFF), focusing on quantum spin systems. Collaborates extensively on projects involving topological materials and low-temperature physics.
Elena Celledoni is a Professor of Mathematics at the Department of Mathematical Sciences, Norwegian University of Science and Technology (NTNU), where she has been employed since 2004. She leads the research group on differential equations and numerical analysis. Her academic background includes a Master’s degree (1993) and Ph.D. (1997) in mathematics from the Universities of Trieste and Padua, Italy, respectively. She has held postdoctoral positions at the University of Cambridge (UK), the Mathematical Sciences Research Institute (MSRI, Berkeley, CA), and NTNU. Her research focuses on numerical analysis, particularly structure-preserving algorithms for differential equations and geometric numerical integration. Recent work includes applications of neural networks in computational mechanics and data-driven modeling. She has co-authored over 100 peer-reviewed articles in journals such as Journal of Computational Physics , SIAM Journal on Scientific Computing , and Physica D . Her research interests span computational methods for dynamical systems, machine learning integration with numerical analysis, and geometric algorithms for shape analysis. She actively collaborates with international researchers, including contributions to conferences like NeurIPS and workshops on theoretical aspects of computational dynamics. Elena is a member of the editorial boards of Journal of Computational Dynamics and has organized workshops on structure-preserving integrators. Her work emphasizes preserving geometric properties in numerical methods, with applications in fluid dynamics, mechanical systems, and image processing.
Jelena Veletic is a Postdoctoral Fellow at the Institute for Educational Research within the Faculty of Educational Sciences at the University of Oslo, specializing in large-scale educational assessment and school leadership analysis using international datasets. Her educational qualifications include: PhD in Educational Measurement from the Centre for Educational Measurement (CEMO), University of Oslo (2023) with thesis "Challenges and Opportunities in Measuring School Leadership. An analysis of data from the Teaching and Learning International Survey (TALIS)" Master of Science in Psychology from the Department of Psychology, University of Banja Luka, Bosnia and Herzegovina (2012) Veletic's research focuses on the intersection of school leadership practices, organizational climate, and teacher well-being, employing advanced statistical methodologies including multilevel modeling and structural equation modeling. Her work examines how leadership styles influence school environments across diverse cultural contexts, particularly through analysis of TIMSS and TALIS datasets. She contributes significantly to measurement model development in educational leadership research. Her publication record reveals a concentrated trajectory in international comparative leadership studies, with increasing emphasis on Nordic educational systems and methodological innovation in cluster analysis for leadership profiling. Recent work demonstrates sophisticated applications of multilevel SEM to unpack complex relationships between distributed leadership and teacher satisfaction. Scientific recognition includes: Marie Skłodowska-Curie Fellowship under EU Horizon 2020 Veletic actively participates in EU-funded research initiatives including the OCCAM project, collaborating with international scholars on secondary analysis of TALIS data. Her work involves substantial grant-funded research in educational measurement and cross-national leadership studies. She maintains active membership in the EKVA and Large-scale Educational Assessment (LEA) research groups at the Institute for Educational Research, contributing to methodological advancements in international educational surveys and leadership assessment frameworks.
Erin Bachynski-Polić is a Professor in the Department of Marine Technology at the Norwegian University of Science and Technology (NTNU). Her research focuses on offshore renewable energy systems, particularly the design and analysis of fixed and floating support structures for wind turbines, hydroelasticity, and optimization of marine systems. She leads several major projects including WAS-XL, Green Energy at Sea, and WINDMOOR, addressing challenges in mooring systems, extreme loading, and floating wind farm layouts. Education includes a Ph.D. from NTNU (2014), an M.S. and B.S.E. from the University of Michigan (2010 and 2009), specializing in Naval Architecture and Marine Engineering with a mathematics minor. Her teaching spans marine dynamics, ocean structure design, and offshore wind courses. Research interests emphasize advancing hydrodynamic and structural models for floating turbines, wake steering techniques, and environmental load analysis. Notable contributions include validation of Morison force formulations, mooring optimization, and storm impact studies. Projects like SFI BLUES and FLOAWER aim to develop next-generation floating support structures for large-scale offshore wind energy.
