جست‌وجوی استاد و پژوهشگر

• New Product Development
• Engineering Design Thinking
• Human-Machine Interaction
• +۷ مورد دیگر

Martin Steinert is a Professor of Engineering Design and Innovation at the Norwegian University of Science and Technology (NTNU), affiliated with the Faculty of Engineering and the Department of Mechanical and Industrial Engineering. He leads the Design & Engineering research group and heads TrollLABS, a prototyping lab he founded in 2014. His research focuses on the fuzzy front end of product/service development, human-machine interactions in critical environments, and disruptive technology management. Education: Ph.D. in Engineering Design. Affiliations: Norwegian Academy of Technological Sciences (NTVA). Teaching: Courses include Innovation by Design Thinking, Fuzzy Front End Engineering, and Engineering Design Methodology for PhD students. Research Interests: 3D printing and additive manufacturing for medical and aerospace applications. Prototyping methodologies and open-source hardware paradigms. Human factors in remote operations and autonomous systems. Generative AI's role in design innovation and ethical challenges. Articles Trends: Recent work emphasizes blood glucose prediction algorithms, haptic surgical simulations, and material science in 3D printing. Themes include clinical relevance in AI-driven healthcare and low-cost space prototyping. Awards: Top 1% in Mechanical Engineering (Stanford, 2022). Grants: Over $15M from NSF, Swiss NSF, and Norwegian Research Council. Advising: Supervising 9 PhD students and leading international collaborations like the CERN Challenge-Based Innovation program. Labs/Teams: TrollLABS pioneers open-source prototyping tools and hosts hackathons (e.g., IDEA Challenge). Collaborations include Stanford University and CERN.

Nina Køpke Vøllestadمشاهده پروفایل

استاد

• Musculoskeletal Disorders
• Primary Health Care
• Physiotherapy
• +۳ مورد دیگر

Nina Køpke Vøllestad is a Professor at the University of Oslo's Department of Public Health and Interdisciplinary Health Sciences. She leads research on musculoskeletal disorders, rehabilitation, and healthcare systems through projects like FYSIOPRIM. Her work spans physiological mechanisms to health economics, leveraging large electronic health records for clinical trajectory analysis. She co-leads the Center for Sustainable Healthcare Education. Education: Dr. scient. (PhD) in Physiology from the University of Oslo (1985). Academic roles include Head of Department (2004-2014) and Institute Chair (2015-2018). Awards include 'Ryggprisen' (2007) and an education excellence prize (2011). Research interests focus on musculoskeletal pain mechanisms, rehabilitation efficacy, and healthcare prioritization. Over 150 publications analyze pain phenotypes, treatment outcomes, and cross-cultural health disparities. Key projects include the INOREG registry study and STORK Groruddalen cohort examining minority women's health. Grants and collaborations include the Arthritis Research UK Center and the Norwegian Ministry of Health. Supervised numerous studies on pelvic girdle pain, temporomandibular disorders, and chronic pain trajectories. Active in clinical trials for physiotherapy protocols and exercise interventions.

Margareta Bergمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Communication
• Pragmatics
• +۳ مورد دیگر

Margareta Berg is a Research Fellow at the University of Oslo's Department of Philosophy, Classics, History of Art and Ideas , affiliated with the Faculty of Humanities . She is a doctoral candidate in Philosophy, focusing on the project How do we understand machines that talk to us? , which explores human interaction with Large Language Models (LLMs) and their utterances. Her background includes a 2024 MA in Linguistics and 2023/2021 BAs in Linguistics and English Language from the University of Oslo. These qualifications anchor her interdisciplinary research in pragmatics, communication theory, and AI ethics. While no specific articles are listed in the provided texts, her work contributes to understanding the sociolinguistic and philosophical implications of human-AI communication. She is actively involved in the project's ongoing investigations, though no awards or grants are explicitly mentioned here. Berg’s affiliation with the Department highlights her integration into academic research, with a temporary position indicating her current stage as a doctoral researcher.

Gillian Ramchandمشاهده پروفایل

استاد

• Linguistic Semantics
• Ontology of Meaning
• Language and Cognition
• +۵ مورد دیگر

Gillian Ramchand is a Professor of Linguistics at UiT The Arctic University of Norway and a key member of CASTLFish, the Center for Advanced Study in Theoretical Linguistics. She is actively engaged in interdisciplinary research through the OASIS network (Ontology as Structured by the Interfaces with Semantics), funded by CNRS, which brings together scholars from linguistics, psychology, neuroscience, philosophy, and computer science to explore the cognitive foundations of meaning. Her research centers on linguistic semantics, the structure of meaning, and the interface between language and cognition. She investigates how language interacts with conceptualization, categorization, and counterfactual reasoning, often drawing on developmental and cross-disciplinary evidence. Her work emphasizes the importance of formal linguistic theory in understanding broader cognitive processes. The recent publications listed reflect a strong trend in theoretical and cognitive linguistics, with a focus on the syntax-semantics interface, the role of language in thought, and the implications of linguistic structure for modeling cognition. Her writings also explore the cultural and philosophical dimensions of language, including identity, diaspora, and the challenges posed by digital communication and AI. Scientific Awards: No specific awards mentioned in the provided text. She mentors and collaborates within academic networks, particularly through OASIS, where she promotes dialogue between formal semantics and empirical cognitive science. While no direct mention of advising students is made, her leadership in research initiatives suggests an active role in training and guiding emerging scholars. She has no known labs or formal research teams explicitly mentioned, but her involvement in CASTLFish and OASIS indicates participation in collaborative research environments.

• Motivation
• Learning Strategies
• Digital Skills
• +۵ مورد دیگر

Ove Edvard Hatlevik is a full-time Professor at the Department of Teacher Education and School Research , University of Oslo. His work focuses on motivation, learning strategies, and digital competence in educational contexts. PhD in Education from the University of Oslo Former roles: Centre for ICT in Education (2008-2016), Nokut (2007-2008), Department of Education (2000-2007) Qualified teacher with secondary school experience Research Interests Dr. Hatlevik investigates digital literacy , ICT integration , and educational psychology . His studies examine: Digital divide in schools Resilience to digital distractions Teacher professional development Psychometric assessment tools ICT self-efficacy Gender differences in digital skills Scientific Output His 15 most recent publications (2015-2025) demonstrate expertise in: Digital responsibility frameworks Large-scale educational assessments (PISA, TIMSS) Monte Carlo simulations in pedagogy Health literacy interventions ICT policy analysis Teacher competence models

Alberto Danilo Garciaمشاهده پروفایل

استاد

• Personality Psychology
• Well-Being
• Resilience
• +۱۴ مورد دیگر

Alberto Danilo Garcia is a Professor in Psychology at the University of Stavanger, affiliated with the Faculty of Social Sciences and the Department of Social Studies. He leads two research laboratories: the Promotion of Health and Innovation (PHI) Lab and the Lab for Biopsychosocial Personality Research (BPS-PR). He has held academic positions at the University of Gothenburg, Washington University School of Medicine, and has been a visiting professor at La Sapienza University of Rome and the University of Fortaleza. His research expertise spans a broad spectrum of psychological domains. Key interests include personality psychology, well-being, resilience, free will, burnout, parasocial relationships, ADHD, autism, and substance addiction . He integrates methods from classical and modern psychometrics, behavioral genetics, epigenetics, and artificial intelligence to develop innovative tools that bridge quantitative and qualitative research. His work often explores the biopsychosocial underpinnings of personality and health, with a particular focus on the Cloninger model of temperament and character. The recent articles reflect a strong trend toward the application of AI in psychological research, the validation of psychometric models of well-being, and the analysis of personality in both clinical and pop-cultural contexts. His publications span journals in psychology, health sciences, and interdisciplinary research, demonstrating a highly integrative approach. Alberto Danilo Garcia has been instrumental in securing external funding, including grants from the Swedish Research Council (2016-2019), and has led multiple large-scale research projects. He has supervised numerous students at the bachelor's, master's, and Ph.D. levels, and has advised postdoctoral researchers. He has also contributed to academic service as a member of the editorial board for Frontiers in Psychology and Scientific Reports. He is the founder and leader of the International Network for Well-Being, a global multidisciplinary research community. He has extensive teaching experience at the bachelor's and master's levels across several universities and has completed formal pedagogical training in higher education.

Hernando Hernandez Lassoمشاهده پروفایل

پژوهشگر ارشد

• Microeconometrics
• Machine Learning
• Development Economics
• +۳ مورد دیگر

Hernando Hernandez-Lasso is a Ph.D. candidate and Research Fellow affiliated with the University of Agder and Universidad Nacional de Colombia. He works at the Department of Management and Innovation while holding a Senior Econometric Modeller position at Gain Theory and a Research Fellow role at CERSEM. Education: MSc in Economics (Universidad Nacional de Colombia) Research: Combines microeconometrics, machine learning, and mathematical modeling to analyze financial misconduct in developing countries Expertise: Large language models (LLMs), natural language processing (NLP), digital finance Collaborations: Inter-American Development Bank (IADB), USAID His work bridges econometric theory, microeconomics, and data science applications in financial crime detection.

Ane Kristine Espesethمشاهده پروفایل

پژوهشگر ارشد

• Cognitive Science
• Artificial Intelligence
• Large Language Models
• +۳ مورد دیگر

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.

Michele Chiniمشاهده پروفایل

پژوهشگر ارشد

• Large Language Models (LLMs)
• Healthcare Sector
• Predictive Analytics
• +۳ مورد دیگر

Michele Chini is a Doctoral Research Fellow at the University of Oslo, affiliated with the Department of Mathematics and the Statistics and Data Science research group. As an Industrial PhD Fellow, he collaborates with NordicRWE and UiT The Arctic University of Norway. Education: BSc in Statistics for Technology and Sciences, University of Padua MSc in Stochastics and Data Science, University of Turin Research Interests: Focus on leveraging Large Language Models (LLMs) for healthcare applications, particularly predictive analytics to enhance healthcare outcomes. His work bridges theoretical properties of LLMs with practical implementations in healthcare data analysis. Supervisors: Arnoldo Frigessi (University of Oslo, Department of Mathematics) Simen Eide (University of Oslo) Christian Jonasson (NordicRWE) Kristian Svendsen (UiT The Arctic University of Norway, Department of Pharmacy; NordicRWE)

• Artificial Intelligence
• Large Language Models
• Political Communication
• +۴ مورد دیگر

Guri Barka Martins is a Doctoral Research Fellow in the Department of Media and Communication at the University of Oslo, actively engaged in her PhD project under the KnowAI initiative since August 2025. Her work bridges media studies, political science, and artificial intelligence research. Her educational background includes: Bachelor of Sociology from ISS Master of Media Studies from IMK Her research critically examines how trust in large language models shapes the acquisition and interpretation of AI-generated political information. Focusing on the intersection of political communication and AI ethics , she investigates behavioral patterns in user reliance on algorithmic systems, with implications for democratic discourse and digital literacy. This work positions her at the forefront of understanding societal adaptation to generative AI in political contexts. She operates within the KnowAI project framework, which structures her doctoral research on human-AI interaction dynamics in political information ecosystems.

• Reverse Logistics
• Sustainable Logistics
• Closed-Loop Supply Chain
• +۱۰ مورد دیگر

Xu Sun is a Postdoctoral Fellow at the Department of Industrial Engineering, UiT The Arctic University of Norway, Campus Narvik. His research bridges logistics, sustainability, and digital innovation within Industry 4.0/5.0 frameworks, with a focus on practical applications in Norwegian contexts including electric vehicle infrastructure and pandemic response. His research portfolio spans Reverse Logistics, Sustainable Logistics, Closed-Loop Supply Chains, Digital Twins, and Industry 5.0 integration. Key themes include applying generative AI to logistics network design, optimizing charging infrastructure for electric trucks, and developing digital twins for circular economy systems. His work emphasizes multi-objective decision-making to balance environmental, social, and economic sustainability in logistics operations. Analysis of Xu Sun's publication trends reveals a strategic shift toward human-centric digital solutions in logistics. Recent works integrate generative AI, digital twins, and simulation to address Industry 5.0 challenges, with notable emphasis on electric mobility infrastructure (2024-2025) and pandemic-related logistics (2021-2022). His research consistently employs case studies from Norway, demonstrating practical applicability while advancing theoretical models for sustainable supply chains. No scientific awards were documented in the source material. While specific student advising details are absent from the profile, Xu Sun's collaborative publication record indicates active mentorship within research teams. His projects frequently involve multi-institutional partnerships and industry engagement, though explicit grant information is not provided in the available text. Xu Sun contributes to the ArcLog research group's Intelligent Manufacturing and Logistics team and leads the 'Industry 5.0 enabled Smart Logistics' project. His work leverages tools like AnyLogic simulation and digital twin technology to develop human-centered logistics solutions, with physical operations based in Campus Narvik office D2150.

• Machine Learning
• Health Informatics
• Cancer Research
• +۵ مورد دیگر

Jan Franz Nygård is an Associate Professor at the Department of Physics and Technology , UiT The Arctic University of Norway. His work bridges Machine Learning with Health Informatics , focusing on cancer registries, AI for medical diagnostics, and data-driven healthcare solutions. UiT The Arctic University of Norway Department of Physics and Technology His research spans Cancer Research , Artificial Intelligence , and Data Science , with recent studies on synthetic data applications, federated learning, and quantum computing in healthcare. Over 15 recent publications highlight his contributions to breast cancer detection, cervical cancer risk prediction, and software testing for medical systems. Key collaborations include partnerships with the Cancer Registry of Norway , international consortia on federated networks, and interdisciplinary teams in Medical Imaging and Bioinformatics . His work addresses challenges in Secure Health Data Analysis and Population Health Management .

• Machine Learning
• Artificial Intelligence in Healthcare
• Digital Health & mHealth
• +۷ مورد دیگر

Maryam Tayefi Nasrabadi is an Associate Professor of Machine Learning in the Department of Physics and Technology at UiT The Arctic University of Norway (Tromsø). She applies advanced machine-learning techniques to solve pressing challenges in digital health, clinical informatics, and chronic-disease prevention. Research Interests Artificial-intelligence-driven clinical decision support Multimodal fusion of wearable, imaging, and electronic-health-record data Explainable AI for endocrinology, cardiology, and nutrition Telehealth, mHealth usability, and large-scale eHealth adoption Population-health data mining for risk-factor discovery Across more than 60 peer-reviewed publications (2019-2025) she has consistently explored how robust machine-learning models can be translated into routine clinical workflows, emphasising interpretability, fairness, and user-centred design. Grants & Collaborative Networks While specific grant numbers are not detailed in the provided text, her extensive multinational co-authorship (Norway, Spain, Iran, Canada, USA, UK, Italy, Lithuania, etc.) signals participation in large-scale funded consortia focused on AI in healthcare and digital epidemiology. Selected Professional Contributions Member of editorial boards and peer-review panels for leading journals in medical informatics and AI Active contributor to Norwegian national reports on AI implementation in healthcare (2022-2023) Frequent speaker at international conferences on machine learning in medicine

Vilde Olsson Lalunمشاهده پروفایل

پژوهشگر ارشد

• Plant Molecular Biology
• Genetics
• Evolutionary Biology
• +۷ مورد دیگر

Vilde Olsson Lalun is a postdoctoral fellow at the Centre for Ecological and Evolutionary Synthesis (CEES), University of Oslo. She obtained her BSc and MSc in Molecular Biology at UiO in 2013 and 2015, respectively, and completed her PhD in Genetics in 2020 under the supervision of Prof. Melinka Alonso Butenko. Her current research integrates experimental biology and bioinformatics within the interdisciplinary REPEAT project, focusing on how short tandem repeat (STR) variation influences adaptation and gene expression in Arabidopsis thaliana and Atlantic cod. Education 2013 – BSc in Molecular Biology, University of Oslo 2015 – MSc in Molecular Biology (Plant Genetics), University of Oslo 2020 – PhD in Genetics, Department of Biosciences, University of Oslo Thesis: "Molecular investigation of receptor kinase signaling specificity in Arabidopsis thaliana" Research Interests Dr Lalun’s work sits at the intersection of molecular plant biology , evolutionary genomics , and functional genetics . During her PhD she dissected peptide ligand–receptor kinase specificity using the IDA–HAE/HSL2 signalling module as a model. Presently, she investigates how STR length polymorphisms modulate gene expression and organismal fitness under environmental stress, leveraging both Arabidopsis and Atlantic cod as complementary model systems. Core methodological strengths include generation of transgenic lines, advanced live-cell imaging, quantitative microscopy, and integrative bioinformatic analyses. She actively contributes to the REPEAT consortium, an interdisciplinary team that addresses fundamental questions of genome plasticity and climate adaptation. By coupling large-scale comparative genomics with targeted experiments, the project aims to clarify how repetitive DNA elements shape regulatory networks controlling development and immunity. Publication Profile Across 11 peer-reviewed papers (2017-2025) in high-impact journals such as Nature Communications , PNAS , eLife , and Plant Cell , her research spans three major themes: Functional dissection of peptide signalling pathways in plant development and immunity. Comparative genomics of short tandem repeats and their impact on gene regulation. Mechanistic studies of receptor kinase activation and signalling specificity. The 2024-2025 outputs include a lead-author review on plant peptide ligands and multi-omics studies that link STR variation to gene body architecture in eukaryotes. Teaching & Outreach Dr Lalun is a committed educator and science communicator. She instructs two undergraduate courses: BIOS1120 – Physiology BIOS3610 – Molecular Plant Science Beyond the classroom she co-hosts the Norwegian-language podcast BioPodden , produces popular-science YouTube lectures, and gives interviews that demystify plant genetics for the public. Collaborations & Networks She is an active member of the Butenko Group at UiO and collaborates extensively within the CEES and the national REPEAT project network. The lab provides cutting-edge facilities for molecular biology, microscopy and bioinformatics, ensuring a vibrant environment for integrative research.

Yuting Yuanمشاهده پروفایل

پژوهشگر ارشد

• Linguistics
• Semantics
• Pragmatics
• +۳ مورد دیگر

Yuting Yuan is a Research Fellow at the Department of Philosophy, Classics, History of Art and Ideas within the Faculty of Humanities at the University of Oslo. She holds a Master's degree in Linguistics from University College London (2023-2024) and a Bachelor's degree in Norwegian from Beijing Foreign Studies University (2019-2023). Her research interests include: Linguistics with specialized focus on Semantics and Pragmatics Gricean and post-Gricean theoretical frameworks Scalar implicature phenomena Human-LLM interaction dynamics She actively participates in the research group "How do we understand machines that talk to us?", which investigates communication patterns between humans and large language models through empirical and theoretical linguistics approaches.