جست‌وجوی استاد و پژوهشگر

• Computer Vision
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Habib Ullah is an Associate Professor in Data Science at the Norwegian University of Life Sciences (NMBU), Norway, where he conducts research at the intersection of computer vision and machine learning. He is affiliated with the Institute of Data Science under the Faculty of Science and Technology. He has previously held academic positions at COMSATS University Islamabad, Pakistan, and the University of Ha'il, Saudi Arabia, and served as a postdoctoral researcher at The Arctic University of Norway. Educational Background: PhD in Information and Communication Technology (Computer Vision), University of Trento, Italy (2011–2015) MSc in Electronics and Computer Engineering, Hanyang University, South Korea (2007–2009) BSc in Computer Systems Engineering, NWFP University of Engineering and Technology, Pakistan (2002–2006) Habib Ullah's research is primarily focused on computer vision and machine learning, with applications in aquaculture, agriculture, and human behavior analysis. He investigates underwater fish feeding sounds using audio classification, develops zero-shot learning models for recognizing unseen classes, and applies deep learning to detect stress in salmon via skin dot patterns. He also explores AI-driven controlled environment agriculture, leveraging sensors and automation for optimal crop growth. His work emphasizes practical AI solutions for real-world challenges in environmental and biological domains. The recent publications highlight a strong trend in leveraging deep learning for zero-shot and semi-supervised learning, particularly in computer vision tasks such as sea ice classification, crowd anomaly detection, and agricultural monitoring. His research spans remote sensing, biomedical signal processing, and human activity recognition, demonstrating interdisciplinary versatility. The keywords reflect a focus on robust feature representation, knowledge transfer, and model generalization. Scientific Awards and Funding: Industrial PhD grant 'Advancing Controlled Environment Agriculture AI' from The Research Council of Norway (Project number 354125, 2 million NOK, 2024) Team member (Coordinator-Participant) in the Battery Cell Assembly Twin (BatCAT) project funded by Horizon Europe (7 mEuro, 2023–2027) Development of an AI-Based Image Analysis System for Monitoring Plant Status (Funding: 1.8 mNOK, starting 2025) Habib Ullah actively supervises PhD projects and contributes to academic service through editorial and organizational roles. He has served as an Associate Editor for IEEE Access, Guest Editor for MDPI Remote Sensing, and Editor of the Springer book Machine Learning Techniques and Sensor Applications for Human Emotion, Activity Recognition, and Support (ML-SHEARS) . He has also been a Track Chair and Program Committee Member for several international conferences, reflecting his leadership in the academic community. His research is supported by significant grants and collaborative projects, indicating strong institutional and international engagement. He is involved in multiple research teams and projects, including the BatCAT project on battery manufacturing and AI applications in controlled environment agriculture with RIFT LABS AS. His lab work integrates deep learning, sensor fusion, and data analytics for environmental and biological monitoring systems.

• Artificial Intelligence
• Machine Learning
• AI Alignment
• +۲ مورد دیگر

Michael Riegler is a Researcher at the AI Department, Simula Research Laboratory , focusing on interdisciplinary applications of Artificial Intelligence in healthcare, sports analytics, and multimedia systems. His work bridges Machine Learning , AI Alignment , and Applied AI across clinical and real-world domains. Key Affiliations: Simula Research Laboratory (AI Department Head) Research Themes: Explainable AI in medicine, multimodal data analysis, and AI-driven health monitoring Research Interests include: Developing AI/ML algorithms for medical imaging (e.g., polyp detection, embryo analysis) Addressing missing data challenges in healthcare through novel imputation techniques Creating multimodal virtual avatars for investigative interview training Designing edge AI systems for sports analytics and sustainable fishing Recent Publications highlight collaborations with institutions in Norway and globally, with a focus on: Medical Applications: Polyp segmentation, ECG analysis, and explainable models for disease detection Sports Analytics: Athlete performance prediction and soccer video processing Data Infrastructure: Lifelogging datasets (ScopeSense), semantic representation frameworks Labs & Teams include leadership in Simula’s AI Department and participation in projects like Medico Multimedia Task , ImageCLEF , and MediaEval workshops. His work emphasizes responsible AI innovation in public sectors and privacy-preserving systems for edge environments.

Thomas Nordahlمشاهده پروفایل

استاد

• Education
• Pedagogy
• Inclusion in Education
• +۳ مورد دیگر

Thomas Nordahl is a Professor of Pedagogy at the University of Inland Norway, affiliated with the Faculty of Teacher Education and Pedagogy and the Department of Pedagogy. He has been at the institution since 2006, focusing on research and academic leadership. Nordahl holds a doctorate from the University of Oslo (2000) and a master’s in pedagogy (cand. paed). He is additionally a Professor II at Aalborg University. Education: Doctorate in Pedagogy (University of Oslo, 2000); Master’s in Pedagogy (cand. paed); Qualified general teacher. His research interests center on learning environments, inclusion, adapted education, pedagogical analysis, and educational leadership. He supervises PhD fellows and oversees internal/external research projects, including analyzing SePU’s extensive data collections. He teaches across kindergarten and school sectors, emphasizing practical educational challenges. Nordahl leads initiatives within the Center for Practice-Oriented Educational Research and the Centre for Studies of Educational Practice, focusing on bridging theory and practice in education. His work addresses contemporary issues in educational policy and leadership.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۹ مورد دیگر

Jim Torresen is a Professor at the Norwegian University of Science and Technology (NTNU), specializing in Computer Science, Artificial Intelligence, and Robotics. He earned his M.Sc. and Dr.ing. (Ph.D.) in computer architecture and design from NTNU in 1991 and 1996 respectively, followed by industry experience in hardware design before transitioning to academia in 1999. Research Interests: His work spans Machine Learning, Evolvable Hardware, and Ethical AI, with notable contributions to music technology, facial expression recognition, and healthcare monitoring systems. He actively explores interdisciplinary applications of AI in creative domains and clinical environments. Publications & Editorial Roles: Torresen has published extensively in journals like Frontiers in Artificial Intelligence and Genetic Programming and Evolvable Machines . He serves as a Topic Editor for Frontiers in Explainable AI and has editorial roles in robotics and biomedical AI domains.

Steffi de Jongمشاهده پروفایل

دانشیار

• Public History
• Cultural Memory Studies
• Holocaust Representation
• +۲ مورد دیگر

Steffi de Jong is Associate Professor of Public History and History Didactics at NTNU's Department of Historical and Classical Studies. She holds a PhD from NTNU and previously held positions at Maastricht University and University of Cologne. Research encompasses: Museum representation of historical testimony Digital memory of the Holocaust Re-enactment as historical practice Sensory dimensions of public history Virtual reality in memorial culture Her publications critically examine how technologies like VR transform Holocaust commemoration, arguing that simulated experiences create new forms of 'post-witnessing'. Recent projects include Gerda Henkel Foundation-funded research on historical re-enactment origins and analyses of digital Holocaust memory. Monographs include 'The Witness as Object' (Berghahn, 2018), which analyzes video testimony in memorial museums, and edited volumes on choreomusicology and women's musical leadership.

Anders Åkermanمشاهده پروفایل

استاد

• Applied Microeconomics
• International Trade
• Labor Economics
• +۵ مورد دیگر

Anders Åkerman is a Professor in the Department of Economics and Finance at the UiS School of Business and Law, University of Stavanger. He is an active researcher in applied economics with a focus on labor, trade, technology, and environmental policy. His research interests span applied microeconomics , international trade , labor economics , and environmental economics . He investigates how technological change, market structure, and global shocks affect firms, workers, and policy outcomes. His work often combines empirical methods with policy relevance. The recent articles reflect a strong trend in analyzing digital transformation (e.g., broadband and trade), environmental impacts of trade and production , and economic resilience during crises such as the pandemic. His publications appear in leading journals like the Quarterly Journal of Economics and American Economic Journal: Applied Economics . He has contributed to public discourse through op-eds in Dagens Nyheter and Svenska Dagbladet , and has been involved in policy commissions like Sweden's Coronakommissionen. He regularly presents research at seminars and international conferences, including the Nordic International Trade Seminar and Stockholm Institute of Transition Economics. Anders Åkerman has advised or collaborated with several researchers and policy experts, including Torsten Persson, Magne Mogstad, and Karolina Ekholm. While formal student advisees are not listed, his collaborative work suggests active mentorship and team leadership. He is affiliated with research networks and institutes such as IFN (Research Institute of Industrial Economics) and participates in interdisciplinary teams focused on economic policy and transition. His upcoming work continues to explore the intersection of technology, environment, and labor markets.

• Multilingualism
• Translanguaging Pedagogy
• English as an Additional Language (EAL) Education
• +۴ مورد دیگر

Georgios Neokleous is a Professor of English in the Department of Teacher Education at the Norwegian University of Science and Technology (NTNU), within the Faculty of Social and Educational Sciences. He holds a PhD in Education from Saint Louis University (2014), focusing on home language use in EAL classrooms. His career began as an EFL/ESL teacher, with extensive experience across Europe and the U.S., and he has developed specialized courses for diverse learner groups. Neokleous’ research emphasizes multilingualism, translanguaging pedagogy, and inclusive literacy practices in linguistically diverse classrooms. Education: PhD in Education, Saint Louis University, 2014 Masters and Bachelor’s degrees (implied, not explicitly stated) Research Interests: Neokleous explores the integration of students’ home languages in EAL settings, translanguaging as a pedagogical tool, and assessment strategies in multilingual environments. His work bridges theory and practice, addressing challenges in teacher education and classroom diversity. Recent trends in his publications highlight cross-national comparisons (e.g., Norway-Cyprus studies), innovative teaching methodologies, and the role of technology in modern classrooms. Advising & Grants: Supervises students at BA, MA, and PhD levels. Collaborates with international researchers like Anna Krulatz and Sviatlana Karpava. Active in organizing academic events, including TESOL International and ECER conferences. Labs/Teams: Engaged in collaborative research groups focused on multilingual education, such as the ‘Learning and Teaching English in the Multilingual Classroom’ initiative. His work often intersects with institutions like the University of Cyprus and Multilingual Matters publishing.

• Hospital Ventilation
• Indoor Airflow Distribution
• Thermal Comfort
• +۳ مورد دیگر

Guangyu Cao is a Professor at the Department of Energy and Process Engineering, Norwegian University of Science and Technology (NTNU). He holds leadership roles in multiple international organizations, including the European standards working group CEN TC156 WG18, REHVA's technical committee, and the editorial board of the Journal of Building Engineering (Impact Factor 5.318). His research focuses on indoor airflow dynamics, ventilation systems in healthcare settings, and airborne disease transmission mitigation, with a strong emphasis on surgical environments and school buildings. Education: PhD in Energy Engineering (2009), Helsinki University of Technology Senior Researcher at VTT Technical Research Center (2009-2014) Research Interests: Hospital ventilation optimization, thermal comfort in clinical settings, airborne infection control, and sustainable building environmental quality. He combines experimental studies with mathematical modeling to evaluate ventilation strategies, particularly in operating rooms and isolation wards. Projects: EU Marie Curie DTN HumanIC (2024–2027) EU H2020 iclimabuilt (2021–2025) NFR POSIred (2020-2024) Labs/Teams: Collaborates with St. Olav's Hospital on indoor environment projects and leads teams in Cold Climate HVAC and Healthy Building Europe initiatives.

• Artificial Intelligence
• Machine Learning
• Probabilistic Graphical Models
• +۷ مورد دیگر

Helge Langseth is a Professor at the Department of Computer Technology and Informatics , within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). His research focuses on Artificial Intelligence , Machine Learning , and Probabilistic Graphical Models , particularly Bayesian Networks and their applications in Decision Support Systems . Langseth's work addresses Explainable AI (XAI) , Reinforcement Learning , and Recommender Systems . He has contributed to Bayesian Optimization , Probabilistic Modeling , and Robotic Control in oceanic environments. His recent publications emphasize transparency , fairness , and scalability in AI systems, with applications spanning maritime trade, migraine diagnosis, and power grid management. He is affiliated with the Intelligent Systems Research Group at NTNU and actively mentors doctoral and master's students. Co-authored works with Yanzhe Bekkemoen , Sverre Herland , and Jørgen Hanssen reflect his role in advising the next generation of AI researchers.

Thomas Michael Sattichمشاهده پروفایل

دانشیار

• Geopolitics
• Sustainability Transition
• Energy Policy
• +۴ مورد دیگر

Thomas Michael Sattich is an Associate Professor at the University of Stavanger , affiliated with the Faculty of Social Sciences and Department of Media and Social Studies . His research focuses on geopolitical implications of sustainability transitions, particularly energy policy interdependence and EU-China relations. PhD in Political Science and Economics Expertise in qualitative methods, mixed methods (cluster analysis), and data visualization Lead researcher on EU-funded digital climate negotiation simulation projects His recent publications examine renewable energy geopolitics, industrial policy competition, and sustainability education frameworks. Methodologically, he specializes in Qualitative Comparative Analysis (QCA) and network analysis, contributing to debates on energy security and regional cooperation.

Anne Burmeisterمشاهده پروفایل

استاد

• Work and Aging
• Age Diversity
• Inclusion
• +۶ مورد دیگر

Professor Anne Burmeister is a full Professor of Organizational Behavior at the University of Cologne, Faculty of Management, Economics, and Social Sciences. She specializes in knowledge transfer, age diversity, inclusion, and interpersonal dynamics in workplaces. Her research bridges organizational psychology with practical applications in aging and diverse teams. Education: PhD in Psychology (summa cum laude), Leuphana University of Lueneburg (2016) MSc in Management and Organizational Analysis, Warwick Business School (2011) BSc in Business Psychology, Leuphana University of Lueneburg (2010) Research Interests: Her work focuses on work and aging, age diversity, inclusion, knowledge transfer, and workplace friendships. She investigates how social interactions influence productivity and organizational health, particularly in multigenerational environments. Recent Trends: Recent publications analyze DEI initiative responses, knowledge sharing dynamics, and interventions for aging workforces. Themes include cognitive load theory, intergenerational collaboration, and ambivalent employee reactions to diversity policies. Scientific Recognition: Awarded 40 leading HR minds 2025 by HR magazine Contact: Email: burmeister@wiso.uni-koeln.de Phone: +49 221-470-5887

Dieu Tien Buiمشاهده پروفایل

استاد

• Geospatial Artificial Intelligence
• Machine Learning
• GIS and Geomatics
• +۶ مورد دیگر

Dieu Tien Bui is a Full Professor in the Department of Business and IT at the University of South-Eastern Norway (USN) School of Business. His research focuses on Geospatial Artificial Intelligence Machine Learning GIS and Remote Sensing Natural Hazard Modeling Environmental Problems (landslides, floods, soil salinity, biomass) . He has contributed to over 15 recent publications in journals like Science of the Total Environment , Remote Sensing , and Geomorphology , emphasizing hybrid AI models for landslide and flood susceptibility. His work spans Vietnam, India, China, and Iran with applications in climate change adaptation and disaster management. Scientific Awards: Global Highly Cited Researcher PhD Supervision: He has supervised 8 PhD students at institutions including USN, NTNU, and Vietnamese universities.

• Maritime Risk Analysis
• Autonomous Ship Systems
• Safety Verification
• +۳ مورد دیگر

Børge Rokseth is an Associate Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His work focuses on maritime systems, autonomous vessel control, and safety verification. He actively supervises Master's students and contributes to research on risk-informed control systems, hybrid power systems, and systems-theoretic process analysis (STPA). Research Interests: Rokseth's research spans autonomous ship systems, dynamic risk assessment, and safety verification. He explores risk-based decision-making for maritime autonomy, hazard identification in hybrid propulsion systems, and control function allocation in dynamic positioning. His work integrates systems theory, machine learning, and regulatory compliance (e.g., COLREGS) to enhance safety and environmental performance in marine operations. Publications: His recent work includes probabilistic trajectory prediction frameworks for autonomous ships, STPA-based safety analyses, and studies on decarbonization barriers in the maritime industry. These publications emphasize risk modeling, systems-theoretic approaches, and simulation-based verification. Teaching: Rokseth teaches courses such as TTK4130 - Modelling and Simulation, contributing to the education of future engineers and researchers in cybernetics and maritime systems.

• Machine Learning
• Graph Neural Networks
• Time Series Analysis
• +۷ مورد دیگر

Filippo Maria Bianchi is an Associate Professor in the Department of Mathematics and Statistics at UiT The Arctic University of Norway, where he conducts research at the intersection of machine learning, dynamical systems, and complex networks. He is also a Senior Researcher at NORCE Norwegian Research Centre and actively contributes to the IEEE Task Force on Learning for Structured Data and the ELLIS Society. Department: Department of Mathematics and Statistics School: Faculty of Science and Technology University: UiT The Arctic University of Norway Adjunct Position: Senior Researcher, NORCE Education: Bachelor’s in Computer Engineering, Sapienza University of Rome Master’s in Artificial Intelligence & Robotics, Sapienza University of Rome (cum laude, 2012) PhD in Machine Learning, Sapienza University of Rome His research focuses on graph machine learning, time series analysis, reservoir computing, and probabilistic forecasting , with applications in energy analytics and remote sensing. He has led and contributed to numerous projects involving Arctic power grids, satellite-based environmental monitoring, and deep learning for sustainability. The recent publications reflect a strong trend in graph neural networks —particularly pooling mechanisms, spatiotemporal modeling, and explainability—alongside applications in energy forecasting, avalanche detection, and remote sensing . His work combines theoretical innovation with real-world impact, especially in Arctic and remote environments. Scientific Affiliations and Leadership: Vice-Chair, IEEE Task Force on Learning for Structured Data Member, ELLIS Society Co-founder, Northernmost Graph Machine Learning group Member, IEEE Task Force on Reservoir Computing Visiting Professor, Politecnico di Milano (2024–2025) He actively mentors students and collaborates on interdisciplinary research. He has led projects in power grid reliability, solar fault detection, and unsupervised change detection in satellite imagery . His work is supported by open-source implementations and reproducible research practices. Laboratories and Research Groups: Northernmost Graph Machine Learning group (co-founder) ARC Research Group, UiT Graph Machine Learning Group, Lugano

Terese Johannessenمشاهده پروفایل

دانشیار

• Quality Improvement in Healthcare
• Nursing Education
• Healthcare Leadership
• +۶ مورد دیگر

Terese Johannessen serves as an Associate Professor in the Department of Health and Nursing Sciences at the University of Agder (UiA), Norway. Her academic work focuses on quality improvement, leadership development, and implementation science within healthcare settings, particularly in nursing homes and home care services. Dr. Johannessen's research primarily centers on understanding quality and safety in long-term care environments. Her work investigates contextual factors influencing healthcare quality, leadership interventions for improvement, and the conceptualization of 'quality' among healthcare providers. She employs qualitative methodologies to explore managers' experiences, implementation challenges, and the development of practical tools for frontline staff. Her research has significant implications for improving care delivery in nursing homes and home care services through evidence-based leadership approaches. Analysis of Dr. Johannessen's publication record reveals a strong thematic focus on the SAFE-LEAD project, a comprehensive research initiative examining leadership interventions for quality and safety in nursing homes and home care. Her work spans multiple dimensions including intervention design, implementation challenges, contextual mapping, and evaluation of leadership approaches across different healthcare settings. The research demonstrates a methodological preference for qualitative and mixed-methods approaches to capture the complex realities of healthcare improvement work. Dr. Johannessen collaborates extensively with researchers including Siri Wiig, Eline Ree, and Ingunn Aase, primarily through the SHARE Centre for Resilience in Healthcare at the University of Stavanger. Her work bridges academic research and practical application in healthcare settings, with significant contributions to understanding how quality improvement efforts can be effectively implemented in real-world contexts. Her research portfolio demonstrates consistent productivity with multiple publications annually, showing progression from foundational studies on contextual factors to the development and testing of specific leadership interventions. The SAFE-LEAD project represents a cohesive research program addressing critical challenges in long-term care quality and safety through systematic investigation and practical tool development.