جست‌وجوی استاد و پژوهشگر

• Gerontechnology
• Social Connectedness in Elderly Care
• Welfare Technology
• +۳ مورد دیگر

Sehrish Akhtar serves as a Postdoctoral Fellow and Part-time Lecturer at the Faculty of Social Sciences, Oslo Metropolitan University. Her academic work centers on technology-driven solutions for social challenges in elderly care and inequality. She is embedded within the 'Living conditions, health, work and social inequality' research group, collaborating with institutional partners including the City of Oslo Nursing Home Agency (SYE) and No Isolation. Her research spans Gerontechnology, Social Connectedness in Elderly Care, and Welfare Technology implementation, with emphasis on participatory design alongside older adults. Key projects include adapting KOMP telepresence technology for nursing homes to combat loneliness ('Safe and Simple Point of Contact with Relatives') and cultural analysis of telepresence as loneliness solutions ('Virtual Presence'). She prioritizes user-centered approaches that bridge technological capabilities with social needs in vulnerable populations. Publication trends reveal a methodological shift from qualitative cultural analysis (2023) toward mixed-methods evaluation of technology efficacy in care settings (2024-2025). Her work consistently addresses social isolation through digital inclusion frameworks, examining how tools like KOMP mediate family connections while navigating institutional constraints in elderly care. Emerging research extends into interprofessional collaboration dynamics within educational systems.

Benjamin Ricaudمشاهده پروفایل

دانشیار

• Machine Learning
• Graph Signal Processing
• Explainable AI
• +۳ مورد دیگر

Benjamin Ricaud is an Associate Professor and Group Leader in Machine Learning at UiT The Arctic University of Norway's Department of Physics and Technology. His core affiliations include membership in the Machine Learning Group, Visual Intelligence center, and co-directorship of the Digital Technology Innovation Lab focused on Arctic-region tech startups. He also co-chairs the annual Northern Light Deep Learning conference. Ricaud's research spans: Fundamental ML : Graph signal processing, explainable AI, and generative models Applications : Microfossil classification, medical diagnostics (retinal aging), drug analysis, and climate data interpretation Emerging domains : Self-supervised learning and biological data analysis using Raman spectroscopy His recent publications (2020-2025) cluster in three domains: Graph ML methodologies (35%) Biomedical/biological applications (40%) Geoscience/climate informatics (25%) with consistent focus on interpretability and real-world data challenges. Teaching includes Image Processing (FYS-2010), Pattern Recognition (FYS-3012), and Machine Learning (FYS-2021). He leads outreach initiatives developing AI exhibits for Tromsø Science Centre.

• Wireless Communications
• Machine Learning
• Digital Twins
• +۵ مورد دیگر

Pierluigi Salvo Rossi is a Professor at the Department of Electronic Systems , Norwegian University of Science and Technology ( NTNU ), with additional roles as Deputy Head of Department (since 2021) and Deputy Manager at the Center for Green Shift in the Built Environment (since 2022). He also serves as a part-time Research Scientist at SINTEF Energy's Gas Technology department. Education: Ph.D. in Computer Engineering, University of Naples “Federico II”, Italy (2005) Dr.Eng. (cum laude) in Telecommunications Engineering, University of Naples “Federico II”, Italy (2002) Research Interests span Wireless Communications , Digital Twins , Machine Learning , and Statistical Signal Processing , focusing on applications like Industrial IoT , Fault Detection , and Energy Systems . His recent Publications highlight trends in Federated Learning , Graph Signal Processing , and Multi-Sensor Anomaly Detection across domains from Natural Gas Pipelines to Subsea Leakages . Scientific Awards include: Exemplary Senior Editor, IEEE Communications Letters (2018) Department Ambassador, NTNU (2016) IEEE Senior Member (since 2011) Professional Roles encompass editorial leadership (e.g., IEEE Sensors Journal) and conference organization (e.g., General Chair for IEEE Sensor Array and Multichannel Signal Processing Workshop, 2022). He leads major funded research projects like PREFERENCE (RCN, 2023-2027) and AUTOSHIP (RCN, 2020-2028).

Andrea Arcuriمشاهده پروفایل

استاد

• Software Testing
• Software Engineering
• Cloud Computing
• +۶ مورد دیگر

Andrea Arcuri is a Professor at the School of Economics, Innovation and Technology within Kristiania University of Applied Sciences . His research focuses on Software Testing , Software Engineering , and Cloud Computing , with a particular emphasis on automated testing techniques for web APIs. Specialized in RESTful, GraphQL, and RPC API fuzzing Developer of the open-source EvoMaster testing tool Pioneer in integrating evolutionary algorithms and symbolic execution for test generation Active in bridging academic research with industrial software testing practices His recent publications show a strong focus on Search-Based Software Testing (SBST) , Automated Test Generation , and Industrial Adoption of Testing Technologies . He has contributed extensively to improving testability through mock generation and database handling in API testing. While no formal scientific awards are listed in the public records analyzed, his work has been consistently published in top-tier software engineering venues since 2013. The articles demonstrate increasing sophistication in fuzzing techniques, with recent extensions to handle complex dependencies like MongoDB and SQL databases.

Ferreira Joao Carlosمشاهده پروفایل

استاد

• Artificial Intelligence
• AI in Health and Medicine
• AI in Energy and Transportation
• +۶ مورد دیگر

Joao Carlos Amaro Ferreira is a Professor at the Faculty of Logistics, Molde University College (HiMolde), Norway. He holds PhDs in Computer Engineering and Industrial Engineering from the Technical University of Lisbon and the University of Minho, respectively. His research focuses on Artificial Intelligence (AI) applications in healthcare, energy, transportation, IoT, blockchain, and smart cities. He has led over 40 projects, including 6 as Principal Investigator, and contributed to international conferences like OAIR and INTSYS. He served as IEEE CIS President (2016-2018) and is an IEEE Senior Member since 2015. His academic contributions span AI-driven solutions for public sector informatics, healthcare data quality, and cybersecurity. He actively participates in European projects such as e-Hospital4Future and explores blockchain applications in supply chains and medical records. Ferreira leads the ABC-AI research group, emphasizing ethical and applied AI. His work bridges academia and industry through projects like gamification systems for eco-driving and AI in fisheries traceability. Recent publications highlight AI's role in cardiovascular disease detection, emergency department optimization, and blockchain-enhanced healthcare interoperability. He collaborates internationally, co-editing journals like Applied Sciences , and has authored patents in edge computing for maritime monitoring.

• Metal Forming
• Aluminum Alloys
• Product Development
• +۳ مورد دیگر

Torgeir Welo is a Professor at the Department of Mechanical and Industrial Engineering , Norwegian University of Science and Technology (NTNU) . He specializes in metal forming , particularly aluminum alloy structures , with a focus on plastic bending behavior , dimensional stability , and 3D forming technologies . His research also encompasses Lean Product Development , emphasizing knowledge reuse and maximizing customer value in automotive and aerospace applications. Key Research Areas : Metal Forming, Aluminum Processing, Springback Control, Lean Development, Additive Manufacturing, Material Substitution Teaching : Courses on Aluminum Technology , Metal Forming Analysis , and Machine Element Design Publications (15 most recent): Focus on springback monitoring , charge weld evolution , flexible forming , machine learning applications , and circular economy frameworks in metal manufacturing.

• Maritime safety management and leadership
• Maritime accident and casualty analysis
• Maritime Autonomous Surface Ships (MASS)
• +۳ مورد دیگر

Tae Eun Kim is an Associate Professor in Maritime Safety Management at UiT The Arctic University of Norway, working within the Department of Technology and Security. Her research, teaching, and industrial collaboration focus on maritime safety and human factors, with particular expertise in maritime safety management, accident analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. Dr. Kim's research spans four interconnected domains: maritime safety management and leadership, maritime accident and casualty analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. She has developed assessment instruments like the Safety Leadership Self-Efficacy Scale (SLSES) and conducted STAMP-based causal analyses of maritime accidents. Her work on MASS addresses safety challenges in mixed navigational environments and examines leadership competencies for autonomous shipping operations. Her human factors research explores how technological advancements impact navigators' performance, crew dynamics, and safety outcomes, including gender parity issues in the maritime industry. Dr. Kim's publication record reveals a strong focus on the intersection of maritime safety, technology, and human performance. Her recent work increasingly addresses autonomous shipping technologies, with numerous publications on AI decision transparency, learning analytics in maritime simulator training, and multi-modal data analysis for nautical skill development. She has conducted systematic reviews on simulator training approaches and scenario design, contributing significantly to methodology development in maritime education and training. Her research demonstrates a clear trajectory toward integrating emerging technologies with traditional maritime safety practices as the industry transitions toward greater automation. Dr. Kim is actively involved in several significant research projects, including the i-MASTER EU Horizon Europe Research and Innovation Project, the REFRAME project, and the SPRICE project (Multidisciplinary approach for spray icing modelling). She is a member of both the Advanced Maritime Ship Operations research group and the Maritime Safety Science (MARSCI) Research Group, demonstrating her commitment to collaborative research in maritime safety science. Dr. Kim teaches several specialized courses at UiT, including SVF-3206 Safety Management and Accident Investigation, TEK-3014 Navigation Technology, MFA-2100 Maritime Digitalization, MFA-8010 Maritime HTO (Human-Technology-Organisation) and Innovation, and MFA-2018 Maritime Administration and Leadership. Her teaching portfolio reflects the interdisciplinary nature of her expertise, bridging engineering, safety science, and organizational behavior in maritime contexts.

• Control Theory
• Model Predictive Control
• Power Electronics
• +۳ مورد دیگر

Morten Hovd is a Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His work focuses on advanced control systems, particularly in model predictive control, optimization, and power electronics. He has contributed to control design for uncertain systems, bilinear models, and modular multilevel converters. Research Interests Control Theory and Model Predictive Control (MPC) Optimization Techniques in Control Systems Power Electronics and Smart Grid Applications Stability Analysis of Hybrid and Discrete-Time Systems Teaching TTK4210 - Advanced Control of Industrial Processes TK8118 - Mini-seminar in Cybernetics

Manuel Linares Alegretمشاهده پروفایل

استاد

• High-energy astrophysics
• Compact objects in binary systems
• Neutron stars
• +۷ مورد دیگر

Manuel Linares Alegret is a Professor in the Department of Physics at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway, where he has been employed since September 2021. He also holds an Associate Professor position at the Polytechnic University of Catalonia (UPC) in Barcelona, Spain, since 2018. His research focuses on high-energy astrophysics with particular emphasis on neutron stars, black holes, white dwarfs, and compact objects in binary systems. Dr. Linares earned his Physics Degree from Universitat de Barcelona (1998-2004) followed by a PhD in Astronomy from Universiteit van Amsterdam (2004-2009). His subsequent career includes prestigious fellowships including Rubicon Fellow at MIT (2009-2012), IAC Fellow (2012-2017), and Marie Curie Fellow at UPC (2017-2018). His research interests primarily center on compact binary systems, particularly millisecond pulsars known as 'spiders' (including black widows and redbacks), neutron star physics, accretion flows, thermonuclear bursts, and the search for super-massive neutron stars. His work combines observational astronomy with theoretical modeling to understand extreme physics in these systems. He leads the LOVE-NEST project, which investigates compact binary millisecond pulsars to find the most massive neutron stars and understand the interaction between accretion flows, pulsar winds, and neutron star magnetospheres. An analysis of his recent publications reveals a strong focus on spider pulsar systems, with particular attention to mass measurements, orbital dynamics, irradiation effects, and the relationship between accretion and rotation-powered states. His work spans multiple observational wavelengths including optical, X-ray, and radio, often utilizing data from major telescopes and space observatories. ERC Consolidator Grant for LOVE-NEST project Marie Curie Fellow IAC Fellow Rubicon Fellow Dr. Linares has supervised numerous students at various levels, including PhD candidates, Master's students, and undergraduate research projects. He currently leads a substantial research team under the LOVE-NEST project, which has received 2M EUR in funding. His group includes multiple postdoctoral fellows and PhD candidates working on various aspects of compact object astrophysics. He teaches Observational Astrophysics (FY3215) at NTNU and has previously taught Quantum Physics and Physics I at UPC. He is the principal investigator of the LOVE-NEST (Looking for Super-Massive Neutron Stars) research group at NTNU, which focuses on compact binary millisecond pulsars. This team conducts research using multiple observational facilities worldwide and collaborates with international groups including those at the Instituto de Astrofísica de Canarias and the University of Manchester.

• Multi-Phase Flow
• Turbulence
• Lagrangian Dynamics
• +۳ مورد دیگر

Rohith Jayaram is a Postdoctoral Fellow in the Department of Chemical Engineering at the Norwegian University of Science and Technology (NTNU), specializing in multi-phase flows and turbulence dynamics. His research focuses on particle-laden flows, bubble-turbulence interactions, and computational fluid dynamics. Education: PhD in Particle suspensions from NTNU MSc in Aerospace Mechanics from ISAE-SUPAERO, France BEng in Mechanical Engineering from BMS College of Engineering, India His work investigates Lagrangian dynamics of solid particles and spheroids in evolving Taylor-Green vortex flows, with recent emphasis on bubble-turbulence interactions. He develops numerical algorithms for flow simulations and contributes to turbulence modeling in both 2D and 3D systems. Research trends include computational modeling of multi-phase flows, DNS validation of particle behavior in unsteady vortices, and extension to spheroid alignment dynamics. Publications span leading journals like Physics of Fluids and Physical Review E . Scientific Awards: Selected as Featured Article in Physics of Fluids (2020) Outreach activities include conference lectures at the European Fluid Dynamics Conference (2024) and European Turbulence Conference (2019). Contact: 238 Kjemiblokk 5 Gløshaugen, Trondheim; rohith.jayaram@ntnu.no

Lilja Øvrelidمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +۳ مورد دیگر

Lilja Øvrelid is a Professor at the Department of Informatics, University of Oslo, leading the Language Technology Research Group. Her research focuses on syntactic and semantic text processing using machine learning techniques such as dependency parsing, negation analysis, and sentiment analysis. She teaches courses including IN1140: Introduction to Language Technology , IN5550: Neural Methods in NLP , and INF5830: Natural Language Processing . Her academic interests span natural language processing, machine learning, and computational linguistics, with a particular emphasis on Norwegian language technology. Recent publications highlight work in sentiment analysis (including patient feedback), event extraction from Norwegian news, benchmarking language models, emotion analysis for under-resourced languages (Pashto, Farsi-Dari), and bias detection in multilingual models. She actively contributes to the development of Norwegian language resources such as NorBench, NorQuAD, and NoReC. Current projects include BigMed and SIRIUS , focusing on biomedical text mining and AI infrastructure. Collaborations with colleagues like Erik Velldal, David Samuel, and Vladislav Mikhailov are frequent in her work. Despite no explicit mention of scientific awards, her contributions to NLP and computational linguistics are substantial through publications, datasets, and tool development.

• Laser Physics
• Nonlinear Optics
• Fiber Lasers
• +۵ مورد دیگر

Prof. Irina T. Sorokina is a Professor of Physics at the Norwegian University of Science and Technology (NTNU), leading the Laser Physics Group. Her research focuses on ultrafast lasers, mid-IR photonics, and their applications in materials processing, quantum computing, and spectroscopy. She holds a prestigious Fellowship from the Optical Society of America (2006) and the IEEE Snell Premium Award (2004). Research Interests: Her work spans laser physics, nonlinear optics, and solid-state laser technologies. Key areas include femtosecond laser development, mid-IR frequency combs, and advanced material processing techniques using ultrafast pulses. Recent projects include subsurface silicon modification, all-fiber mid-IR laser systems, and applications in quantum networks. Publications: Her 15 most recent articles (2023–2025) emphasize mid-IR scaling, dissipative solitons, and novel laser architectures. These contributions highlight advancements in energy-efficient laser systems and their industrial applications. Awards: Fellow of the Optical Society of America (2006) IEEE Snell Premium Award (2004) Co-founder of NTNU spin-off ATLA Lasers AS Advising & Innovation: Supervises graduate students in laser physics and materials science. Her lab collaborates on spin-off ventures and advanced projects like subsurface silicon processing for photovoltaics and quantum sensors. Research also extends to energy-dense battery materials and supercontinuum generation in chalcogenide fibers. Labs/Teams: Heads the Laser Physics Group at NTNU, focusing on mid-IR ultrafast lasers and their interdisciplinary applications. Collaborates internationally on projects like double-frequency comb spectroscopy and femtosecond laser writing in ZnS crystals.

Tor Helge Aasمشاهده پروفایل

استاد

• Innovation Management
• Digital Servitization
• Service Innovation
• +۹ مورد دیگر

Tor Helge Aas is a Professor at the Department of Management and Innovation, School of Business and Law, University of Agder, and holds a part-time position as Professor II at Kristiania University College. He is the Director of the Executive MBA program at UiA and actively contributes to research and teaching in innovation management. His affiliations include the Research Centre for Studies of Innovation for Sustainable Transition (RIST) and the ISPIM Scientific Panel. His research interests focus on innovation management , particularly in digital servitization, service innovation, innovation processes, collaboration for innovation, and management control. He examines how organizations in manufacturing and service sectors transition to service-oriented business models through digital platforms and ecosystem collaboration. The recent publications highlight a strong trend in digital servitization , platform-based innovation , and human-technology interaction in Industry 5.0. His work spans business model innovation, legitimacy in smart services, and coopetition in R&D projects, with a consistent focus on organizational transformation and sustainable innovation. Scientific Awards and Recognitions: No explicit awards mentioned in the text. Advising and Grants: He has supervised Master’s and PhD students (implied through academic roles). Actively involved in Horizon 2020 projects: OpenInnoTrain (Work Package Manager) and REDI program. Research funded by EU frameworks, indicating competitive grant acquisition. Labs and Research Teams: Member of RIST – Research Centre for Studies of Innovation for Sustainable Transition . Active in ISPIM (International Society for Professional Innovation Management) Scientific Panel. Collaborates extensively with researchers like Anne-Laure Mention, Katja Maria Hydle, and Karl Joachim Breunig.

• Tsetlin Machines
• Reinforcement Learning
• Machine Learning
• +۳ مورد دیگر

Xuan Zhang is an Associate Professor at the Department of Information and Communication Technology, University of Agder. His research focuses on Tsetlin Machines, learning automata, and their applications in machine learning, computer vision, and hyperspectral imaging. Research Trends: Zhang’s recent work includes developing interpretable machine learning models (e.g., Tsetlin Machines), optimizing convolutional architectures for image processing, and applying automata theory to solve multi-armed bandit problems and channel selection in cognitive networks. His field spans theoretical analysis and practical implementations in AI, remote sensing, and health informatics. Scientific Contributions Co-developed advanced Tsetlin Machine variants for XOR/NOT operator convergence, disease forecasting, and image restoration Published in journals like IEEE Transactions on Pattern Analysis and Machine Intelligence , Information Sciences , and Applied Intelligence Explored Bayesian pursuit algorithms, hierarchical learning automata, and particle swarm optimization techniques Contact: xuan.zhang@uia.no

• Machine Learning
• Artificial Intelligence
• Medical Imaging
• +۴ مورد دیگر

Elisabeth Wetzer is an Associate Professor in Machine Learning at the Department of Physics and Technology, UiT The Arctic University of Norway. Her research bridges artificial intelligence with healthcare applications, focusing on multimodal image registration, bias mitigation in AI, and physics-informed learning models. Current Role: Associate Professor, Machine Learning Group Research Themes: AI ethics, medical imaging, cross-modal representations, algorithmic fairness Her recent work explores technical challenges in PET imaging analysis and societal implications of AI bias. Collaborative projects span medicine, mathematics, and computer science disciplines. Key scientific contributions include: Physics-informed deep learning for PET image data Studies on multi-task learning efficacy in medical classification Research on gender bias in algorithmic systems She actively participates in diversity initiatives and public outreach, including presentations at Nobel laureate conferences and media engagements on AI ethics.