Amir Taherkordi is a Professor in the Networks and Distributed Systems group at the Department of Informatics, University of Oslo, Norway. His research focuses on resource-efficiency, scalability, adaptability, and mobility in distributed systems for emerging technologies like IoT, Fog/Edge/Cloud Computing, and Cyber-Physical Systems (CPS). University: University of Oslo Department: Informatics Academic Rank: Professor His research spans IoT, Edge/Fog Computing, and Cyber-Physical Systems, emphasizing energy efficiency, privacy preservation, and self-adaptive architectures. Key areas include network traffic classification, computation offloading, and federated learning applications in vehicular systems. Recent publications highlight advances in latency-aware IoT data transmission , federated vehicular networks , energy-efficient wireless charging , and privacy-preserving data integration . These works often integrate machine learning with network optimization. Projects include the CPS Lab at UiO, DILUTE (Fluid Service Abstraction), and the Gemini Centre on IoT . He collaborates on initiatives like PACE for energy informatics curricula development.
Gudmund Grov is an Associate Professor in Digital Security at the Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo. His research focuses on cybersecurity, with emphasis on anomaly detection, explainable AI, and security modeling. He is actively contributing to advancements in autonomous cyber defense and machine learning applications in security operations. His research interests span Digital Security , Network Anomaly Detection , Explainable AI (XAI) , Machine Learning for Cyber Defense , Security Modeling , and Risk Modeling in Enterprise Architecture . His work integrates formal reasoning with practical modeling to enhance system security and interpretability. The recent publications reflect a strong trend towards intelligent and interpretable cybersecurity systems, combining deep learning with formal methods to detect and explain network threats. His work bridges the gap between theoretical modeling and real-world security applications, particularly in autonomous defense and labeled dataset generation for APTs. No scientific awards were mentioned in the provided text. Gudmund Grov collaborates extensively with researchers in cybersecurity and formal methods. While specific grants and advising roles are not detailed, his co-authorship on multiple projects indicates active research supervision and collaboration. He is involved in developing frameworks for labeled data generation, contextual anomaly detection, and explainable alerts in SOC environments. There is no explicit information about labs or research teams, but his work suggests involvement in cybersecurity research groups at the University of Oslo focusing on AI-driven security and formal verification.
Bruno Dzogovic is an Assistant Professor at Oslo Metropolitan University's Faculty of Technology, Art and Design, specifically within the Department of Computer Science. His research focuses on 5G/6G networks, cybersecurity, cloud computing, and software engineering. 5G/6G mobile networks Cloud computing and virtualization Cyber defense systems Wireless communication Industrial networks Biomedical Wireless Sensor Networks His recent work explores secure network slicing, container technologies, and applications of 5G in healthcare and elderly care systems. He is an active member of the Autonomous Systems and Networks (ASN) research group, contributing to advancements in digital forensics and vulnerability assessment for modern communication systems.
Mohammad Derawi is a Professor in the Department of Electronic Systems at the Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU), Gjøvik campus. He leads the Smart Wireless Systems (SWS) research group and serves as the scientific leader of the IoT Lab at NTNU Gjøvik. Educational Background: PhD in Information Security from NISLab (Norway) and CASED (Germany) BSc and MSc in Informatics from DTU (Denmark) His research interests span smart wireless systems, Internet of Things (IoT), information security with a focus on biometric authentication, digital electronics, applied machine learning for activity recognition, and e-learning technologies. His work integrates cybersecurity, embedded systems, and data science to develop secure and intelligent IoT solutions for real-world applications. The recent publications highlight a strong trend in mmWave-based sensing for unmanned aerial systems, RF fingerprinting for secure identification, IoT security frameworks, and machine learning applications in education and human resource analytics. His research bridges theoretical innovation with practical implementation, particularly in smart cities, healthcare, and transportation. Scientific Awards and Recognition: Invitation to the Crown Prince and Princess's 50th birthday celebration, 2023 Study Quality Award, NTNU, 2017 Norway’s Youngest Professor Award, 2016 Denmark’s youngest M.Sc. engineering award, 2009 IEEE Commendation for Young Professionals Volunteer, 2011 Multiple best paper awards from IEEE, ACM, and Springer Mohammad Derawi has been involved in several funded research and development projects, including IoT Safetraffic (RFF Inland), Ambulance Drone (NTNU Vice-Rector), Wireless ECG (Innovation Norway), biometric handgun security (RFF Innlandet), and the EU Framework 7 TURBINE project. He mentors students and collaborates with international researchers, contributing significantly to both academic and applied domains. His leadership in the SWS group and IoT Lab fosters innovation in wireless and secure embedded systems. He is actively engaged in laboratory and team-based research, particularly through the Smart Wireless Systems group and the IoT Lab, focusing on developing secure, intelligent, and scalable solutions for next-generation wireless applications.
Professor Sule Yildirim Yayilgan is a distinguished academic at the Department of Information Security and Communication Technology (IIK) within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) in Gjøvik. She has held the position of Professor since 2020, following her tenure as Associate Professor from 2016-2020. Dr. Yayilgan previously served as Head of Department between 2005-2009 at HIHM (now part of NTNU). Her academic journey spans over 30 years in teaching and research, with significant contributions to interdisciplinary fields bridging AI, cybersecurity, and privacy. Her educational background includes a MSc in Computer Engineering (1995) and a PhD in Artificial Intelligence and Computer Science (2002). Dr. Yayilgan has led and participated in numerous international research projects funded by EU Horizon 2020, Eurostars, Erasmus+, and various Norwegian research councils. She currently leads the MR PET (Multidisciplinary Research group on Privacy and data protEcTion) research group and serves on the scientific board of NTNU's strategic area in Data Science. Dr. Yayilgan's research spans multiple domains with a unifying focus on ethical, legal, and privacy-preserving AI systems. Her work addresses critical challenges in health, energy, education, and security sectors through advanced AI methodologies. She has published over 100 journal and conference papers, with recent work focusing on hate speech detection, border security technology acceptance, smart grid security, and explainable AI applications. Her publications demonstrate a strong emphasis on practical implementations that balance technical innovation with societal considerations. As an active research leader, she currently oversees several significant projects including VIPA-DELF (vineyard disease detection using federated learning), METICOS (border control technology monitoring), CINELDI (intelligent electricity distribution), and AQMA (air quality monitoring). She also serves on multiple ethics boards and research integrity committees, reflecting her commitment to responsible innovation. Dr. Yayilgan has supervised numerous graduate students throughout her career, advising 41+2 (in progress) MSc students and 3+2 (periods) +6 (in progress) PhD candidates. Her administrative contributions include membership in NTNU's Research Integrity Committee, the Trondheim ACM Women Chapter, and various project management boards for EU-funded initiatives. She maintains active professional affiliations with IEEE, the International Association for Pattern Recognition, and COST Actions focused on language technologies and security research.
Audun Jøsang is a Professor of Cybersecurity at the University of Oslo and holds a Visiting Professor position at Queensland University of Technology (QUT) . His work focuses on trust and reputation systems in digital environments, with notable contributions to subjective logic —a mathematical framework for reasoning under uncertainty. Education : MSc in Information Security from Royal Holloway, University of London , MSc and PhD in Telecommunications from Norwegian University of Science and Technology (NTNU) Books : Subjective Logic: A Formalism for Reasoning Under Uncertainty (2016), Cybersecurity: Technology and Governance (2011) His research spans cybersecurity , artificial intelligence , and risk assessment , with applications in online marketplaces , social media , and decision-making under uncertainty . He has developed mathematical models for uncertainty-aware influence propagation and competitive information spread using subjective logic. Audun Jøsang’s work bridges theoretical foundations and industrial applications of computational trust and security analytics . His recent publications explore ethical AI , fair federated learning , and dynamic intelligence assessment for artificial general intelligence development.
Anna Mavroudi is an Associate Professor at the Department of Education , University of Oslo , with a focus on ICT in Learning , Learning Analytics , and University Pedagogy . She previously held positions at Norwegian University of Science and Technology (NTNU) and Royal Institute of Technology (KTH), Sweden. Education: PhD in Technology-Enhanced Learning (Open University of Cyprus, 2009–2015) Awards: Best Paper at ICALT (2018) and EDUCON (2018) Research Interests: Learning Analytics, Adaptive Learning, Ethical AI in Education Her recent publications address AI ethics , synthetic data generation , and higher education pedagogy . She contributes to STEM education , digital literacy , and teacher professional development through empirical studies and design frameworks. Projects: BraStart, PATHWISE, Use of Digital Technology in Higher Education She is affiliated with the Living and Learning in the Digital Age (LiDA) research group and serves as a peer reviewer for journals like Nordic Journal of Digital Literacy and Interactive Learning Environments .
Amirhosein Taherkordi is an Associate Professor at the Department of Information Security and Communication Technology within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). His academic profile shows continuous research activity with publications spanning from 2011 through 2025, indicating an established career trajectory in computer science and networking research. Dr. Taherkordi's research interests focus on addressing fundamental challenges in distributed computing environments, particularly in resource-constrained scenarios. His work spans Internet of Things (IoT) systems, edge and fog computing architectures, network security protocols, and machine learning applications for network traffic analysis. He has made significant contributions to energy-efficient data collection protocols for wireless sensor networks, privacy-preserving techniques for industrial IoT systems, and communication-efficient approaches for federated learning in vehicular networks. His research consistently bridges theoretical innovation with practical implementation, addressing real-world challenges in smart transportation, environmental monitoring, and industrial automation systems. An analysis of Dr. Taherkordi's recent publication trends (2023-2025) reveals a strong emphasis on federated learning applications for vehicular networks (FedAGL, FedAPT), energy-efficient IoT data collection strategies (eU2U, ECMSH), and the integration of transfer learning with edge computing for transportation applications (TELEGAIT, FOGFLEET). His work increasingly addresses the critical tension between computational efficiency and accuracy in distributed systems, with growing applications in environmental monitoring (PmForecast) and circular economy frameworks. The interdisciplinary nature of his research spans computer science, electrical engineering, and environmental science domains. Dr. Taherkordi maintains an active collaborative research profile, working with international colleagues across multiple institutions as evidenced by his diverse publication venues including IEEE Transactions, ACM journals, and various conference proceedings. His research program appears to be well-established with consistent funding, though specific grant details aren't provided in the available text. He likely leads or contributes significantly to research groups focused on networking, IoT, and edge computing at NTNU, mentoring students in these emerging technology domains.
Linga Reddy Cenkeramaddi is a **Professor** in the Department of Information and Communication Technology at the University of Agder (UiA), Norway. He holds a PhD in Electrical Engineering from NTNU (Trondheim, Norway) and Master’s degrees from IIT Delhi and IIT Chennai. His research focuses on Cyber-Physical Systems (CPS), Autonomous Systems, Robotics, AI/ML, Wireless Sensor Networks, and 5G/6G-enabled technologies. He leads projects such as LUCAT (UAV communication tracking) and INCAPS (Indo-Norwegian collaboration in CPS). **Education**: PhD (NTNU), MSc in Physics (IIT Chennai), MSc in Integrated Electronics (IIT Delhi). **Research Interests**: Energy-efficient wireless communication, autonomous vehicles, edge intelligence, mmWave sensing, and smart cities. **Teaching**: Courses include embedded systems, mmWave sensing, and wireless prototyping. **Key Contributions**: Developed low-power embedded systems, contributed to UAV communication protocols, and pioneered AI-driven healthcare solutions. **Grants**: Co-PI in the INMOST offshore mechatronics project. **Labs/Teams**: Autonomous and Cyber-Physical Systems (ACPS), Electronics and IoT (E&IOT), Intelligent Mechatronics (iTron). His work bridges academia and industry, impacting healthcare, smart agriculture, and environmental monitoring. Future research includes multi-modal sensing, multi-agent systems, and 6G communication integration with AI.
Roman Vitenberg is a Professor at the Department of Informatics, University of Oslo. His research focuses on distributed systems, blockchain, privacy, and middleware. He leads the Blockchain Lab, which runs Norway's production node in the EBSI network. Key contributions include work on fault-tolerant overlays, privacy-preserving frameworks for genomic data, and blockchain applications in healthcare. He teaches courses on distributed systems and blockchain technologies. Education: Ph.D. from Technion (Israel Institute of Technology), M.Sc. from Hebrew University of Jerusalem. Previous roles include postdoc at UC Santa Barbara and researcher at IBM. Research Interests: Distributed algorithms, blockchain systems, cloud/fog computing, dependability, and privacy-preserving techniques. Awards: Best Demo Award at ACM DEBS 2014, Best Paper Award at ACM DEBS 2016, Most Influential Paper Award (2007 paper recognized in 2017). Grants & Projects: PriTEM (privacy-preserving energy management), Conserns, Credence, and EBSI-NE (operating Norway's EBSI node). Advising: Supervised over 10 PhD and master students, including notable alumni at Spotify and Max-Planck Institute. Publications: Over 100 peer-reviewed articles in top venues like IEEE Transactions, ACM conferences, and blockchain-focused journals.
Basel Cat is a Professor and Head of the Department of Information Security and Communication Technology at NTNU's Faculty of Information Technology and Electrical Engineering. His research focuses on cybersecurity, information security assurance, and innovative approaches to cyber range technologies. Key areas include vulnerability analysis, privacy protection, and AI-driven security solutions. Research Interests Cybersecurity incident triage and attack chain analysis Quantitative security evaluation models for web and cloud services Automated vulnerability injection in source code IoT security and cognitive digital twin architectures Adversarial AI applications in cybersecurity exercises Publications highlight advancements in cybersecurity education, attack-defense scenario modeling, and the integration of AI/LLMs in security frameworks. Recent work explores frameworks for evaluating cloud services and OWASP-aligned web application security standards. Collaborations involve development of hybrid IoT cyber ranges and frameworks for security assurance metrics. His research has been featured in top-tier journals like Computers & Security and Journal of Information Security and Applications .
Mads Lund Pedersen is a Researcher at the University of Oslo (UiO) and Norment, affiliated with the Department of Cognitive and Clinical Neuroscience. His academic background includes a Dr.philos. (PhD) in Cognitive Neuroscience from UiO (2017) and a Master's in Cognitive Neuroscience (2012). He has held postdoctoral positions at UiO (2017–2020) and was a visiting scholar at Brown University’s Laboratory of Neural Computation and Cognition (2017–2019). His research focuses on computational modeling of decision-making processes in psychiatric and neurological disorders, particularly using reinforcement learning and drift-diffusion models. Key interests include understanding reward sensitivity in addiction, cognitive control mechanisms in adolescence, and the neural basis of psychiatric conditions like depression and psychosis. Collaborations include institutions such as Brown University, Washington University in St. Louis, Harvard Medical School, and the Central Institute of Mental Health in Mannheim. His work integrates neuroimaging, computational models, and genetic data to explore mental health biomarkers and comorbidity mechanisms. Recent projects include longitudinal studies of brain structure in psychosis, normative cognitive trajectories in youth, and the impact of interventions like attention bias modification. Pedersen’s contributions span over 30 peer-reviewed articles in journals like Biological Psychiatry , NeuroImage , and Journal of Cognitive Neuroscience .
Woldaregay, Ashenafi Zebene is a researcher at UiT The Arctic University of Norway, affiliated with the Faculty of Health Sciences and the Department of Clinical Medicine. His work bridges digital health, artificial intelligence, and clinical applications, particularly in diabetes management and infectious disease surveillance. He is a key contributor to the EDMON (Electronic Disease Surveillance and Monitoring Network) project, which leverages self-recorded health data from people with Type 1 diabetes for early outbreak detection. PhD in Digital Health / Health Informatics (2021) Master’s in Electronic Disease Surveillance (2016) His research focuses on applying machine learning, data science, and AI to solve pressing healthcare challenges. Key areas include blood glucose pattern analysis in diabetes, anomaly detection, mHealth adoption, wearable technology, and syndromic surveillance. He has developed models for infection detection, surgical risk prediction, and deidentification of clinical text. His work emphasizes real-world applicability, patient engagement, and data privacy. The most recent articles show a strong trend toward transformer models, synthetic data, and instruction-guided NLP in clinical contexts, alongside continued work in mHealth usability, caregiver support, and personalized health monitoring. His publications span journals in health informatics, medical informatics, and digital health, reflecting interdisciplinary collaboration. Scientific contributions include: Development of the EDMON system for real-time infection monitoring Creation of datasets for wearables and mHealth motivation factors Systematic reviews on reinforcement learning in diabetes and AI in healthcare security Innovation in cluster detection algorithms (K-CUSUM) for outbreak detection While direct information on grants and advising is not provided, his role as a doctoral candidate and co-author on numerous student-led studies suggests involvement in research mentoring. He collaborates extensively with researchers such as Gunnar Hartvigsen, Eirik Årsand, and Karl Øyvind Mikalsen, indicating membership in a large, active digital health research group. He is involved in a multidisciplinary research lab focused on digital health innovation, mHealth systems, and AI-driven clinical decision support. The team works on real-time monitoring, data privacy, and user-centered design of health technologies, with applications in chronic disease management and public health surveillance.
Anis Yazidi is an Associate Professor at the Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, where he leads research in the Research Group for Digital Signal Processing and Image Analysis. His academic profile demonstrates significant contributions to artificial intelligence, machine learning, and signal processing with over 50 publications between 2021-2025 in high-impact venues including IEEE Transactions, Frontiers journals, and AAAI proceedings. Professor Yazidi's research spans multiple interconnected domains with particular emphasis on Tsetlin Machines, deep learning for medical applications, and signal processing theory. His work bridges theoretical foundations with practical implementations, developing novel frameworks like DREAMS for EEG analysis with model card reporting and interpretable methods for ECG classification. His contributions to learning automata theory, particularly in convergence analysis of Tsetlin-based algorithms, represent significant theoretical advances. The research portfolio also extends to cybersecurity applications of AI for IoT protection, agricultural technology for plant disease detection, and renewable energy modeling for wind-speed statistics. Yazidi's publication record reveals a strong interdisciplinary approach, with collaborations across computer science, neuroscience, medical diagnostics, and engineering disciplines. His recent work shows increasing focus on trustworthy AI systems, ethical considerations in medical applications, and specialized neural architectures tailored for specific data modalities including EEG, ECG, and eye-tracking data. The research demonstrates both theoretical rigor in algorithm development and practical implementation for real-world problems. Professor Yazidi maintains an active collaboration network with researchers across the Department of Informatics at UiO, particularly with Pedro Lind, Hugo Lewi Hammer, and Paal Engelstad, while also engaging in international collaborations. His work contributes significantly to both the theoretical foundations of learning systems and their practical implementation in diverse application domains from healthcare to renewable energy.
Diana Saplacan Lindblom is a Researcher at the University of Oslo's Department of Informatics, Faculty of Mathematics and Natural Sciences. She is a member of the Robotics and Intelligent Systems Research Group (ROBIN) and actively contributes to the Vulnerability in Robot Society (VIROS) research project (2021-present) and the Ethical Risk Assessment of Artificial Intelligence in Practice (ENACT) project (2023-present). Dr. Saplacan received her Ph.D. from the University of Oslo in 2020 with a thesis titled "Situated abilities: Understanding Everyday Use of ICTs" from the Design of Information Systems (DESIGN) Research Group. During Spring 2023, she was a visiting researcher at the Human-Robot Interaction Lab, Department of Social Informatics, Kyoto University, Japan, and a guest researcher at Tohoku University's Frontier Research Institute for Interdisciplinary Sciences. Her research focuses on user studies in Human-Robot Interaction (HRI) and Human-Robot cooperation, with particular emphasis on digitalization of home- and healthcare services, robots as welfare technologies, and ethics regarded through Universal Design principles. She investigates privacy, safety, and security aspects related to robots in healthcare settings, bridging legal and technical considerations. Her work often employs qualitative methods including story dialogue techniques to understand user perspectives and professional reactions to emerging technologies. Analysis of her recent publications reveals a strong interdisciplinary approach connecting computer science, social sciences, and healthcare. Her work spans technical aspects of robotics, ethical considerations in AI implementation, and practical user studies across diverse populations including elderly care recipients and healthcare professionals. She frequently examines how Universal Design principles can be applied to social and assistive robots to ensure accessibility and inclusion. Dr. Saplacan has received notable recognition including an Honorable Mention at HRI (2024) and being named among "Women changing the field of AI in Norway" (2021, 2022). She has also earned Best Paper Awards at ACHI-IARIA (2018, 2020) and a Best Paper Finalist Award at ARSO (2021). HRI Honorable Mention (2024) Women changing the field of AI in Norway (2021, 2022) Best Paper Finalist Award - ARSO (2021) Best Paper Award, ACHI - IARIA (2020) Best Paper Award, ACHI - IARIA (2018) Dr. Saplacan has served as co-supervisor for Ph.D. candidates Adel Baselizadeh (completed 2024) and Marieke van Otterdijk (defense scheduled for December 2024). Her research is supported through collaborations with multiple academic partners including SINTEF, HIOF, and NTNU, as well as industry partners such as DNB, Posten, NAV, Medsensio, and Hypatia Learning. She actively contributes to standardization efforts as a member of Standards Norway Committee on AI & Ethics (WG3) and the IEEE Artificial Intelligence Standards Committee. She is a key contributor to the ROBIN research group's work on healthcare robotics and leads efforts in the UD-Robots project, which examines how universal design principles can be applied to robotics. Her work with the Norwegian Council for Digital Ethics and participation in international workshops demonstrates her commitment to shaping ethical frameworks for emerging technologies.
