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Lina Bertling Tjernberg is a Professor at the Department of Electrical Engineering, KTH Royal Institute of Technology, and Deputy Head of the School of Electrical Engineering and Computer Science (EECS) with responsibility for research conditions and impact. She served as Director of KTH's Energy Platform during 2018-2024 and holds memberships in IVA (Swedish Royal Academy of Engineering Sciences) and the IEEE Power & Energy Society. Research Focus: Applying mathematics (statistics, optimization, life cycle assessment) to enhance reliability and predictive maintenance in electric power systems, with emphasis on future electricity grids integrating microgrids, battery storage, HVDC, nuclear/pumped/hydro/wind/solar power, hydrogen, and electrified transport. Collaborations: Engaged with Comillas Pontifical University (Madrid), Addis Ababa University, Norwegian University of Science and Technology (NTNU), and IEA Wind. Key Research Trends: Recent articles highlight advancements in microgrid control (2025), SMR nuclear energy integration (2025), AI-driven asset management (2024), hydrogen sector coupling (2024), and renewable forecasting techniques (2024). Awards: 2021 Power Woman of the Year 2022 Energy Power List (Sweden’s top 20 energy influencers) Leadership Roles: Swedish Electromobility Center (SEC) board Chair of Swedish Electrical Standards (SEK Svensk Elstandard) Member, IEEE PES ISGT Europe steering committee

• Electrical Power Networks
• Predictive Maintenance
• Renewable Energy Integration
• +7 more

Zhonghai Lu is a Professor of Electronic Systems Design (specializing in Dependable and Autonomous Systems) at KTH Royal Institute of Technology, part of the Department of Electrical Engineering in the School of Electrical Engineering and Computer Science (EECS). He serves as Program Director for KTH's Embedded Systems master's program and Director of Studies at the Division of Electronics and Embedded Systems. His research focuses on Network-on-Chip (NoC), computer architecture, embedded systems, and Prognostics and Health Management (PHM) of power electronics. He leads a research group exploring in-network processing and embedded intelligence, transforming passive networks into active computational frameworks. Lu holds a BSc from Beijing Normal University (1989), MSc and PhD from KTH (2002, 2007), and an MBA in Innovation and Growth from the University of Turku (2012). He has authored over 240 scientific papers, including journal articles and peer-reviewed conferences, with notable recognitions such as Best Paper Awards at NOCS’2015 and EU HiPEAC, and a Featured Paper in IEEE Transactions on Computers (2020). He serves as Associate Editor for ACM Transactions on Architecture and Code Optimization (TACO) and has chaired major conferences like HiPEAC’2017 and NOCS’2018. His research group’s recent work includes integrating AI into hardware acceleration, fault-tolerant neural networks, and RUL estimation for power electronics using recurrent neural networks. Lu has secured grants from the Swedish Research Council and Intel Corporation and developed courses like IL2230 (Hardware Architectures for Deep Learning) and IL2233 (Embedded Intelligence), pioneering embedded AI education at KTH. Education: BSc (Beijing Normal University), MSc/PhD (KTH), MBA (University of Turku) Awards: Best Paper Awards (NOCS, EU HiPEAC), Swedish Research Council Grants, Intel Research Gifts Labs/Teams: Research Group on In-Network Processing and Embedded Intelligence

• Computer Architecture
• Embedded Systems
• Network-on-Chip (NoC)
• +7 more

Henrik Boström is a Professor of Computer Science specializing in Data Science Systems at the Division of Software and Computer Systems, KTH Royal Institute of Technology. His research focuses on trustworthy machine learning , with emphasis on conformal prediction (for confidence-calibrated predictions) and explainable AI . He is the developer of Python packages crepes (conformal classifiers/regressors) and xrf (explainable random forests). His primary research domains include: Developing robust methods for uncertainty quantification in predictive models Creating interpretable machine learning frameworks Optimizing ensemble techniques for high-dimensional data Applying ML to healthcare informatics and industrial diagnostics Analysis of his recent publications reveals strong emphasis on: (1) advancing conformal prediction theory for trustworthy AI, (2) enhancing interpretability of complex models like random forests and GNNs, and (3) developing efficient algorithms for uncertainty-aware learning in domains including healthcare, graph data, and high-dimensional regression. He serves as examiner for multiple degree projects and teaches courses including Programming for Data Science (ID2214) and Research Methodology and Scientific Writing (II2202) . He leads development of open-source tools for conformal prediction and model interpretation.

• Trustworthy Machine Learning
• Conformal Prediction
• Explainable Artificial Intelligence
• +2 more

Lars Nordström is a Professor at the Division of Electric Power and Energy Systems within KTH Royal Institute of Technology, Stockholm, Sweden. His work bridges control systems , communication networks , and power systems , with a focus on future architectures, functionality, and quality aspects of ICT for power grid operations. He has led initiatives such as the Swedish Centre of Electric Power Engineering and served as Thematic Leader for Smartgrids in KIC InnoEnergy. In 2014, he was a Visiting Professor at Washington State University. Education : Ph.D., MSc.EE Nordström's research explores the intersection of smart grids , machine learning , and cybersecurity for power systems. Key areas include: Wide-Area Monitoring and Control (WAMC) systems Decentralized control strategies for DC microgrids Impedance modeling using neural networks Data-driven methods for islanding detection ICT reliability and protocol design for grid operations His recent publications emphasize machine learning applications in power systems, including LSTM networks for EV charging management, graph attention networks for stability monitoring, and digital twin approaches for cyber-attack mitigation. These works span disciplines such as Smart Grids, Power Electronics, and Data Science. Scientific Recognitions : Senior Member, IEEE Senior Member, CIRED Senior Member, Cigre Past Chairman, Swedish IEC TC57 Mirror Committee Nordström actively teaches and examines graduate courses like Communication and Control in Electric Power Systems and Computer Applications and Machine Learning in Electric Power Systems . His work influences industry practices through collaborations on digital substations, energy market analysis, and resilience strategies.

• Power System Control
• Smart Grids
• Communication Systems
• +11 more

Mario Romero is an Associate Professor in Visualization at the Department of Computational Science and Technology (CST), KTH Royal Institute of Technology. He leads the InfraVis national research infrastructure for data visualization and is a Digital Futures Faculty member. His roles include national technical manager of InfraVis, member of the Executive Committee of Digital Futures, and Associate Director for Seminars & Workshops. Education: PhD in Computer Science (Georgia Tech, 2009), MSc in Computer Science (UIUC, 2001), and dual BSc degrees in Industrial Engineering and Construction Engineering (Universidad San Francisco de Quito, 1996). He is a Fulbright Scholar from Ecuador and holds postdoctoral experience at Uppsala University. Research focuses on Human-Computer Interaction, Visualization, and Ubiquitous Computing. Key projects include: TENT: Technology-Enhanced Neurosurgical Training VisBac: Visualizing airborne bacteria in ORs PSP: Platform for Smart People (autism support) SMART: Predictive maintenance in pharmaceuticals Homo Colossus: Energy footprint visualization Awards: Selected for IVA's 100 research2business projects (2021). Co-founded BrailleTouch (blind-friendly keyboard) and Anymaker (3D sketching app). Supervised students in C-Awards-winning projects (e.g., Yue Liu's thesis defense in 2024). Teaching: Responsible for courses like Information Visualization (DH2321) and Advanced Graphics & Interaction (DH2413). Active in organizing conferences (e.g., Eurographics 2020 Education Track Chair).

• Human-Computer Interaction
• Data Visualization
• Ubiquitous Computing
• +6 more

Patrik Hilber is a Professor at KTH Royal Institute of Technology, working in the Division of Electromagnetic Engineering and Fusion Science within the School of Electrical Engineering and Computer Science (EECS). He serves as Deputy Director of First and Second Cycle Education at EECS and heads the QED AM research group. He is also a board member of YH-electrical engineering. Research Interests: His research focuses on reliability engineering, asset management, maintenance optimization, and smart grid technologies in electric power systems. Key areas include transmission and distribution systems, dynamic line and transformer rating, wind power integration, multiobjective optimization, condition monitoring, and data quality in power systems. He applies advanced modeling and data-driven approaches to improve power system planning, operation, and resilience. The recent trends in his publications (2020–2025) highlight a strong emphasis on dynamic rating technologies (DLR and DTR), data quality and machine learning applications in outage analysis, reliability-centered planning for wind farms and distribution systems, and the integration of renewable energy and electric vehicles. His work bridges theoretical modeling with practical utility applications. Teaching and Academic Leadership: He is examiner and course responsible for several degree projects in electrical engineering, power systems, and energy innovation. He also teaches courses on reliability evaluation, asset management, and innovation in electric power engineering. Publications and Books: He has authored a book titled Reliability Analysis and Asset Management Applied to Power Distribution (2014) and a book chapter on cable segment replacement optimization. His scholarly output includes numerous peer-reviewed articles in leading journals such as IEEE Transactions on Power Systems , Reliability Engineering & System Safety , and Applied Energy . Education: He holds a Ph.D. (2008), a Licentiate degree (2005), and an M.Sc. (2000), all from KTH. He became a Docent (Associate Professor) in 2014.

• Reliability Engineering
• Asset Management
• Maintenance Optimization
• +13 more

Ola Carlson is a Professor in Sustainable Electric Power Production at Chalmers University of Technology. He specializes in electrical systems for renewable power production and hybrid electric vehicles. Since 2022, he serves as a senior advisor to the Swedish Wind Centre, focusing on island operation with Chalmers wind turbine and battery systems. Research Interests His research spans renewable power systems, wind energy integration, grid stability, and microgrid optimization. Key projects include modeling Nordic transmission systems, analyzing wind turbine bearing currents, and developing maintenance schedules for aging components. Article Trends Recent publications emphasize wind turbine design, microgrid stochastic optimization, and dynamic state estimation for transmission protection. Topics cover machine learning applications in forecasting, fault handling, and battery degradation impacts on energy systems. Projects & Collaborations RESIST - Energy islanding for resilient systems (2026–2027) COSPACT - Nordic-Baltic co-simulation platform (2020–2023) Fossil Free Energy Districts (2016–2019) Collaborations with ABB, Swedish Energy Agency, and European Commission Labs & Teams Works with Power Grids and Components at Chalmers, leading projects like 'Detecting and eliminating bearing currents' (2018–2023) funded by the Swedish Energy Agency. Involved in Chalmers Campus as a testbed for intelligent grids.

• Renewable Power Systems
• Wind Energy Integration
• Hybrid Electric Vehicles
• +3 more

Ebru Turanoglu Bekar is a Senior Lecturer at the Department of Industrial and Materials Science, Chalmers University of Technology, specializing in Smart Maintenance and Production Systems. She contributes to the Production Service Systems & Maintenance research group. Research Interests: Total Productive Maintenance (TPM), Artificial Intelligence applications in manufacturing, Multi-Criteria Decision Making, Performance Measurement systems Recent Focus: Development of data-driven algorithms for predictive maintenance, integration of digital twins in industrial contexts Key Projects: Factory SensAI (2025–2028) - Data integration for AI in manufacturing Trustworthy Predictive Maintenance TPdM (2022–2025)

• Total Productive Maintenance
• Artificial Intelligence
• Multi-Criteria Decision Making
• +3 more

Christer Malm is a Professor at Umeå University's Department of Community Medicine and Rehabilitation, Section of Sports Medicine. His research spans molecular muscle adaptation, anti-doping technologies, and physical performance optimization for firefighters and athletes. Primary Affiliation: Umeå University, Sweden Key Focus Areas: Exercise physiology, proteomics, anti-doping, muscle disease mechanisms Research Interests: Muscle Adaptation: Revisiting the damage-repair hypothesis using proteomic screening to study cytoskeletal remodeling. Anti-Doping: Developing proteomic methods to detect autologous blood doping and investigate erythrocyte breakdown mechanisms. Work Capacity: Establishing physiological benchmarks for Swedish firefighters through extensive testing. Musculoskeletal Diseases: Comparative proteomic analysis of trapezius, vastus lateralis, and extraocular muscles to uncover disease resistance mechanisms. Exercise Impact: Exploring how physical activity modulates immunity in health and disease contexts. Scientific Contributions: Over 20 years of publications in Journal of Sports Sciences , PLOS ONE , and Scandinavian Journal of Medicine & Science in Sports , including studies on anabolic steroid effects and cold climate physiology. Ongoing Projects: PhD studies on blood doping detection, firefighter performance limits, and cross-country skiing physiology. Contact: christer.malm@umu.se

• Sports Medicine
• Exercise Physiology
• Proteomics
• +3 more

Jessica Edlom serves as a PhD student and adjunct teacher at Karlstad University, actively contributing to strategic communication research within the global music industry. Her work bridges academic theory and practical industry challenges, with particular focus on digital transformation and fan-brand relationships. Her core research examines strategic communication practices, fan engagement dynamics, and transmedia marketing strategies in music. She investigates how artists like ABBA and Taylor Swift leverage phygital experiences to cultivate fan communities, exploring tensions between commercial imperatives and authenticity. Key interests include pandemic-era industry adaptation, value co-creation mechanisms, and the commodification of fan participation through choreographed engagement. Analysis of her publication timeline reveals a clear evolution from foundational studies on Nordic music branding (2017-2019) toward cutting-edge explorations of immersive technologies and fan experience design (2023-2025). Recurring thematic threads include the strategic mobilization of fan communities through social media, authenticity maintenance in digital branding, and industry adaptation to technological disruption. Her methodological approach frequently employs strategy-as-practice frameworks to uncover practitioner-level tensions in brand work.

• Strategic Communication
• Music Industry
• Brand Management
• +3 more

Georgios Andrikopoulos is an Assistant Professor at KTH Royal Institute of Technology's Department of Industrial and Environmental Management (ITM), affiliated with the Digital Futures Faculty. He serves as Co-Principal Investigator (Co-PI) on the 'Real-time exoskeleton control for human-in-the-loop optimization' project, focusing on advanced robotics and human-technology interaction. His research spans soft robotics, exoskeleton systems, and adaptive climbing robots, with applications in healthcare, aerospace, and education. Key projects include: "Connecting Bodies – Designing Shape-changing Wearables" (Postdoc Fellowship, 2023–2025) "Advancing real-time exoskeleton control for human-in-the-loop optimization" (Demonstrator Project) SEC scholar collaboration with Mohamed Elbadawi (May–June 2024) Research interests emphasize: Soft robotic actuators for safe human interaction Optimization of compliant mechanisms in robotics Vortex adhesion systems for autonomous inspection Design of child-friendly interactive robots His work integrates robotics with control systems, biomechanics, and human-centered design. Over 50 peer-reviewed articles demonstrate contributions to exoskeleton technology, climbing robot algorithms, and soft actuator modeling. He advises students like Laia Turmo Vidal (Postdoc) and Mohamed Elbadawi (SEC scholar). Affiliated with the cross-disciplinary Digital Futures initiative, he collaborates with Stockholm University and RISE Research Institutes to address societal challenges through digital innovation.

• Robotics
• Biomedical Engineering
• Control Systems
• +4 more

Mahdi Fazeli is an Associate Professor at the School of Information Technology, Halmstad University, Sweden, specializing in hardware security and trust, energy-efficient computing, and embedded and cyber-physical systems. His academic journey began with a Ph.D. in Computer Engineering from Sharif University of Technology, Iran, in 2011. His career progression includes positions as Associate Professor at Bogazici University (2019-2021) and Iran University of Science and Technology (2016-2019), and Assistant Professor at the same institution (2011-2016). His research interests focus on hardware security and trust, reliable VLSI circuits and systems, energy-efficient computing, and dependable embedded systems. His work bridges the gap between theoretical security concepts and practical implementations in real-world systems, particularly in IoT and embedded environments. He has established himself as a leading researcher in Physical Unclonable Functions (PUFs), hardware trojans detection, and energy-efficient security solutions for resource-constrained devices. His publication record shows a clear progression and deepening expertise in hardware security, with recent work focusing on cutting-edge applications in edge computing, vehicular networks, and IoT security. His 2023-2025 publications demonstrate significant contributions to magnetic memory-based security primitives, anomaly detection systems, and energy-efficient security mechanisms. Throughout his career, Fazeli has led multiple research initiatives including the Dependable Systems and Architecture Lab (DSA) and the Networked and Embedded Systems Lab at Iran University of Science and Technology. His leadership extends to heading the Hardware Group and serving as Vice Chair for Educational Affairs, demonstrating his commitment to both research excellence and academic administration.

• Hardware Security
• Embedded Systems
• Energy-Efficient Computing
• +5 more

Verena Siewers is a Research Professor at the Department of Biology and Biological Engineering, Chalmers University of Technology. Her work focuses on synthetic biology and metabolic engineering of yeast cell factories for producing biofuels, pharmaceuticals, nutraceuticals, and bioplastics, with particular emphasis on developing biosensor tools for pathway optimization. Key research themes: yeast-based biosensors, lipid metabolism engineering, CRISPRi/a applications, and dynamic gene regulation Notable projects include: Development of acetic acid tolerance mechanisms Optimization of fatty acid ethyl esters production Engineering phosphoketolase pathways for acetyl-CoA overproduction Her recent articles reveal trends in: CRISPR-mediated pathway engineering Stress response transcriptional profiling Heterologous plant gene expression in yeast Promoter and transcription factor engineering Funding sources: VINNOVA Novo Nordisk Foundation Carl Tryggers Stiftelse EU Horizon grants Swedish Research Council (VR) Formas

• Synthetic Biology
• Metabolic Engineering
• Yeast Cell Factories
• +5 more

Johanna Sörensen is an Associate Senior Lecturer at the Division of Water Resources Engineering within Lund University's Faculty of Engineering (LTH) . She specializes in urban hydrological processes , particularly during extreme precipitation , and advocates for blue-green infrastructure (NBS, SUDS) to enhance climate change adaptation and reduce flood risks . Her work bridges technical performance of water systems with urban planning reforms for sustainable solutions. Research Focus : Urban hydrology, blue-green infrastructure, stormwater management Teaching : Advanced Hydrology, Sustainability, Pipe System Engineering Her research involves Artificial Neural Networks for hydrological modeling, decision support indicators for water planning, and fieldwork in Malmö . She collaborates with Swedish Environmental Protection Agency and companies on leakage minimization in water distribution systems. Recent projects include StormMan (governance for sustainable stormwater) and RörANN (smart pipe monitoring). Scientific Awards: The New Generation Prize by Swedish Association for Water (2018) Supervision: Regularly supervises 2–3 Master's thesis projects with industry partners. Network: Active in EU projects and collaborations across Scandinavia, Brazil, and Eastern Africa .

• Urban Hydrology
• Extreme Precipitation
• Blue-Green Infrastructure
• +4 more

Per-Erik Hellström is a Professor at KTH Royal Institute of Technology, affiliated with the Department of Electronics and Embedded Systems. His research focuses on semiconductor process technology, particularly the heterogeneous integration of materials like SiGe, Ge, high-κ dielectrics, and metal gates with Si CMOS to advance integrated circuits. He leads KTH's FDSOI CMOS process and circuit technology, emphasizing sequential 3D integration for future CMOS developments. Additionally, he manages the Si and SiC process line at Electrum Laboratory, overseeing tool maintenance, process control, and upgrades. Researcher ID: ORCID Location: Kistagangen 16 Email: pereh@kth.se His work involves developing nanometer-sized transistors through double patterning techniques and studying material integration for enhanced device performance. He teaches courses in electrical circuits, semiconductor devices, and nanotechnology at both Bachelor's and Master's levels, including Electrical Engineering (IF1330) , Embedded Electronics (IE1206) , and Introduction to Integrated Circuits (IL2241) . He also supervises degree projects and exams. Scientific achievements include the 2020 G03 Best Paper Award for gate stack research. His recent publications highlight advancements in Type-II superlattices, 3D integration, and high-temperature sensors. Key collaborators include PhD students working on nanotechnology and process engineering.

• Semiconductor Process Technology
• Heterogeneous Integration
• Nanoelectronics
• +4 more