Cicek Cavdar is an Associate Professor at the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology , Sweden. She leads the Intelligent Network Systems research group and specializes in Telecommunication Networks , with a focus on Beyond 5G/6G Mobile Networks , Energy Efficiency , and AI-Assisted Network Management . PhD in Computer Science (2009) from University of California, Davis and Istanbul Technical University Her research spans Cell-Free Massive MIMO , Reconfigurable Intelligent Surfaces (RIS) , UAV Communication Systems , and Green Network Technologies . She actively contributes to 6G Network Architecture and Non-Terrestrial Networks , including satellite and aerial systems. Recent publications highlight AI-driven network optimization for handover management, energy-aware resource allocation , and multi-agent reinforcement learning in complex communication environments. She teaches advanced courses in Communication Systems , Machine Learning , and Software Engineering at KTH.
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
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
Luca Peretti is an Associate Professor in Electric Machines and Drives at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Department of Electrical Engineering, Division of Electric Power and Energy Systems. He works as a researcher in the EMD (Electric Machines and Drives) group and serves as Partner Director for KTH's strategic partnership with ABB. Education: M.Sc. in Electronic Engineering (2005) from University of Udine, Ph.D. from University of Padova (2008) Professional Experience: Postdoc at University of Padova (2009-2010), Principal Scientist at ABB Corporate Research (2010-2018), Associate Professor at KTH (2018-present) His research focuses on: Automatic parameter estimation in electric machines Multiphase drive systems Sensorless control algorithms Loss segregation in drive systems Condition monitoring of industrial and transportation applications Recent publications demonstrate expertise in variable phase-pole machines, harmonic plane decomposition, predictive control algorithms, and advanced modeling of permanent magnet motors. Key application areas include transportation electrification, wind energy systems, and industrial drive technologies. Scientific roles include: Associate Editor, IET Electric Power Applications Journal (2019-present) Theme Co-Leader, Swedish Electromobility Center (2020-present) Member, IEEE (2021-present) and IET (2006-present) He leads the strategic partnership with ABB and contributes to doctoral program committees at University of Padova.
Yang Liu is a tenured Associate Professor at the Department of Management and Engineering , Linköping University, Sweden, and an Adjunct Professor at the University of Oulu, Finland. His expertise spans smart manufacturing, clean energy transition, and Industry 4.0 applications. He holds an M.Sc. and D.Sc. from the University of Vaasa, Finland. Research & Awards: Liu's work focuses on sustainable systems, decision support systems, and AI-driven energy efficiency. He has authored over 140 Web of Science publications, including top 0.1% ESI Hot Papers. He is ranked among the world's top 2% scientists (Stanford-Elsevier) and leads globally in 'big data analytics in manufacturing' and 'Industry 4.0-driven circular economy' research. Leadership & Projects: He leads projects like FlexSUS (EU Horizon 2020) and PERSEUS, developing tools for smart urban energy planning and 15-minute city models. He serves as Editor-in-Chief of Cleaner Engineering and Technology and Guest Editor for multiple journals. His research emphasizes bridging data science with sustainability challenges in manufacturing and energy systems. Key Achievements: Top-ranked in global citations, ESI Highly Cited Papers, and industry-driven sustainability frameworks. Grants: Leads EU-funded projects and collaborates with Siemens Energy on energy transition solutions. Labs & Teams: Part of the Environmental Technology and Management (MILJÖ) division and Unit for Product Service Innovation (MILJOPSI) at Linköping.
Dr. Harry T. Conway is the Alternate Permanent Representative of Liberia and Chair of the Marine Environment Protection Committee (MEPC) at the International Maritime Organization (IMO). He leads global maritime environmental policy initiatives, including the 2023 IMO GHG Strategy. His academic affiliations include guest lecturing at the International Maritime Law Institute's special course on marine environmental protection and opposing a WMU PhD candidate's thesis. Education: PhD in Politics and International Relations (Cardiff University, UK), MA (Distinction) in International Maritime Policy (University of Greenwich, UK), and MBA (Hanze University of Applied Sciences, Netherlands). His research focuses on environmental politics, with emphasis on climate agreements and maritime decarbonization. Professional Experience: Policy Officer and Officer-in-Charge of Liberia's IMO Permanent Mission (2012–present), Chief of Staff at Liberia Maritime Authority (pre-2012), and finance roles in Liberian banking institutions. He contributed to the 2050 Africa Integrated Maritime Strategy for the African Union and serves on the International Quality Assessment Review Body (IQARB). Publications include contributions to 'The African Union and the Law of the Sea' and peer-reviewed articles on maritime innovation and decarbonization. He frequently speaks at international shipping conferences and advises on maritime regulatory frameworks.
Zhibo Pang is an Adjunct Professor at KTH Royal Institute of Technology's Department of Intelligent Systems (EECS) and Senior Principal Scientist at ABB Corporate Research Sweden. His work focuses on digital transformation in industry and healthcare, spanning robotics, AI, control systems, and wireless communication. He leads projects in embodied intelligence, Industry 4.0, and Healthcare 4.0, with 23 granted patents and over 120 journal papers. Education: PhD in Electronic and Computer Systems (KTH, 2013), MBA in Innovation & Growth (University of Turku, 2012). Key Roles: IEEE Technical Committee Chair, Editor of 6 IEEE journals, ABB Inventor of the Year (2016, 2018, 2021). Research Interests: Robotics safety, wireless automation, federated learning, digital twins, and IoT security. Recent Projects: Cloud-fog automation frameworks, robot skin systems for healthcare, and latency-aware industrial control. His work bridges academia and industry through cross-functional collaborations.
Saurabh Amin is a Professor in the Department of Civil and Environmental Engineering at the Massachusetts Institute of Technology (MIT), where he also serves as the Edmund K. Turner Professor and Undergraduate Officer. He is a Principal Investigator at the Laboratory of Information and Decision Systems and holds affiliations with the Operations Research Center and the Center for Computational Science and Engineering. His educational background includes: B.Tech. 2002, Indian Institute of Technology (IIT) Roorkee M.S. 2004, University of Texas (UT) Austin Ph.D. 2011, University of California (UC) Berkeley Saurabh Amin's research focuses on the design and control of infrastructure systems using game theory and optimization in networks. His work spans three main areas: resilient network control, information systems and incentive design, and optimal resource allocation in large-scale infrastructure systems. By concentrating on critical infrastructure domains including highway transportation, electric power distribution, and urban water networks, his research develops innovative theory and tools to enhance system performance against both stochastic and adversarial disruptions. His approach involves modeling cyber-physical interactions in infrastructures to assess vulnerabilities, developing detection and response tools for failures at various scales, and designing economic incentive schemes that improve aggregate public good while accounting for dependencies and private information among strategic entities. Amin's work bridges mathematical systems theory with practical civil engineering applications, creating a rigorous theoretical foundation for infrastructure resilience that addresses diverse failure mechanisms from natural disasters to deliberate malicious actions. His recent publications demonstrate a strong focus on decarbonization of energy systems, resilient infrastructure planning under climate uncertainty, optimization methods for complex networked systems, and game-theoretic approaches to sustainable infrastructure management. His work increasingly integrates artificial intelligence and machine learning techniques with traditional control theory to address contemporary challenges in infrastructure resilience and sustainability. The research shows a clear trajectory toward addressing climate change impacts on infrastructure systems while maintaining economic efficiency and operational reliability. Professor Amin has received numerous prestigious awards and honors: Common Ground Excellence in Teaching Award, 2025 HSCC Test-of-Time Award, 2024 MIT CEE, Distinguished Service and Leadership Award, 2023 Samuel M. Seegal Prize (SoE) – inspiring students in pursuing and achieving excellence, 2022 Earll M. Murman for Excellence in Undergraduate Advising, 2022 C3.ai Digital Transformation Institute Research Award, 2020 MIT, Ole Madsen Mentoring Award, 2020 MIT, Energy Initiative Research Award, 2020 National Academy of Engineering, China-America Frontiers of Engineering Symposium speaker, 2019 MIT, Robert N. Noyce Career Development Professor, 2015-2018 Google Faculty Research Award, 2015 National Science Foundation CAREER Award, 2015 Siebel Energy Institute Research Award, 2015 MIT, Solomon Buchsbaum AT&T Research Fund Award, 2012 Professor Amin has been actively involved in significant research projects including the C3.ai DTI project on Causal Reasoning for Real-Time Attack Identification in Cyber-Physical Systems and another on Learning in Routing Games for Sustainable Electromobility. He serves as the chief scientist on multi-institutional NSF grants, including the $9 million Foundations of Resilient Cyber-Physical Systems (CPS) project. His teaching portfolio includes courses such as 1.008 Engineering for a Sustainable World, 1.104 Sensing and Intelligent Systems, 1.020 Engineering Sustainability: Analysis and Design, and 1.208 Resilient Networks. As Undergraduate Officer, he plays a key role in shaping the educational experience for civil and environmental engineering students at MIT. Professor Amin leads the Resilient Infrastructure Networks Lab at MIT, where his team develops theoretical foundations and practical tools for infrastructure resilience. The lab focuses on the intersection of control theory, game theory, and optimization applied to cyber-physical infrastructure systems. Current research directions include pandemic-resilient urban mobility and hurricane-resilient smart grid operations, reflecting the lab's commitment to addressing pressing societal challenges through rigorous systems engineering approaches.
Vanya Darakchieva is a Professor in Solid State Physics at Lund University's Faculty of Engineering (LTH), serving as Principal Investigator at NanoLund: Centre for Nanoscience and Director of C3NiT: Centre for III Nitride technology. She is a core member of Lund's profile areas in Nanoscience and Semiconductor Technology, Light and Materials, and The Energy Transition, reflecting her interdisciplinary impact. Her research centers on wide bandgap semiconductors, particularly gallium nitride (GaN) and gallium oxide (Ga 2 O 3 ), with emphasis on defect engineering, electron transport, and advanced characterization techniques. She pioneers terahertz spectroscopy and electron paramagnetic resonance methods to analyze material properties critical for quantum technologies and energy-efficient electronics. Her work bridges fundamental physics with industrial applications in high-frequency devices and green semiconductor technology. Recent publications reveal a sharp focus on structural optimization of GaN crystals, doping mechanisms, and contact engineering—key bottlenecks in next-generation power electronics. Trends show increasing collaboration with international teams on epitaxial growth techniques and defect-driven property control. No scientific awards were documented in the provided text. She actively supervises PhD candidates including Logotheti, A. and Rindert, V., guiding dissertation projects within major grants. Darakchieva leads nine research projects with 150+ million SEK in funding, including two flagship Knut and Alice Wallenberg Foundation initiatives (2025–2030) on quantum-ready semiconductors and ceramic-to-semiconductor transformation, plus Swedish Research Council and Vinnova grants targeting terahertz characterization and III-nitride technology. Her work is anchored in NanoLund and C3NiT infrastructure, fostering cross-departmental teams for nanofabrication and device prototyping. Current efforts integrate magnetron sputtering, MOCVD growth, and in-situ characterization to solve industry challenges in thermal management and electron mobility for 6G communications and renewable energy systems.
Karl Henrik Johansson is a Professor at the School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology in Stockholm, Sweden, where he also serves as the Founding Director of Digital Futures. He is a Fellow of both IEEE and the Royal Swedish Academy of Engineering Sciences, and has held leadership positions including Immediate Past President of the European Control Association and IEEE Control Systems Society Vice President Diversity, Outreach & Development. Dr. Johansson earned his MSc in Electrical Engineering and PhD in Automatic Control from Lund University. His academic journey includes visiting positions at prestigious institutions such as UC Berkeley, Caltech, and NTU. His research focuses on networked control systems and cyber-physical systems with applications in transportation, energy, and automation networks. His work investigates fundamental challenges in connecting physical world systems through communication networks, exploring how wireless communication and sensor technology can enhance system robustness, reliability, energy efficiency, and safety. Current research directions include security of cyber-physical systems, distributed optimization, multi-agent systems, and applications to intelligent transportation and energy networks. Analysis of his recent publications reveals a strong focus on distributed optimization algorithms, secure networked control, multi-agent systems, and applications to transportation and energy networks. His work increasingly integrates machine learning techniques with traditional control theory, addressing challenges in privacy-preserving distributed computation, resilient state estimation, and resource allocation in complex networked systems. IEEE Control Systems Society Hendrik W. Bode Lecture Prize (2024) Swedish Research Council Distinguished Professor (2018-2027) Wallenberg Scholar (2009-2026) IFAC Young Author Prize IEEE CSS Distinguished Lecturer (2017-2019) IFAC Outstanding Service Award IEEE Fellow Dr. Johansson has supervised over 100 postdocs and PhD students, with many now holding prominent positions at institutions worldwide. His research has been supported by significant grants including the Swedish Research Council Distinguished Professor Grant (2018-2027), multiple Wallenberg Foundation grants, and numerous EU and national research projects. He has directed major research centers including ACCESS Linnaeus Centre (2009-2016) and Strategic Research Area ICT TNG (2013-2020). His research group operates within the Digital Futures initiative and maintains strong connections with industry partners through projects like the Integrated Transport Research Lab (supported by Scania and Ericsson) and Smart Mobility Lab. The group actively collaborates with international institutions and participates in major EU-funded projects addressing challenges in cyber-physical systems, transportation, and energy networks.
Olle Eriksson is a Professor in the Department of Physics and Astronomy at Uppsala University, specifically affiliated with the Materials Theory division. His research focuses on theoretical and computational approaches to understanding magnetic materials and their properties. His primary research interests include first principles calculations of bulk materials and surfaces, with particular emphasis on magnetism and chemical bonding. His methodological expertise spans full-potential implementations of density functional theory, dynamical mean-field theory, and self-interaction correction. He also conducts calculations of finite temperature magnetism using Monte Carlo simulations and atomistic spin-dynamics simulations, as well as investigations into lattice dynamics and finite temperature effects on phase stability. Professor Eriksson's recent work demonstrates a strong focus on magnetocaloric materials for magnetic refrigeration applications, two-dimensional magnetic materials including van der Waals magnets, topological magnetic textures such as skyrmions, and computational methods for improving density functional theory. His research has significant implications for energy-efficient cooling technologies, next-generation spintronic devices, and fundamental understanding of quantum magnetic phenomena. Materials Science : Magnetocaloric materials, battery materials, 2D materials Computational Physics : Density functional theory, Monte Carlo simulations, spin dynamics Magnetism : Topological textures, chiral magnets, ultrafast dynamics His extensive publication record shows consistent contributions to high-impact journals across physics and materials science, with a notable increase in interdisciplinary work connecting computational physics with materials design for energy applications.
Özer Özkahraman is a postdoctoral researcher at the Division of Robotics, Perception and Learning (RPL) at KTH Royal Institute of Technology. He works under Ivan Stenius and John Folkesson, focusing on underwater mission planning, simulation, and integration of autonomous systems. His email is ozero@kth.se . He completed his PhD at KTH under Petter Ögren, researching large-scale multi-agent coverage planning for autonomous underwater vehicles (AUVs). Current projects include the SMaRCSim multi-domain simulation platform and development of underwater vehicles like LoLo, SAM, and Evolo. Research interests span autonomous underwater systems, multi-agent coordination, control systems, and simulation infrastructure. He emphasizes modular, accessible frameworks for vehicle testing and real-world deployment. His work bridges theoretical methods (e.g., control barrier functions) with practical applications in marine robotics. Publications focus on AUV navigation, environmental sensing, and adaptive control. Projects like Real2Sim aim to align simulation with real-world vehicle dynamics using motion capture data. He collaborates internationally on topics like data-driven damage detection and model compression for resource-constrained robots. No academic awards are explicitly mentioned. He actively seeks collaborators for projects in sonar simulation, flow field modeling, and cyber-physical system integration.
Sven Werner is a Senior Professor at Halmstad University's Academy of Entrepreneurship, Innovation and Sustainability. His expertise lies in district heating and cooling systems, with a focus on decarbonization, energy efficiency, and fourth/fifth generation technologies. He has authored foundational textbooks, such as Energiförsörjning: En introduktion till vårt energisystem , and contributed to international platforms like DHC+ and the IEA's Low-Temperature District Heating Annex. His research includes pioneering the concept of 'Fourth Generation District Heating' and analyzing global heating/cooling demands. Key achievements include over 50 short courses for industry professionals and presentations across 20 countries. Current projects include a book on the world history of district heating. Research Highlights: Low-temperature systems, renewable integration, and thermal storage. Impact: Most-cited article on district heating (Annex X Final Report, 2014), cited every six hours in 2021. International Contributions: Co-developed the Pan-European Thermal Atlas (PETA) and advised the EU Energy Council on energy efficiency. Werner's work bridges academia and industry, emphasizing practical solutions for sustainable energy systems. His publications span journals, conference papers, and policy guides, addressing topics like heat distribution costs, industrial heat recovery, and smart grid technologies.
Anh Tuan Le is an Associate Professor at the Department of Electrical Engineering, Chalmers University of Technology. He holds a PhD in Power Systems from Chalmers (2004) and a Master's in Energy Economics from the Asian Institute of Technology (1997). Specializes in power grid planning, electricity market modeling, and renewable energy integration Active in electric vehicle-grid interaction and battery storage systems Develops voltage stability solutions and decentralized control strategies His recent research focuses on: Flexibility markets for congestion management Machine learning applications in load forecasting Real-time security margin control using AI Key projects include: DigiRES (2024-2027): Digital integration of multi-energy flexibility POTENT-X (2024-2027): Port energy transition hubs FLEXIGRID (2019-2023): Distribution grid flexibility solutions
Prof. Olfa Kanoun is a Visiting Professor at Mid Sweden University's Department of Electronics, affiliated with the STC Research Centre. She specializes in embedded measurement systems, focusing on sensor technologies, energy harvesting, and impedance spectroscopy. Her research spans battery diagnosis, bio-impedance applications, and flexible nanocomposite sensors for force, temperature, and humidity measurements. She holds a PhD from the University of the Bundeswehr Munich (2001) and has been a professor at TU Chemnitz since 2007. A senior IEEE member, she co-founded the International Multi-Conference on Systems, Signals, and Devices (SSD) and initiated the International Workshop on Impedance Spectroscopy (IWIS). She leads the Autonomous Sensor Systems research group, advancing energy-efficient embedded sensor systems. Her honors include a 2015 award from Tunisia’s Ministry of Social Affairs. She actively contributes to IEEE’s Instrumentation and Measurement Society and chairs the Technical Committee on Nanotechnology in Instrumentation and Measurement (TC 34).
