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Atila Alvandpour serves as Professor and Head of the Integrated Circuits and Systems Division at Linköping University's Department of Electrical Engineering (ISY), concurrently holding the position of Vice Head of the Department. He joined the university in 2003 following senior research scientist roles at Intel Corporation's Circuit Research Lab (1999-2003). His educational foundation includes M.S. and Ph.D. degrees earned from Linköping University in 1995 and 1999 respectively. Alvandpour's research centers on advanced nano-scale integrated circuit design , with pioneering work in data converters (ADCs/DACs) , RF transceivers , and ultra-low-power systems . His expertise spans sensor interfaces, energy-harvesting architectures, and multi-GHz digital circuits, driving innovations for IoT and biomedical applications through novel analog/mixed-signal techniques. Recent publications (2024-2025) reveal a strategic focus on system-level integration for emerging technologies, particularly energy-efficient SoCs for wireless optical sensing, RF energy harvesting, and bio-implantable devices. This trend emphasizes circuit miniaturization, power optimization, and multi-functional integration in cutting-edge CMOS processes. No formal scientific awards are documented in the source materials. As Division Head and active researcher with 24 U.S. patents, Alvandpour leads a significant research group within the Division of Electronics and Computer Engineering (ELDA). His IEEE senior membership and editorial roles for flagship journals like IEEE Journal of Solid-State Circuits demonstrate substantial professional influence, though specific grant details remain unspecified.

• Integrated Circuits and Systems
• VLSI Design
• Analog and Mixed-Signal Circuits
• +6 more

Kent Bertilsson is a Professor and Director of Studies at the Department of Computer and Electrical Engineering (DET) at Mid Sweden University . He serves as a Deputy Prefect and specializes in Power Electronics , with a focus on Embedded Systems , Power Converters , and Fiber Installation Equipment . His research includes projects like DeHigh (electrification of work vehicles) and STORE (electrical energy storage). His work spans High-Frequency Converters , Planar Magnetics , and Multilevel Inverters , with applications in Electric Vehicles and Renewable Energy Systems . He has extensively published in journals like IEEE Transactions on Power Electronics and Energies , emphasizing component optimization and energy efficiency. Notable projects include 48 V Drive Systems and Smart Industry Sweden .

• Power Electronics
• Embedded Systems
• Electrical Engineering
• +6 more

Henk Wymeersch is a Professor at Chalmers University of Technology's Communication Systems department, part of the School of Electrical Engineering. He leads the Radio Localization and Sensing research area and is affiliated with the FORCE Research Center on optical communication. His work focuses on algorithm design and system analysis for 5G/6G systems, emphasizing integrated communication, localization, and sensing. Notable contributions include RIS-aided positioning, bistatic/multistatic sensing, and joint communication-sensing frameworks. Research Interests: His primary areas include Reconfigurable Intelligent Surfaces (RIS), 6G positioning/sensing, integrated ISAC systems, mmWave/V2X positioning, and distributed radar networks. Recent work explores challenges in near-field localization, OFDM-based ISAC under hardware impairments, and privacy-preserving techniques for localization systems. Publications: Over 485 publications (2025) highlight his expertise in mmWave SLAM, RIS applications, and 6G enablers. Recent trends focus on 6G sustainability, distributed ISAC architectures, and leveraging RIS for robust localization in cluttered environments. Affiliations: Active in the Communication Systems Group and FORCE Research Center. Collaborates internationally on Hexa-X 6G projects and standards development.

• Telecommunications
• Wireless Communication Systems
• Radio Localization
• +5 more

Ana Rusu is a Professor and leader of the Mixed-Signal Integrated Circuits and Systems Group at the Division of Electronics and Embedded Systems, Department of Electrical Engineering, KTH Royal Institute of Technology. She holds a Docent title from KTH and has been at the university since 2001. Her research focuses on energy-efficient circuits, biomedical applications, and emerging technologies like graphene and SiC. She has supervised numerous PhD students and led major projects such as AIsing (VR-funded) and Implantable Bioimpedance Spectrometer (SSF-funded). Education: Diploma Engineer (M.S.) from Technical University of Iasi (1983), PhD from Technical University of Cluj-Napoca (1998), Docent in Circuit Theory (KTH, 2006). She previously served as Director of Doctoral Education at the School of ICT (2013–2017) and Vice-Dean at EECS (2018–2022). Research interests include energy harvesting, spintronics-CMOS integration, and Ising Machines. Her work spans over 150 peer-reviewed publications and includes awards like the T-NANO Best Paper (2020) and ISCAS Best Paper (2023). She has advised 16+ PhD graduates and actively contributes to academic governance and education.

• Energy-Efficient Circuits
• Biomedical Applications
• Wireless Communications
• +6 more

Torsten Wik is a Professor in Control Engineering at Chalmers University of Technology. He leads the Control Engineering research group and focuses on process control with theoretical and applied methodologies. Institution: Chalmers University of Technology Department: Control Engineering His research spans optimal control, model reduction, and systems with model uncertainties. Applications include energy-saving systems, environmental improvement, biological systems (water purification, recirculating fish farms, LED greenhouse lighting), and battery estimation/modeling/control. Recent work emphasizes battery degradation diagnosis, state estimation, fast charging, and reconfigurable systems. Key methodologies include physics-informed frameworks, machine learning integration, entropy-based predictive algorithms, and hypergraph modeling. Applications extend to electric vehicles, photovoltaic systems, fuel cells, and biofilm reactors. Publications highlight collaborations across engineering domains, focusing on control theory, electrochemical modeling, and real-time optimization. His work bridges theoretical advancements with industrial applications in energy systems, transportation, and sustainable agriculture.

• Control Engineering
• Process Control
• Optimal Control
• +11 more

Christoph Kessler is a Professor and Head of the Software and Systems (SAS) division at the Department of Computer and Information Science (IDA), Linköping University, Sweden. He leads the Programming Environment Laboratory’s research group focusing on compiler technology, parallel computing, and heterogeneous systems. His work includes the development of tools like OPTIMIST, PARAMAT, and SkePU, and he has contributed over 100 publications in journals and conferences. He holds a PhD from the University of Saarbrücken and a Habilitation from the University of Trier. Research interests span parallel programming, compiler optimization, and energy-efficient scheduling for heterogeneous systems. He has secured a 30M SEK grant from SSF for the ASTECC project, advancing adaptive software for edge-cloud computing. Notable contributions include frameworks for GPU-based systems and methodologies for optimizing resource allocation on many-core architectures. His team’s work emphasizes practical applications in high-performance computing, including tools for course management (StASy) and energy-aware scheduling algorithms. The SAS division, under his leadership, focuses on software engineering and computer systems research with strong industry collaboration.

• Parallel Programming
• Compiler Technology
• Optimization Algorithms
• +3 more

Federico Ciccozzi is an Associate Professor in Computer Science at Mälardalen University's School of Innovation, Design and Engineering, where he leads the ASSO research group and the VR ORPHEUS project. He also serves as Head of Research Education in Computer Science and Electronics at the university. His academic journey includes a M.Sc. in Global Software Engineering (via the GSEEM program) and a Ph.D. in Computer Science and Engineering from Mälardalen University (2014), followed by promotion to Docent (Associate Professor) in 2017. Education: M.Sc. in Global Software Engineering (GSEEM program, joint between Mälardalen, L'Aquila, and Amsterdam) Ph.D. in Computer Science and Engineering (Mälardalen University, 2014) Docent (Associate Professor) in Computer Science (Mälardalen University, 2017) His research focuses on model-driven engineering, robotics software engineering, and software architecture. He has pioneered work in blended modeling approaches, EAST-ADL extensions, and formal verification of complex systems, particularly in robotics and automotive domains. Recent projects emphasize industrial collaborations, such as optimizing ROS2 multi-robot systems and enhancing safety-critical software through model-based methodologies. Research Contributions: Developed frameworks for transforming surface languages into augmented EAST-ADL models Advanced blended modeling techniques across JetBrains MPS and Eclipse tools Examined consistency management in industrial model-driven development Edited special issues on model-driven engineering and low-code development His work bridges academic innovation and industrial practice, with notable projects like the Rubus Component Model for vehicular systems. He actively organizes workshops (e.g., RoSE, ASYDE) and contributes to standardization efforts like the Portable Test and Stimulus Standard. Labs/Teams: Leads the ASSO research group, focusing on advanced software engineering methodologies and robotics systems development.

• Model-Driven Engineering
• Robotics Software Engineering
• Software Architecture
• +3 more

Ming Xiao is an Associate Professor in the Division of Information Science and Engineering at KTH Royal Institute of Technology's School of Electrical Engineering and Computer Science (EECS). He is affiliated with the Digital Futures Faculty and leads research in wireless communications, machine learning, and network coding. His work focuses on 6G networks, distributed learning, and secure communications. Affiliations: KTH EECS, Digital Futures, Swedish Research Council, EU Horizon Europe projects Roles: Editor for IEEE Transactions on Wireless Communications, TPC Co-Chair for VTC Fall Research Interests: Dr. Xiao's expertise spans wireless communication systems (e.g., mmWave, NOMA), network coding, machine learning applications in communications, and energy-efficient distributed systems. He has pioneered work on intelligent reconfigurable surfaces (RIS), federated learning in edge computing, and integrated sensing-communications (ISAC). Projects: Ongoing EU-funded projects include ASCENT (autonomous vehicular networks) and COVER (unmanned aerial vehicles for emergency response). Past projects include 6G channel coding and intelligent energy management in smart communities. Grants: Over 12 active grants from VR, EU Horizon Europe, FORMAS, STINT, and VINNOVA Awards: IEEE Vehicular Technologies Society Best Paper Award (2023), World Top 2% Researcher (2020–2023), Highly Cited Researcher in Computer Science/Engineering. Labs/Teams: Leads the KTH Digital Futures initiative, collaborates with RISE Research Institutes, and manages a team of 12 PhD students/postdocs focusing on 6G, distributed ML, and secure IoT.

• Wireless Communications
• Network Coding
• Machine Learning
• +10 more

Anders Lansner is a Professor of Computer Science at Stockholm University and holds an affiliated professorship at KTH Royal Institute of Technology. He leads the Lansner Lab (Computational Biology and Neurocomputing) at the Department of Computational Science and Technology (CST) within the School of Computer Science and Communication (CSC) at KTH. His research focuses on computational neuroscience and brain-like computing, emphasizing mathematical and computational models of neuronal networks in the neocortex and basal ganglia. Key projects include developing neuromorphic algorithms for supercomputers and FPGA-based hardware implementations. Lansner manages the computational neuroscience platform for the Stockholm Brain Institute (SBI) and the neuroinformatics platform for StratNeuro (Karolinska Institutet). His lab contributes to EU projects such as FACETS and NEUROChem, and collaborates with KTH’s Electronics Department on modular brain-inspired FPGA designs. Research interests span synaptic plasticity mechanisms, memory systems (episodic, semantic, and working memory), and applications in neuromorphic computing. He supervises graduate students and teaches courses in computational neuroscience. Lansner’s work bridges theoretical neuroscience with engineering, aiming to advance brain-inspired AI and hardware systems. His lab’s StreamBrain framework supports heterogeneous computing architectures for brain-like neural networks. Notable collaborations include cross-disciplinary efforts in neuromorphic hardware development (e.g., memristor-based learning engines) and olfactory system modeling. Lansner’s research addresses both fundamental brain mechanisms and technical applications in data analysis and neurorobotics.

• Computational Neuroscience
• Neuromorphic Engineering
• Brain-like Computing
• +4 more

Sobhi Barg serves as an Assistant Senior Lecturer in Power Electronics at Mälardalen University's Department of Computer and Electrical Engineering (DET) in Sundsvall, Sweden. His position within the STC Research Centre focuses on advanced power conversion systems and magnetic component design for electric vehicles and renewable energy applications. Education: PhD in Electrical Engineering from National Engineering School of Sfax (2018) Erasmus Master in Sustainable Transportation and Electrical Power Systems (University of Oviedo, University of Nottingham, Polytechnic Institute of Coimbra) (2015) Master in Electrical Systems from National Engineering School of Tunis (2010) Engineering Degree from National Engineering School of Tunis (2008) His research centers on multi-objective optimization of power electronic systems , with expertise in core loss modeling for high-frequency magnetics, wireless power transfer, and EV power conversion. Recent work demonstrates innovative approaches to planar magnetics using unbalanced-flux techniques and precise core loss calculation for non-sinusoidal waveforms, significantly advancing efficiency in power converter design. Publications since 2019 reveal strong focus on magnetic component optimization and loss modeling , with 50% appearing in IEEE Transactions journals. Key trends include development of empirical core loss models for complex waveforms (2025), novel unbalanced-flux approaches for planar magnetics (2023-2024), and multi-objective GA optimization techniques for flyback transformers (2019). Scientific Recognition: Erasmus Mundus Scholarship-Category A (48,000 Euro) for Master studies in Sustainable Transportation and Electrical Power Systems (2013-2015) Dr. Barg teaches Analog Electronics and Electric Circuits laboratory courses while contributing to the STORE (Electrical Energy Storage) and MDOBC research projects. His work at the STC Research Centre bridges theoretical modeling with practical applications in renewable energy systems and electric vehicle powertrains, emphasizing experimental validation through Seebeck effect measurements and FEA simulations. Current research activities include DC inductor design based on Ampere's Law (2024) and continued refinement of core loss models for next-generation power converters, with significant implications for high-efficiency energy conversion in sustainable transportation systems.

• Power Electronics
• Electric Vehicle Power Systems
• AC Motor Drives
• +6 more

Aamir Mahmood is an Associate Professor at the Department of Computer and Electrical Engineering at Mid Sweden University and an Adjunct Professor at NUST, Pakistan. His research focuses on 5G/6G wireless communication , Industrial IoT , RF interference management , and time synchronization . Education: B.Sc. NUST (2002), M.Sc. and Ph.D. Aalto University (2008, 2014) Collaborations: Nokia Research Center, IEEE Sweden VT-COM-IT His recent work explores STAR-RIS for 6G IoT, NOMA for industrial networks, and deep reinforcement learning in MEC systems. Key trends include ultra-reliable communication for industrial automation and interference management in heterogeneous networks. Awards : IEEE WCNC’13 Best Paper Ericsson Research Foundation Grant Nokia Foundation grant STINT grants IEEE Sweden VT-COM-IT Best Student Journal Paper Award Swedish Institute funding Interreg Aurora funding Awarded 80+ peer-reviewed publications and active in IEEE leadership roles.

• Wireless Communications
• Industrial IoT
• 5G/6G Networks
• +4 more

Lena Wosinska is a Research Professor at Chalmers University of Technology, specifically in the field of Optical Networks since June 2019. Prior to her current position, she served as a Professor of Telecommunications at KTH Royal Institute of Technology, where she established and directed the Optical Networks Lab.

• optical networks
• 5G transport networks
• energy efficiency
• +5 more

Muhammad Ihsan Al Hafiz is a Doctoral Student at the KTH Royal Institute of Technology, affiliated with the Division of Software and Computer Systems under the School of Electrical Engineering and Computer Science. His research focuses on hardware accelerators for neuromorphic computing and FPGA-based solutions. PhD (2024–Present): Hardware Accelerator for Neuromorphic Computing MSc (2021–2023): Embedded System, Track: Embedded Electronics His work spans fields such as Neuromorphic Computing , FPGA Design , and Embedded Systems , emphasizing hardware optimization for industrial applications. His recent publication introduces a reconfigurable FPGA accelerator for Bayesian Confidence Propagation Neural Networks, reflecting his focus on AI-driven hardware solutions. Current affiliations include: Role: Researcher Institution: KTH Royal Institute of Technology Division: Software and Computer Systems

• Neuromorphic Computing
• Hardware Acceleration
• FPGA Design
• +3 more

Jordi Altayo Gonzalez is a Doctoral student and Researcher at KTH Royal Institute of Technology, working within the Division of Electronics and Embedded Systems. He holds teaching positions across multiple digital design and embedded systems courses while conducting advanced research in hardware architectures. His academic journey includes a Bachelor's degree in Electrical Engineering with Electronics specialization from UPC Barcelona (2018) and a Master's degree in Embedded Systems with Embedded Electronics focus from KTH (2020). His current research investigates coarse grain reconfigurable architectures (CGRA) and Synchoros VLSI design methodologies, bridging computer architecture, hardware design, and energy-efficient computing. Gonzalez teaches four key courses at KTH: Digital Design (IE1205) as instructor, Digital Systems Design and Verification using Hardware Description Languages (IL2234) as both teacher and course responsible, Digital Systems Design using Hardware Description Languages (IL1332), and Embedded Hardware Design in ASIC and FPGA (IL2225). His work represents the intersection of academic research and practical engineering education in electronic systems. Based in room 2422 at Teknikringen 31, he maintains professional presence through his KTH profile and personal website, though his online content primarily showcases culinary interests alongside his academic profile.

• Electronics
• Embedded Systems
• VLSI Design
• +2 more

Carlos Alberto Barrera Diaz is a researcher affiliated with the University of Skövde , specifically within the School of Engineering Science and its Production and Automation Engineering department. His work focuses on Reconfigurable Manufacturing Systems (RMS) , where he applies simulation-based multi-objective optimization (SMO) and knowledge discovery methods to address challenges in dynamic production environments. His research spans from 2020 to 2023 and involves collaborations with academics like Amir Nourmohammadi, Henrik Smedberg, and Amos H.C. Ng. Key themes include RMS availability analysis, buffer capacity allocation, task assignment to workstations, and knowledge-driven optimization techniques. Publications in journals such as Mathematics, IEEE Access, and MDPI highlight his technical expertise and contributions to industry-specific challenges like mass customization and Industry 5.0 sustainability goals. His findings demonstrate how SMO methods can enhance decision-making in RMS, particularly under fluctuating production volumes and capacity constraints. He has been funded by the Knowledge Foundation (KKS) through the Virtual Factories with Knowledge-Driven Optimization (VF-KDO) profile and acknowledged support from VINNOVA’s EXPLAIN project. While no direct student advising is mentioned, his work has significantly advanced RMS optimization frameworks through industrial case studies and algorithmic innovations.

• Reconfigurable Manufacturing Systems
• Simulation-based Optimization
• Multi-Objective Optimization
• +4 more