جست‌وجوی استاد و پژوهشگر

• Telecommunication Networks
• Beyond 5G/6G Mobile Networks
• Edge/Cloud Computing
• +۷ مورد دیگر

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.

Michael Felsbergمشاهده پروفایل

استاد

• Artificial Visual Systems
• Computer Vision
• Robot Vision
• +۴ مورد دیگر

Michael Felsberg is a Professor and Head of Division at the Department of Electrical Engineering (ISY) at Linköping University, leading the Computer Vision Laboratory (CVL). His research focuses on artificial visual systems (AVS), including 3D computer vision, computational imaging, object tracking, and autonomous systems. He emphasizes HVS-inspired approaches to bridge the gap between human and machine vision capabilities. Notable achievements include over 20,000 citations (h-index 47), leadership roles in the Wallenberg AI, Autonomous Systems and Software Program (WASP), and recognition as Sweden’s top AI researcher by Vinnova. His work spans academic contributions, industry collaborations, and interdisciplinary projects like climate science applications of machine learning. Positions : WASP Executive Committee Member, WASP Area Cluster Leader for Machine Learning, and Vice-Head of Department (Electrical Engineering). Education : Extensive academic background in electrical engineering and computer vision (details not explicitly stated). Research trends in his articles reflect advancements in autonomous systems, multimodal AI, and robust vision models. His teams address challenges like object tracking, generative models for 3D simulation, and culturally diverse AI systems. Awards : Tracking Challenge Winner (OpenCV, 2015) Best Paper Awards (ICPR 2016, VISAPP 2021) Vinnova’s Highest-Ranked Swedish AI Researcher (2018) He advises numerous PhD students and oversees grants in WASP-funded initiatives. CVL collaborates on projects like disaster-response robotics and Berzelius supercomputer utilization for AI.

• Autonomous Underwater Vehicles (AUVs)
• Multi-Agent Systems
• Robotics
• +۶ مورد دیگر

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.

Nir Pitermanمشاهده پروفایل

استاد

• formal verification
• automata theory
• model checking
• +۴ مورد دیگر

Nir Piterman is a Professor in Computer Science at the University of Gothenburg's Department of Computer Science and Engineering. Previously, he was a Lecturer and later Reader (Associate Professor) at the University of Leicester (2010-2019), following postdoctoral research at EPFL (2005-2007) and a Research Fellowship at Imperial College London (2007-2010). PhD from Weizmann Institute of Science (2005), supervised by Amir Pnueli Postdoc at EPFL with Tom Henzinger (2005-2007) Research Fellow at Imperial College London (2007-2010) Lecturer at University of Leicester (2010-2019), promoted to Reader in 2012 Universitets Lektor (Associate Professor) at University of Gothenburg (2019-2021), promoted to Professor in 2021 His research focuses on formal verification, automata theory, and synthesis from temporal specifications. Current work under the ERC Consolidator Project dSynMA extends reactive synthesis to multi-agent systems, exploring frameworks combining message passing and variable sharing, algorithmic analysis of games with partial information, and logic extensions for agent interaction. He has supervised eight PhD students, including Prabhat Kumar Jha (path planning in game solving), David Lidell (automata constructions for LTL with past), and Claudia Cauli (cloud infrastructure security reasoning, 2022), with theses covering program verification, temporal logic, and game algorithms. ERC Consolidator Grant (2021-?, dSynMA) Editor-in-Chief, Formal Methods in System Design Editor, Acta Informatica Nir has taught courses such as Principles of Concurrent Programming (Chalmers, 2019-2025), Advanced C++ Programming (University of Leicester, 2012-2017), and Synthesis from Temporal Specifications (University of Buenos Aires, 2010). He actively recruits PhD candidates and has hosted postdoctoral researchers at multiple institutions.

Anna Gautierمشاهده پروفایل

استادیار

• Multi-Agent Systems
• Robotics
• Artificial Intelligence
• +۳ مورد دیگر

Anna Gautier is an Assistant Professor in the Department of Computer Science at Chalmers University of Technology, affiliated with the Division of Data Science and AI. Previously, she was a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology (2023–2025), focusing on mechanism design for multi-robot systems. Her research emphasizes planning under uncertainty, multi-agent systems, and human-robot interaction. She holds a PhD from the University of Oxford (2023), an MSc from the London School of Economics, and dual undergraduate degrees from Washington University in St. Louis. Education Background: PhD in Computer Science, University of Oxford (2023) MSc in Applied Mathematics, London School of Economics BA in Mathematics and BS in Computer Science, Washington University in St. Louis Research Interests: Dr. Gautier explores planning algorithms for multi-agent systems, particularly in uncertain environments. She designs mechanisms to coordinate robots and humans, leveraging game theory and formal methods. Her work addresses challenges like resource allocation, risk-aware decision-making, and trust in autonomous systems. Recent projects include contingency planning for autonomous vehicles and auction-based resource distribution. Professional Activities: She co-chairs the ECAI 2025 Demonstration Track and teaches the course Safe Robot Planning and Control at KTH. Her projects include collaborations with WASP-Nest (PerCorSo) and TECoSA on trustworthy autonomy. She actively publishes in top venues like AAMAS and AAAI. Labs and Teams: Affiliated with Chalmers' Data Science and AI division, she leads research in multi-agent systems and human-AI collaboration.

• Control Systems
• Electric Vehicles
• Hybrid Electric Vehicles
• +۴ مورد دیگر

Nikolce Murgovski is an Assistant Professor at Chalmers University of Technology, specializing in Mechatronics . He focuses on electric and hybrid vehicle energy management , autonomous driving systems , and optimization algorithms for powertrain design. His work bridges control theory , battery technology , and transport electrification . Current projects include CHARGE (2023–2026) for charging and trip planning , and EcoPilot (2022–2026) for energy-efficient autopilot development. Collaborates with institutions like Volvo Cars , Swedish Electromobility Centre , and VINNOVA on autonomous vehicle control and thermal energy systems . His recent publications emphasize convex optimization , eco-driving strategies , and collision avoidance in complex environments. He has contributed to tools like CONES for electromobility studies and has led research on hybrid powertrains and predictive energy management .

Tommy Löfstedtمشاهده پروفایل

دانشیار

• Machine Learning
• Computer Vision
• Medical Image Analysis
• +۴ مورد دیگر

Tommy Löfstedt is an Associate Professor at Umeå University , affiliated with the Department of Computing Science and the Department of Mathematics and Mathematical Statistics. His research focuses on machine learning , computer vision , and medical image analysis , with applications in life sciences, radiation therapy, and biomedical imaging. He leads multiple research projects, including AI-driven delineation in radiation therapy, quantitative MRI for radiotherapy, and machine learning for plant nutrient uptake. Current research emphasizes structured regularization methods to improve model interpretability and robustness. Key applications include medical image segmentation , Alzheimer's classification , and uncertainty estimation in MRI . Recent publications highlight his work on morphological regularization , adversarial attack mitigation , and multi-task learning in medical imaging contexts. His projects span 2022–2026 with funding for pediatric oncology automation and gynecological cancer staging. Affiliated with both computing and mathematical departments, he bridges algorithm development with applied mathematical frameworks in medical and life science domains.

• Robotics
• Autonomous Systems
• Formal Methods
• +۵ مورد دیگر

Jana Tumova is an Associate Professor at the Division of Robotics, Perception and Learning, KTH Royal Institute of Technology. Her research focuses on designing algorithms for safe, purposeful autonomous systems using formal methods to ensure rigorous specifications and guarantees. Applications span autonomous driving, UAV exploration, and network control. She teaches courses like Artificial Intelligence (DD2380) and leads the Robotics, Reading Group (FDD3316) . Her work emphasizes formal methods integration with AI, safety-critical control, and human-robot interaction. Notable research directions include risk-aware planning, belief space control, and contingency planning under uncertainty. She has published extensively on motion planning, robust control synthesis, and multi-agent systems. Key technical contributions include techniques like Belief Control Barrier Functions , Backward Underapproximate Reachability (BURNS) , and Transitional Grid Maps . She actively participates in interdisciplinary initiatives like the Control for Societal-Scale Challenges: Roadmap 2030 .

• Computer Architecture
• Reconfigurable Computing
• Network-on-Chip (NoC)
• +۷ مورد دیگر

Ioannis Sourdis is a Full Professor at the Department of Computer Engineering, Chalmers University of Technology, Sweden. His research focuses on computer architecture, reconfigurable computing, network-on-chip (NoC) design, memory systems, and fault-tolerant embedded systems, with applications in biomedical informatics and hardware security. Current projects include EUMMSS (Efficient Uncore Mechanisms for Multicore Space Systems, funded by the Swedish National Space Board) and eProcessor (European Processor Ecosystem, funded by the European Commission). Past initiatives include the DeSyRe project (on-demand system reliability), ECOSCALE (exascale reconfigurable computing), and SHARCS (secure hardware-software architectures). His work spans NoC router design (e.g., FastTrackNoC, DDRNoC), memory compression (MemSZ, L2C), and biomedical security applications (heartbeat-based protocols). He has published extensively in venues like DATE, ICS, PACT, and IEEE Transactions on Networking. Key research areas: Chiplet-based systems , hybrid memory architectures , FPGA acceleration , and real-time stream aggregation .

Georgios Andrikopoulosمشاهده پروفایل

استادیار

• Robotics
• Biomedical Engineering
• Control Systems
• +۴ مورد دیگر

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.

Anna Brunströmمشاهده پروفایل

استاد

• Computer Networking
• Internet Architectures
• 5G/6G Mobile Systems
• +۳ مورد دیگر

Anna Brunström is a Full Professor and Head of the Distributed Intelligent Systems and Communications Research Group (DISCO) at Karlstad University's Department of Computer Science. She holds a part-time role as a Researcher at the University of Malaga's Institute of Software Engineering and Technologies (ITIS). Her research focuses on computer networking, Internet architectures, low latency communication, and 5G/6G mobile systems. She leads the nationally funded DRIVE initiative and collaborates on European projects like 6G-PATH. She actively contributes to IETF standardization, notably as a former rmcat WG chair. Her work spans over 200 publications, emphasizing network measurement, latency optimization, and multipath protocols. Education: Ph.D. (1996) and M.Sc. (1993) from College of William & Mary, B.Sc. (1991) from Pepperdine University. Research Interests: Distributed systems, IoT networking (NB-IoT), satellite communication (Starlink), machine learning for positioning, and transport protocols (QUIC, MPTCP). Recent work includes latency-aware scheduling, 5G/6G performance analysis, and edge computing frameworks. Publications highlight trends in: 1) Satellite network throughput modeling, 2) 5G/6G architecture validation, 3) Machine learning applications for positioning and network analysis, 4) Cross-layer optimization of latency-critical services. Collaborations with industry and academia drive applied research in smart grids, healthcare, and automotive communication. Labs/Teams: DISCO group at Karlstad University, leading the DRIVE research profile and 6G-PATH consortium involvement.

• Mechatronics
• Signal Processing
• Control Systems
• +۷ مورد دیگر

Jonas Sjöberg is a Full Professor of Mechatronics at Chalmers University of Technology, where he leads the Mechatronic research group in the College of Engineering. His research spans multiple aspects of mechatronic systems with a strong focus on automotive applications. Sjöberg holds leadership roles in numerous research projects related to autonomous vehicles, vehicle control systems, and transportation safety. His research interests encompass a broad spectrum of mechatronics applications, with particular emphasis on model-based methods, signal processing, control systems, system identification, and optimization for design and product development of mechatronic systems. Sjöberg's work bridges theoretical control engineering with practical automotive applications, especially in the domains of Automotive Active Safety and Hybrid Electric Vehicles. Analysis of Sjöberg's recent publications reveals a strong research trajectory focused on autonomous vehicle technologies, with particular attention to vehicle dynamics control, intersection safety, road surface condition estimation, and optimization of vehicle maneuvers. His work demonstrates a consistent approach of applying advanced control theory to solve real-world transportation challenges, with increasing emphasis on machine learning techniques integrated with traditional control systems. Sjöberg actively supervises research and education at both undergraduate and graduate levels while leading multiple research projects funded by VINNOVA, the European Commission, and other organizations. His research group collaborates extensively with both academic institutions and industry partners in the automotive sector. His laboratory work focuses on mechatronic systems development, particularly for automotive applications including autonomous bicycles, bus docking systems, and vehicle control algorithms. The research group maintains strong connections with the automotive industry, particularly in Sweden's robust vehicle technology ecosystem.

Atila Alvandpourمشاهده پروفایل

استاد

• Integrated Circuits and Systems
• VLSI Design
• Analog and Mixed-Signal Circuits
• +۶ مورد دیگر

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.

• Computer Networking
• Internet Protocols
• Network Security
• +۳ مورد دیگر

Marco Chiesa is an Associate Professor at the KTH Royal Institute of Technology in the Intelligent Network System Lab (INSight) group under the Division of Software and Computer Systems . His research focuses on computer networking, particularly Internet protocols and architectures, with emphasis on security, privacy, network design optimization, and Software Defined Networking (SDN) approaches. Current research areas: SDN, IXPs, stateful packet processing, network monitoring Teaching roles: Advanced Internetworking (IK2215), Computer Hardware Engineering (IS1200), Network Systems with Edge or Cloud Datacenters (IK2227) Email: mchiesa@kth.se Recent publications highlight advancements in high-speed packet processing, network security, and SDN applications. Key trends include leveraging programmable switches for stateful operations, improving BGP hijacking detection, and optimizing network monitoring on multi-pipeline architectures.

• Information Security
• Cybersecurity
• Software Architecture
• +۵ مورد دیگر

Mathias Ekstedt is a Professor of Industrial Information and Control Systems at KTH Royal Institute of Technology in Stockholm, Sweden. Affiliated with the Software Systems Architecture and Security (SSAS) research group under the Division of Network and Systems Engineering in the Department of Computer Science, School of Electrical Engineering and Computer Science (EECS). He holds a Ph.D. (2004) and M.Sc. (1999) from KTH. Co-founder of foreseeti (acquired by Google in 2022) Director of KTH's Master Programme in Cybersecurity Member of the Digital Futures research center's Trust Working Group Affiliated with Center for Cyber Defense and Information Security (CDIS) Ekstedt's research focuses on information security and cybersecurity integrated with software/systems architecture modeling and analysis . His work emphasizes probabilistic attack/defense graphs for system-of-systems security evaluation, particularly in SCADA and Industrial Control Systems within power infrastructure. He has developed the Meta Attack Language (MAL) and collaborated extensively with the power industry. Recent research trends (2022-2025) include: Threat modeling languages for ICT and power systems Probabilistic attack graph applications in energy flexibility markets and smart cities Software Bill of Materials (SBOM) challenges in Java ecosystems Dynamic attack graph generation and lazy evaluation techniques Cyber-physical security for low-voltage grids and substation automation Ekstedt supervises 17 Ph.D. students (11 as main supervisor, 6 as co-supervisor) and has mentored numerous postdocs. He leads major projects like the SSF project CHAINS (software supply chain security) and coordinates initiatives within SweGRIDS , HONOR , and SOCCRATES .