جست‌وجوی استاد و پژوهشگر

Erdal Aksoyمشاهده پروفایل

دانشیار

• Semantic Scene Perception
• Action Semantics
• Autonomous Systems
• +۹ مورد دیگر

Erdal Aksoy is an Associate Professor at Halmstad University 's School of Information Technology , with visiting scholar roles at Volvo Group Trucks Technology and Zenseact AB . His work focuses on semantic scene perception , action semantics , and environment understanding for autonomous systems including robots and unmanned vehicles. Education : PhD from University of Göttingen, postdoctoral research at Karlsruhe Institute of Technology (KIT) and University of Göttingen Research Interests : Semantic scene perception, action semantics, autonomous systems, human-robot interaction, LiDAR processing, and deep learning applications His recent publications demonstrate expertise in LiDAR data processing (SalsaNet, SalsaNext), semantic state estimation for robotic cloth manipulation, and multimodal failure detection systems. He has coordinated the HORIZON Europe ROADVIEW consortium with 15 partners. Scientific recognition includes Best Student Paper Award at IJCAI 2021 AI4AD workshop Best AI Master’s Thesis Award from Swedish AI Society (SAIS) Wimanska Prize for best bachelor thesis Distinguished Service Award as IEEE Robotics and Automation Letters Associate Editor His advising track record shows mentorship of award-winning students across bachelor, master, and PhD levels. Erdal Aksoy maintains active collaborations between academia and industry, particularly with automotive technology companies.

• Computer Systems
• Operating Systems
• Distributed Systems
• +۱ مورد دیگر

Luke Cheeseman serves as a Research Fellow in the Division of Computer Systems at Uppsala University's Department of Information Technology, contributing to the institution's research initiatives in computational infrastructure and system design. His research profile, inferred from departmental alignment, centers on foundational computer systems disciplines including: Operating Systems Distributed Systems Computer Architecture Embedded Systems These areas address critical challenges in system reliability, resource optimization, and hardware-software integration for modern computing environments.

James Nguyenمشاهده پروفایل

مدرس

• Philosophy of Science
• Scientific Modeling
• Epistemology
• +۳ مورد دیگر

James Nguyen is an academic researcher at the Department of Philosophy , Stockholm University , focusing on philosophy of science, epistemology, and scientific modeling. His work critically examines the nature of scientific representation, model-based understanding, and theoretical frameworks. University: Stockholm University Department: Department of Philosophy Nguyen’s research investigates how scientific models function as representational tools, with particular interest in their epistemic reliability and philosophical foundations. His publications address topics such as the fiction view of models, explanatory reasoning, and the stabilization of scientific understanding. His recent publications (2021–2025) span diverse subfields including scientific representation theory, modeling practices, epistemic trust in models, and interdisciplinary philosophical critiques. Despite the absence of explicit awards or student advising information in the available texts, his work remains deeply embedded in theoretical and methodological debates within contemporary philosophy of science.

• Power Electronics
• Electric Vehicles
• Traction Motor Systems
• +۴ مورد دیگر

Artem Rodionov is a researcher at Chalmers University of Technology, specifically affiliated with the Department of Electrical Power Engineering . His work focuses on power electronics and electric vehicle technologies, with specialization in traction drive systems and energy efficiency optimization. Current projects: LongDrive (2024–2027) with Volvo Group and Energimyndigheten, PowerDrive (2022–2025) funded by EU, and Integrerade drivsystem (2016–2020) with Energimyndigheten Collaborators: Yujing Liu, Nimananda Sharma, Alessandro Acquaviva, Anton Kersten Key research themes include: Power electronics for transportation electrification High-density drive systems for EVs Thermal management of power modules Multi-motor drivetrain verification Capacitor dimensioning in traction applications Publication trends show expertise in: IEEE Transactions: Inverter loss analysis IECON Conferences: Capacitor sizing, bus bar inductance Doctoral thesis: High power density EV drives Multi-phase motor efficiency studies Cooling system parameter sensitivity

• Information Network Analytics
• Decentralized Machine Learning
• Data Mining
• +۵ مورد دیگر

Sarunas Girdzijauskas is a Professor at the Department of Computer Science within KTH Royal Institute of Technology's School of Electrical Engineering and Computer Science (EECS), where he leads the Graph Analytics and Network Learning group (GALE) . He also holds a Senior Researcher position at RISE (Research Institutes of Sweden) and has served as Program Director for EECS's doctoral program in Information and Communication Technology (2019-2022) and Deputy Director of Third-Cycle Education at EECS. PhD from Ecole Polytechnique Fédérale de Lausanne (EPFL) in 2016 Docent in Computer Science at KTH (2016) Coordinated multiple large-scale projects: H2020 Marie Curie RAIS, Marie Curie ITN iSocial Research Focus : His work spans decentralized machine learning systems, graph analytics, and blockchain infrastructure. Key areas include: Information network analysis for social and technical systems Federated learning with adaptive personalization Graph partitioning and distributed algorithms Privacy-preserving models with differential privacy Knowledge distillation for evolving graph representations Scalable solutions for big data and IoT botnet detection Article Trends : Recent work demonstrates convergence of graph neural networks with federated learning, emphasizing privacy (differential privacy in 5/15 articles), robustness (out-of-distribution detection in 3 articles), and decentralized infrastructure (blockchain, gossip protocols, and P2P overlays). The articles frequently address temporal modeling, knowledge distillation, and heterogeneous graph representations. Scientific Leadership : Coordinated H2020 Marie Curie European Training Network 'RAIS' (2018-2023) Coordinated Marie Curie ITN 'iSocial' (2012-2017) Activity Leader for EIT Digital Innovation Activities Teaching & Advising : Has supervised/examined over 60 master theses and currently advises 8 PhD students, including Adam Orucu (Main Supervisor, 2024-), Filip Cornell (Main Supervisor, 2020-), and Ahmed Emad Samy Youssif (Main Supervisor, 2019-). Former supervisees include 9 PhDs like Dr. Edvin Listo Zec (2025) and Dr. Debaditya Roy (2024).

• Machine Learning
• Artificial Intelligence
• Vehicular Communication
• +۴ مورد دیگر

Cristofer Englund is the Dean of the School of Information Technology at Halmstad University and holds a professorship in Information Technology. He earned his PhD in Electrical Engineering in 2007. His teaching focuses on supervising bachelor and master’s theses in machine learning and artificial intelligence (AI), with students receiving awards such as Wimanska priset (2019) and the SAIS Master Thesis Award (2017, 2021). His research spans machine learning applications in emotion/posture recognition, behavior prediction, anonymization, and vehicular communication for traffic safety and automated driving. He currently supervises Felix Rosberg (Engage Studios) on image/video anonymization and Maytheewat Aramrattana (VTI) on connected transportation safety analysis. Research interests include AI ethics, safety-critical systems, and smart city technologies. Recent work emphasizes de-identification systems, drone detection, and federated learning in automotive ecosystems. His articles analyze AI applications in urban infrastructure, cybersecurity for anonymization, and real-time drone surveillance. Notable student awards include grants for Felix Rosberg’s work on anonymization defense mechanisms and Maytheewat’s contributions to traffic safety modeling. Englund collaborates with industry partners like Engage Studios and VTI, integrating academic research with real-world challenges. His work bridges theoretical advancements in machine learning with practical implementations in transportation, cybersecurity, and urban planning.

• Computer Networking
• Low Latency Communication
• Multi-Path Systems
• +۳ مورد دیگر

Johan Garcia is an Associate Professor of Computer Science at Karlstad University, Sweden, where he earned his Ph.D. in 2005. His research focuses on computer networking, particularly low-latency communication in multi-path systems, Starlink satellite performance, and deterministic network emulation using tools like KauNetEm. He has led projects such as the 8-year DRIVE initiative and the HITS project, collaborating with industry partners like Icomera. His work includes evaluating cellular and satellite connectivity for trains, as well as machine learning explainability and network protocol optimization. Education: Ph.D. in Computer Science (Karlstad University, 2005). Key projects include KauNetEm development, mobility testing across the Arctic Circle for Starlink/5G, and sectorization-based localization algorithms for eNodeBs. His research spans wireless networking, protocol evaluation, and algorithmic optimization for network reliability and performance. Research interests include: satellite communication performance, cellular networks in high-speed mobility, deterministic network emulation, ML model interpretability, and protocol efficiency in heterogeneous networks. He has advised multiple master’s and bachelor’s projects and contributed to over 100 publications since 2000. Notable collaborations include the EU FP6 Newcom Network of Excellence and the Swedish Knowledge Foundation-funded 'Reliable and Secure Communication in SCTP' project. Current roles include sub-project manager in DRIVE and co-leader of wireless network modeling work packages.

• Control Theory
• Dynamical Network Systems
• Social Network Analysis
• +۳ مورد دیگر

Ye Tian is a Researcher at the Division of Decision and Control Systems at KTH Royal Institute of Technology. His current position is under the supervision of Professors Karl Henrik Johansson and Angela Fontan. He holds a PhD in Control Theory and Control Engineering from Xidian University (2021), advised by Professor Long Wang. Previously, he was a visiting student at the University of California, Santa Barbara (2017–2019), working with Professors Francesco Bullo and Noah E. Friedkin. Between 2021 and 2025, he held research positions at Peking University, Kyoto University, and Nanyang Technological University. His research focuses on dynamical network systems, particularly in social networks applications. This involves interdisciplinary approaches combining control theory, network dynamics, and computational methods. His work addresses challenges in system stability, distributed control, and networked decision-making processes. Ye Tian's scholarly contributions span high-temperature electronics, silicon carbide integrated circuits, and sigma-delta modulators. His publications highlight advancements in semiconductor materials and circuit design for extreme environments, with applications in aerospace, energy systems, and sensor networks.

Björn Lisperمشاهده پروفایل

استاد

• Computer Science
• Software Engineering
• Real-Time Systems
• +۵ مورد دیگر

Björn Lisper is a Professor at Mälardalen University, Sweden, affiliated with the School of Innovation, Design and Engineering and the Division of Computer Science and Software Engineering. His research focuses on formal methods, real-time systems, embedded software, static analysis, and high-level synthesis. He has contributed to advancements in WCET analysis, machine learning applications in testing, and compiler optimization techniques. His work emphasizes practical industrial applications, particularly in automotive and multi-core systems. Research Interests: Real-Time Systems & WCET Analysis Static Program Analysis High-Level Synthesis for FPGAs Machine Learning in Software Testing Formal Methods & Verification Embedded Systems Design Publications span topics like neural network accelerators, automated testing frameworks, and compiler optimizations, reflecting a blend of theoretical and applied computer science. His work is characterized by collaboration between academia and industry to bridge gaps in embedded software predictability and performance.

Mikael Asplundمشاهده پروفایل

استادیار

• Cyber-Physical Systems Security
• Formal Methods
• Dependability and Reliability
• +۹ مورد دیگر

Mikael Asplund is an Assistant Professor in the Department of Computer Science at Linköping University, affiliated with the Software and Systems (SAS) division. His research focuses on the security and reliability of cyber-physical systems, particularly in intelligent transportation, smart grids, and autonomous systems. Research Interests: His work integrates formal reasoning, protocol design, and evaluation through simulations and real-world testbeds. Key areas include formal verification of security protocols, remote attestation, automated penetration testing, and vulnerability analysis in critical infrastructure such as EV charging and battery storage systems. Recent Research Trends: His recent publications (2023–2025) emphasize formal methods for security assurance, automated testing, and the application of these techniques to emerging technologies like 5G/6G networks, electric vehicles, and energy systems. There is a strong focus on provable security and practical implementations in embedded and distributed environments. Best paper award at ARES 2024. Nominated for best student paper at VEHITS 2025. Academic Leadership and Grants: He leads or co-leads major projects funded by WASP, ELLIIT, Vinnova, SSF, and Horizon Europe, including Automating Security Assurance using Formal Methods , Protocol Security Verification , and CyberSecDome . He is responsible for the Master’s Program in Cybersecurity and the IT program at LiU, and actively promotes innovation in computer science education. He also coordinates the Cybersecurity Lab at LiU, a dedicated facility for hands-on cybersecurity training.

Jörgen Olssonمشاهده پروفایل

استاد

• Solid-State Electronics
• High-frequency MOS-based devices
• SOI-technology
• +۴ مورد دیگر

Professor Jörgen Olsson is a faculty member at Uppsala University's Department of Materials Science and Engineering with a specialization in Solar Cell Technology. He serves as Deputy Head of Department and Director of Postgraduate Studies, while also participating in multiple university committees including the Doctoral Education Board (FUN), Teknat Faculty Advisory Committees for both Research and Education, and the Teknat Equal Opportunities Committee. Ph.D. in Electronics from Uppsala University (1996) Visiting Scientist at Digital Semiconductor, Hudson, MA (1997) Promoted to Professor in Solid-State Electronics (2008) Professor Olsson's research spans semiconductor device physics with evolving focus areas. Early work centered on high-frequency MOS-based devices, SOI-technology, and RF-power devices. His more recent research has shifted toward photovoltaics, particularly thin-film solar cells including CIGS and CZTS technologies. His publications demonstrate expertise in both fundamental semiconductor physics and practical device applications, with significant contributions to understanding device behavior under various conditions. Analysis of his recent publications (2016-2022) reveals a dual research trajectory: continued work on RF power devices and amplifiers for particle accelerators, alongside growing contributions to photovoltaic technology. His work bridges electrical engineering and materials science, with applications ranging from wireless communications to renewable energy. The consistent publication record demonstrates sustained research productivity across multiple domains of semiconductor device physics. Professor Olsson has served in significant academic leadership roles including Director of Postgraduate Studies and Deputy Head of Department. His extensive publication record (over 180 scientific papers) indicates substantial research activity and mentorship within his field. His work with the Doctoral Education Board suggests active involvement in graduate education and academic program development. At the Ångström Laboratory, Professor Olsson headed the Solid State Device Group, where research spanned semiconductor device fabrication, characterization, and modeling. His work connects fundamental device physics with practical applications in both electronics and renewable energy sectors, reflecting the interdisciplinary nature of modern materials science research.

Martin Jacobssonمشاهده پروفایل

دانشیار

• Machine Learning
• Biomedical Engineering
• IoT and Wearable Technologies
• +۵ مورد دیگر

Martin Jacobsson is an Associate Professor at the School of Computer Science and Communication (CBH) at KTH Royal Institute of Technology, affiliated with the Digital Futures Faculty. He co-founded the Digital Futures research center, which focuses on cross-disciplinary digital technologies addressing societal challenges such as healthcare innovation, IoT systems, and wireless communication. His work emphasizes practical applications with high industrial relevance and strategic importance through collaborations with Stockholm University and RISE Research Institutes of Sweden. His research interests span machine learning in clinical decision support, biomedical data compression, wearable sensor networks, and low-power wireless communication protocols. Notable projects include drone-based motion capture systems for sports analytics, embedded emergency systems, and predictive models for surgical outcomes using ML techniques. Publications highlight contributions to healthcare informatics (e.g., trauma care improvement), IoT device optimization (e.g., battery-free wearables), and wireless network protocols (e.g., LoRaWAN interference analysis). His work bridges theoretical advancements with real-world implementations in healthcare, sports, and industrial IoT. He is actively involved in the Digital Futures community, engaging through LinkedIn, YouTube, and academic conferences. The center is located at Osquars Backe 5 in Stockholm, with contact via info@digitalfutures.kth.se.

• Embedded Systems
• FPGA Design
• Fault Tolerance
• +۵ مورد دیگر

Johnny Öberg is an Associate Professor at the Division of Electronics and Embedded Systems, KTH Royal Institute of Technology. He specializes in embedded systems, FPGA design, and fault-tolerant hardware architectures. His research focuses on radiation effects in electronics, machine learning acceleration, and network-on-chip (NoC) systems. He teaches and examines courses such as Computer Systems Architecture (IS2202), Embedded Hardware Design in ASIC and FPGA (IL2225), and Embedded Systems Design Project (IL2232). His work often bridges theory and practice, emphasizing real-world applications in aerospace, automotive, and IoT domains. Key research trends include improving reliability in SRAM-FPGAs through statistical fault injection, developing hardware-accelerated machine learning frameworks, and optimizing NoC architectures for predictable performance in mixed-criticality systems. Recent projects include the SAFEPOWER architecture for energy-efficient systems and collaborations on structural health monitoring using Lamb wave analysis. No scientific awards are explicitly mentioned in the provided texts. Johnny has advised on multiple degree projects but no specific student names are listed. His contributions include foundational work in GALS (Globally Asynchronous, Locally Synchronous) communication bridges and protocol grammars for low-power implementations. Labs/teams: Active involvement in the ICES (Innovative Centre for Embedded Systems) and the Suaineadh project for space-deployable structures. Collaborates on interdisciplinary initiatives like the ABB NoC and Panacea NoC prototypes.

• Artificial Intelligence
• Machine Learning
• Virtual Sensors
• +۳ مورد دیگر

Stefan Byttner is a Professor at the School of Information Technology, Halmstad University. His research focuses on artificial intelligence, machine learning, virtual sensors, safe AI (XAI), and monitoring of heterogeneous mechatronic systems. He supervises doctoral students in XAI and leads major initiatives like the "MAISTR" program and "Innovation platform AI.m". Master's Program Manager (2015-2018) Director of Doctoral Program (2012-2018) Head of Department ISDD (2018-) Acting Dean, School of Information Technology (2022-2023) Collaboration Leader at ITE (2017-2018) His research integrates AI with mechatronics and industrial IoT , emphasizing explainability and safety in deployed systems. Recent work explores graph neural networks for clinical and spatiotemporal forecasting applications, as well as diffusion models for time series imputation. Key publication trends include neuroimaging AI , time series modeling , and industrial anomaly detection . Applications span district heating systems , vehicle diagnostics , and healthcare analytics with PET scans. Teaching areas include artificial intelligence, data mining, thesis supervision at bachelor's and master's levels, and technology-democracy intersections. No awards or student names are explicitly mentioned in available texts.

• Computer Science
• Wireless Sensor Networks
• Software Technologies
• +۹ مورد دیگر

Edison Pignaton De Freitas is a Professor at the School of Information Technology , Halmstad University. His research focuses on wireless sensor networks and software technologies, particularly in applications involving UAVs and intelligent transportation systems. Research areas include machine learning for energy systems, vehicular network safety protocols, and software-defined networking Recent publications emphasize intelligent infrastructure models (2025), UAV base station positioning (2025), and SDN-based FANET emulation (2025) Key contributions span multiple domains: Scientific Focus: - Machine learning applications in photovoltaic systems and transportation networks - UAV communication optimization and swarm intelligence algorithms - Energy-efficient sensor network design for healthcare and military surveillance - Advanced antenna array positioning methods for vehicular scenarios