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Zhonghai LuView profile

Professor

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

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

• Learning Engineering
• Technology-Enhanced Learning
• Question-Based Learning
• +12 more

Olof Bälter is a Professor in Computer Science at KTH Royal Institute of Technology, affiliated with the Division of Media Technology and Interaction Design within the School of Electrical Engineering and Computer Science. He is the founder of the Technology-Enhanced Learning research group and holds a focus on learning engineering and human-computer interaction. His research interests center on technology-enhanced learning , question-based learning , learning analytics , AI in education , and inclusive pedagogy . A consistent theme in his work is improving efficiency in education and daily life through digital tools. He developed the Pure Question-Based Learning (Pure QBL) methodology, a digital Socratic approach that enhances student engagement and learning outcomes. His work extends to wellness in education through initiatives like walking seminars, and he investigates digital interventions for mental health, such as online Cognitive Behavioral Therapy (CBT) courses. His recent publications highlight trends in AI-generated educational content , learning efficiency , digital pedagogy , and inclusive course design , with applications in computer science education, language instruction, and global development. His research often employs experimental and data-driven methods, including randomized controlled trials and learning analytics. Teacher of the Year at the Surveying program KTH's Pedagogical Prize Higher Education Hero STINT Excellence in Teaching Scholarship (2008 and 2013) Olof Bälter has supervised numerous courses in programming, computer science, media technology, and learning engineering. He has collaborated with institutions such as Stanford University, Williams College, Region Stockholm, Stockholm University, and organizations like Promobilia and Begripsam. His projects aim to scale effective learning methods globally and make education more accessible and efficient. He leads research on the effectiveness of Pure QBL for students with ADHD and is involved in developing digital tools for health literacy and professional development in Ethiopia and Rwanda. His work bridges theory and practice, aiming to transform educational delivery through innovation and evidence-based design.

Eva KosekView profile

Professor

• Chronic Pain Research
• Neuroimmunology
• Musculoskeletal Disorders
• +3 more

Professor Eva Kosek holds dual academic positions as Professor of Clinical Pain Research at Karolinska Institutet (since 2015) and Uppsala University (since 2020). She is affiliated with the Department of Clinical Neuroscience and leads the Mechanisms of Pain and Treatment Research Group . Her roles include senior consultant at Uppsala University Hospital's Pain Center. Education: MD from Uppsala University (1986), PhD from Karolinska Institutet (1996). Specializations: Rehabilitation Medicine (1998), Pain Relief (2001). Academic promotions: Associate Professor at Karolinska (2004), Full Professor (2015). Research Focus: Chronic pain mechanisms, neuroimmune interactions, fibromyalgia, and autoimmune pathways. Key projects include the RAFT trial (Rituximab for fibromyalgia autoantibody therapy) and the BACPAP consortium for low back pain phenotyping. She chairs IASP's Terminology Task Force, introducing the 'nociplastic pain' concept. Key Contributions: Discovered anti-satellite glial cell IgG antibodies in fibromyalgia patients, linked to symptom severity. Pioneered neuroimaging studies on pain modulation circuits. Authored over 300 publications, with recent work on cerebrospinal fluid biomarkers and lipid metabolite profiles. Awards: 2024 Roland Melzack Lecture Award from IASP. Recognized for redefining pain taxonomy and translational research. Grants: Active funding includes Swedish Research Council grants on fibromyalgia autoimmunity, environmental exposures, and neuroinflammation. Total grants exceed SEK 100M over her career. Labs/Teams: Leads a multidisciplinary team at Karolinska's Pain Research Center, collaborating internationally on translational pain studies. Active in biobanking initiatives like the Swedish Chronic Pain Biobank.

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +4 more

Zenun Kastrati is an Associate Professor at the Department of Informatics, Linnaeus University. His research focuses on Artificial Intelligence, Natural Language Processing, Machine Learning, Semantic Web, Sentiment Analysis, and Learning Technologies. He contributes to the Data-driven Business Innovation (DBI) and Interaction Design Research Groups, leading projects like Forest 4.0, RAPID, and IGNITE. His recent work involves Explainable AI, medical imaging, and multilingual NLP. Ph.D. in Computer Science (NTNU, 2018) Master's in Computer Science (EU TEMPUS Programme) Previous Lecturer/Researcher at University of Prishtina His research spans AI applications in medical diagnostics , NLP , sentiment analysis , and semantic technologies . Key projects include Forest 4.0 (environment monitoring) and RAPID (online education in Pakistan). Publications highlight his expertise in deep learning , transformer models , and context-aware systems . Recent publications demonstrate trends in Explainable AI (XAI) for healthcare, medical imaging techniques, and multilingual NLP frameworks. Other work explores social media analytics , student feedback analysis , and pedagogical document classification . Zenun's teaching includes Fundamentals of Programming , Object-Oriented Programming , Web Applications , Data Analytics , and Adaptive Web courses at BSc and MSc levels.

• Robotics
• Human-Robot Interaction
• Machine Learning
• +7 more

Christian Smith is an Associate Professor and Lecturer at the Department of Robotics, Perception and Learning at Kungliga Tekniska Högskolan (KTH Royal Institute of Technology). His research focuses on robotics and applications in human-centered environments like home environments, small workshops, and healthcare facilities, including the development of new robotic systems for research. Teaching Roles: Course Coordinator/Teacher/Examiner for courses such as Introduction to Robotics (DD2410), Research Project in Robotics (DD2411), and Java Programming for Python Programmers (DD1380) Research Themes: Human-Robot Interaction, Behavior Trees, Exoskeletons, Intent Recognition, and Multimodal Perception Awards: No specific scientific awards mentioned in the provided text His KTH profile highlights work on adaptive robotics systems and formalized control strategies. The research portfolio spans from theoretical studies on behavior tree programming to applied work in assistive technologies and teleoperation systems.

Tommy LöfstedtView profile

Associate Professor

• Machine Learning
• Computer Vision
• Medical Image Analysis
• +4 more

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.

Zebo PengView profile

Professor

• Embedded Systems
• Electronic Design Automation
• SoC Testing
• +6 more

Zebo Peng is a Professor and Deputy Head of Department at Linköping University's Department of Computer and Information Science (IDA), leading the Software and Systems (SAS) division. His research focuses on embedded systems design, electronic design automation, SoC testing, and real-time systems with emphasis on fault tolerance and hardware/software co-design. He has contributed to projects like the ASTECC initiative, funded by the Swedish Foundation for Strategic Research, addressing adaptive software in edge-cloud continuum systems. Key research interests include cyber-physical systems security, time-sensitive networking (TSN), and optimization techniques using genetic algorithms. Recent work explores thermal-aware design for reliability, security-aware scheduling, and stability guarantees in control systems. His publications span journals like IEEE TPDS and ACM TECS, alongside conference contributions on topics like resource management and fault detection in distributed systems. Prof. Peng collaborates extensively within the SAS division, which bridges academic and industrial research in software engineering and computer systems. His team's projects address challenges in real-time systems, embedded security, and parallel computing architectures.

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

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

• Space Robotics
• Control Theory
• Computer Vision
• +4 more

Pedro Roque is a Postdoctoral Researcher at KTH Royal Institute of Technology in Stockholm, affiliated with the Wallenberg AI, Autonomous Systems and Software Program (WASP) and associated with the Division of Decision and Control Systems (DCS). He obtained his Ph.D. in 2024 from the same division under the supervision of Prof. Dimos Dimarogonas, Prof. Mikael Johansson, and Prof. Jana Tumova. His research focuses on practically applicable theoretical results in robotics and control, with emphasis on space and aerial systems. Dr. Roque is particularly interested in developing algorithms that directly contribute to system performance and enhanced capabilities. He currently leads the setup of a Space Robotics Laboratory at KTH, associated with the Space Center and the WASP NEST DISCOWER project. He is an advocate for open-source software and hardware, contributing to NASA Astrobee and PX4 projects, with his research tested on the International Space Station and indoor flight arenas. Dr. Roque's work demonstrates a clear progression from theoretical foundations to practical implementation in space environments. His recent publications show an increasing focus on multi-agent coordination in microgravity, with significant contributions to model predictive control for space robotics applications. The research spans from fundamental control theory to complete system implementation, reflecting his commitment to bridging theory and practice. ICRA 2022 Outstanding Coordination Award for work on decentralized model predictive control for collaborative UAV bar transportation Dr. Roque actively mentors Master's students in Space Robotics, Control, and Vision, with supervision details available on his personal website. He has collaborated extensively with NASA Astrobee and PX4 projects, and his DISCOWER project involves collaboration with 3 Ph.D. students, 2 Master's students, 6 Professors, and one Post-doc. He also completed a 4-month internship at JPL within the Maritime and Multi-Agent Systems group. He leads the Space Robotics Laboratory at KTH, associated with the Space Center and the WASP NEST DISCOWER project, which has already demonstrated capabilities to Digital Futures, SAAB AB, SAAB Inc., and Purdue scholars. The laboratory focuses on weightless robotics, collaborative robotics (Space Cobot), and exploration robotics (MoonHopper), with practical testing on the International Space Station.

Claudia Bernhard-OettelView profile

Professor

• Work and Organizational Psychology
• Temporary and Part-Time Employment
• Self-Employment and Gig Economy
• +7 more

Claudia Bernhard-Oettel is a Professor and Deputy Head of Department at the Department of Psychology, Stockholm University , with a focus on work and organizational psychology . Her career spans roles at institutions like the Swedish Institute for Working Life, Södertörn University College, and Karolinska Institutet, where she coordinated interdisciplinary initiatives in the Stockholm Stress Center. She serves on editorial boards and grant review committees, including the Research Council for Health, Working Life and Welfare (FORTE) and the Academy of Finland. Education: Diplom in Psychology (equivalent to Master's) from TU Dresden (2001); PhD in Psychology from Stockholm University (2008). Her research examines changing labor markets , emphasizing temporary employment , self-employment , and gig work . Key areas include organizational justice , effort-reward imbalance , and career sustainability . She investigates how job insecurity and psychological contracts affect health, well-being, and career transitions. Recent articles highlight trends in temporary agency work narratives , illegitimate tasks , and self-employment health trajectories . Her workgroup-level analyses of leadership and task design offer practical insights into mitigating stress and turnover in the public sector. Scientific Contributions: Editorial leadership in the Scandinavian Journal of Work and Organizational Psychology (2019–2024). Coordination of the Stockholm Stress Center Graduate School (2017–2018). Membership in grant review committees for FORTE and the Academy of Finland. Advising: Supervised doctoral students in alternative employment forms , organizational justice , and workplace lock-in . Current supervisees include Louise Bergman (2025 defense) and Clara Plückelmann.

Damir IsovicView profile

Associate Professor

• Real-Time Systems
• Embedded Systems
• Scheduling Algorithms
• +3 more

Damir Isovic is an Associate Professor and Vice-Chancellor for Internationalization at Mälardalen University's Academy of Innovation, Design and Technology. Previously, he served as Dean of the School of Innovation, Design and Engineering. His roles include leadership in academic administration and participation in national boards. He holds a PhD and has extensive international teaching experience. Research focuses on real-time systems, embedded systems design, and scheduling algorithms. Notable contributions include seminal work in real-time scheduling recognized by the IEEE Technical Community on Real-Time Systems. He has organized major conferences and delivered keynotes globally. His publications emphasize hybrid scheduling approaches, real-time operating systems (RTOS), media processing in resource-constrained systems, and MPEG standards. Recent work integrates memetic algorithms with fuzzy controllers and explores multi-core scheduling fairness. His research bridges theoretical scheduling models with practical embedded system implementations. No scientific awards explicitly listed in the text. Advising activities include supervising PhD students, though specific names are not provided. Lab affiliations include the Division of Networked and Embedded Systems, where he develops frameworks like GENESIS for embedded system engineering. His work emphasizes cross-disciplinary collaboration and industry partnerships in education and technology development.

Andreas J. KasslerView profile

Professor

• Software Defined Networking
• Programmable Dataplanes
• Network Virtualization
• +7 more

Andreas J. Kassler is a Full Professor of Computer Science at Karlstad University, Sweden, where he has been since 2005. He co-chairs the Distributed Systems and Communication (DISCO) group and focuses on networking, cloud computing, and wireless networks. His research includes software-defined networking, future internet architectures, and network optimization. He has authored/co-authored over 130 peer-reviewed publications, holds 6 patents, and serves on editorial boards of journals like Journal of Internet Engineering . Education : Ph.D. in Computer Science, Universität Ulm (2002) Docent (Habilitation), Karlstad University (2007) M.Sc. in Mathematics/Computer Science, Universität Augsburg (1995) Research Interests : Software Defined Networking (SDN) Programmable Dataplanes Wireless Mesh Networks Time-Sensitive Networking (TSN) Edge Computing Machine Learning for Network Optimization Recent Directions : His work spans TSN scheduling, hybrid P4 solutions for 5G, and explainable AI in energy communities. He explores network resilience, latency optimization, and multi-objective control in microgrids. Service Contributions : Track co-chair for VTC 2015 General chair for Wired/Wireless Internet Communications (WWIC) 2013 Editor-in-Chief of IARIA Journal on Advances in Internet Technology Labs/Teams : Leads DISCO group at Karlstad University. Collaborates with global teams on projects like mmWave backhaul networks and SDN-enabled industrial control systems.

• Human-Robot Interaction
• Social Robotics
• Group Dynamics
• +3 more

Sarah Gillet is a Postdoctoral Researcher at the Division of Robotics, Perception, and Learning at KTH Royal Institute of Technology, where she focuses on developing social robot behaviors to foster collaboration and inclusion in human groups. Her research addresses challenges like in-group favoritism through computational approaches to shape group interactions. She holds a Doctoral Thesis (2024) titled Computational Approaches to Interaction-Shaping Robotics . Her work emphasizes group dynamics , robot-mediated inclusion , and pedagogical robotics , particularly in children and adolescent populations. Key areas include gaze behavior analysis, equitable participation promotion, and social robot roles such as mediators in educational settings. Dr. Gillet teaches the Social Robotics (DD2413) course and supervises master theses. Her recent publications explore robot gaze behaviors for participation balance, socially appropriate listening, and influence prediction models like RoSI. She actively participates in conferences like ACM/IEEE HRI and IEEE RO-MAN. Her research integrates computational methods with social science insights to design robots that actively improve human group interactions, with applications in education, collaboration, and bias mitigation.

• Artificial Intelligence
• Neural Networks
• Computational Neuroscience
• +4 more

Summary Pawel Andrzej Herman is an Associate Professor at the Division of Computational Science and Technology within the School of Computer Science and Communication (CSC) at KTH Royal Institute of Technology. His research focuses on computational neuroscience, brain-inspired AI, and machine learning applications in healthcare and cognitive science. He teaches multiple courses including Artificial Neural Networks and Deep Architectures , supervises degree projects across computer engineering and electrical engineering disciplines, and actively contributes to interdisciplinary research initiatives. His work bridges theoretical neuroscience with practical AI solutions, emphasizing synaptic plasticity models, neuromorphic computing, and medical diagnostic systems. Key areas include olfactory perception modeling, working memory mechanisms, and FPGA-accelerated neural networks. He collaborates internationally on projects such as AI-driven medical imaging and cognitive neuroscience studies. Dr. Herman’s research has been published in high-impact journals and conferences, with recent contributions to understanding neural mechanisms of odor naming deficits, beta/alpha oscillations in working memory, and spiking neural network architectures. His technical leadership spans HPC frameworks like StreamBrain and interdisciplinary tools for scientific data storage (NoaSci).

Tony LindebergView profile

Professor

• Computer Vision
• Computational Neuroscience
• Medical Image Analysis
• +4 more

Tony Lindeberg is a Professor of Computer Science—Computational Vision at KTH Royal Institute of Technology, affiliated with the Division of Computational Science and Technology. He teaches the course Image Analysis and Computer Vision (DD2423). His research focuses on scale-space theory, early vision, and computational modeling of biological and auditory vision systems. Key contributions include theories on receptive fields, time-causal spatio-temporal models, and feature detection algorithms. Research interests span computational neuroscience, medical image analysis, and spatio-temporal recognition. Lindeberg has pioneered work on scale-invariant image features, affine transformations, and Galilean diagonalization for motion analysis. He is the author of the foundational book Scale-Space Theory in Computer Vision (1993). His work bridges computer vision and biological vision systems, with applications in gesture recognition, dynamic texture analysis, and neural networks. He leads the Vision Lab and Computational Brain Science Lab at KTH, emphasizing theoretical rigor and practical algorithms for visual perception tasks.