Per-Olov Östberg is an Associate Professor at the Department of Computing Science, Umeå University, and a research leader in the Autonomous Distributed Systems Lab (ADSLab). His work focuses on resource management for distributed cloud environments using AI/ML-based techniques, with a particular emphasis on ethical reasoning integration for responsible AI solutions. Research Themes: Cloud-edge continuum optimization, serverless frameworks, 6G computing challenges, data fabric architectures, and energy-aware systems Projects: COGNIT (cognitive serverless framework), WARA Common Information Bridge (data-driven cloud operations), De facto Center of Excellence in Autonomous Distributed Systems His publications (2011-2024) demonstrate consistent contributions to cloud resource management, including fairshare scheduling, decentralized prioritization, and power-performance tradeoffs. He has collaborated on interdisciplinary projects with institutions across Europe. Scientific Awards: None explicitly stated in provided information.
Leif Asp is a Professor in Lightweight Composite Materials and Structures at Chalmers University of Technology, working within the Division of Materials and Computational Mechanics. His research focuses on developing innovative materials that serve multiple functions, particularly structural batteries that can simultaneously store energy like a battery and carry mechanical load. Professor Asp's primary research interests include: Structural batteries and multifunctional composites Carbon fiber-based energy storage materials Synthesis, characterization, and design of multifunctional materials Mechanical and electrochemical properties of composite materials Computational modeling of structural battery systems Sustainable manufacturing and life cycle analysis of structural power composites His work bridges the gap between traditional structural materials and energy storage systems, creating what's often referred to as "massless energy" solutions. These materials could revolutionize industries like electric vehicles and aerospace by reducing overall weight while maintaining or increasing energy capacity. Analysis of Professor Asp's recent publications reveals a strong focus on practical implementation of structural battery technology. His research spans fundamental material science (characterizing carbon fibers for battery electrodes), engineering design (optimizing structural battery components), and systems integration (assessing viability for electric vehicles and aerospace applications). A notable trend is the increasing emphasis on sustainability, with several recent papers addressing recycling, life cycle analysis, and green synthesis methods for structural battery components. Professor Asp leads multiple significant research projects funded by prestigious organizations including the United States Air Force, Swedish Research Council, European Commission, and Swedish Innovation Agency. These projects focus on advancing structural battery technology from laboratory concepts toward practical applications. His research group appears to be highly collaborative, with numerous publications featuring co-authors from various institutions and disciplines, reflecting the interdisciplinary nature of structural power composites research.
Håkan Johansson is a Professor in the Dynamics division of the Department of Mechanics and Maritime Sciences at Chalmers University of Technology. His research focuses on computational methods to analyze controlled mechanical systems, with applications in wind turbines, heavy vehicle drivelines, and wave propagation in soft biological tissues. Professor Johansson's primary research interests include computational mechanics, wind turbine dynamics, railway system dynamics, biomechanics, condition monitoring systems, optimization methods, and structural dynamics. His work bridges theoretical computational methods with practical engineering applications across multiple domains, particularly in renewable energy systems and transportation infrastructure. Analysis of his publication record reveals a strong focus on computational modeling applied to real-world engineering problems. His recent work demonstrates significant contributions to wind turbine technology, railway infrastructure monitoring, and biomechanical modeling. The publications show a consistent pattern of applying advanced computational techniques to solve complex mechanical system challenges, with increasing emphasis on digital twin technology and model-based condition monitoring systems. Professor Johansson leads or participates in multiple research projects including 'Towards Digital Twins of the Human Body for Personalized Safety' (2025-2026), 'AI-Driven Constrained Optimal Control for Bi-manual Loco-Manipulation' (2024-2029), and 'A Digital Twin for Durability to Accelerate Development and Enable Predictive Maintenance' (2024-2027). His research has received funding from various sources including VINNOVA, Wallenberg AI program, and Swedish Wind Power Technology Center. His research group focuses on computational methods for mechanical systems with applications across multiple domains. The work involves developing advanced computational models, validation through experimental data, and implementation in real-world monitoring and optimization systems. Current efforts emphasize digital twin frameworks and model-based condition monitoring for various engineering systems.
Fredrik Johansson is an Associate Professor in the Department of Data Science and AI at Chalmers University of Technology. His research focuses on developing machine learning methods for healthcare applications, causal inference, and handling imperfect data. He leads multiple funded projects including WASP AI/MLX and research on causal machine learning for healthcare applications. Johansson's core research interests include: Machine learning for clinical decision support and healthcare analytics Causal inference methods for observational data Handling missing values and data quality issues Interpretable and robust ML models Domain adaptation and transfer learning Reinforcement learning for treatment policies His recent publications demonstrate strong focus on clinical ML applications (dermatology, rheumatology, Alzheimer's) and methodological work on causal inference. Frequent themes include handling missing data, model interpretability, and healthcare policy optimization. Collaborative work spans multiple medical domains using registry data, proteomics, and medical imaging. He leads significant research projects including: Kausalitet och sidoinformation för effektiv maskininlärning (VR-funded) Maskininlärning för kausal inferens från observationsdata (Wallenberg) Förutsättningar för inlärning av överförbara koncept (Wallenberg) Fattigdomsfällor i Afrika (Formas-funded)
Professor Javid Taheri is a leading academic at Karlstad University (2019–present), previously serving as Associate Professor (2015–2019) and Senior Lecturer (2015). His research focuses on cloud computing, edge computing, distributed systems, and AI-driven networking. He holds a Ph.D. in Information Technologies from The University of Sydney (2007) and an M.Sc./B.Sc. in Electrical Engineering from Sharif University of Technology (2000/1998). Research interests include cloud-edge continuum systems , resource optimization , 5G/6G networking , and AI for IoT . Notable contributions include frameworks like PerfSim (microservice performance simulation) and MultiScaler (auto-scaling for cloud applications). Publications highlight innovations in edge computing optimization, security for distributed systems, and machine learning for resource management. He has co-authored over 150 papers across top venues like IEEE Transactions and ACM conferences. Academic leadership includes roles as conference chair (IC2E 2023) and editorial work for journals on cloud and edge computing.
James Gross is a Professor at the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm. He leads research in mobile systems and networks, with a focus on 5G/6G, edge computing, and performance evaluation. He is Associate Director of KTH's Digital Futures center and a board member of the Innovative Centre for Embedded Systems. Previously, he directed the ACCESS Linnaeus Centre (2016–2019) and was Assistant Professor at RWTH Aachen University. PhD, TU Berlin (2006) Studies: TU Berlin, UC San Diego His research lies at the intersection of wireless networking, edge computing, and mathematical performance modeling. Key areas include ultra-reliable low-latency communications (URLLC), age-of-information, network calculus, and resource allocation. He applies these to 5G/6G, cyber-physical systems, and industrial IoT. His work combines theoretical modeling with real-world implementation and standardization impact. The recent publications highlight a strong focus on deterministic and reliable communications for future networks. Topics include hierarchical inference at the edge, age-of-information optimization, finite blocklength coding, and integration of TSN with wireless systems. There is a clear trend towards AI/ML for resource management and semantic communications, reflecting the evolution of intelligent edge networks. Best Paper Award, ACM MSWiM 2015 Best Demo Paper Award, IEEE WoWMoM 2015 Best Paper Award, IEEE WoWMoM 2009 Best Paper Award, European Wireless 2009 ITG/KuVS Dissertation Award, 2007 James Gross has supervised PhD students such as Samie Mostafavi and advises numerous master's projects. His research has been funded by national science foundations in Germany and Sweden, the ICT TNG SRA, Linnaeus ACCESS Centre, DFG-funded UMIC Centre, German Ministry of Science, and various industry partners. His work has led to patents and influenced wireless standards. He is involved in initiatives like the TECoSA project on trustworthy edge computing and organizes summer schools on Edge AI and 6G. His lab conducts experimental research on edge computing testbeds (e.g., Ainur, ExPECA) and wireless performance evaluation.
Lina Gyllencreutz is an Associate Professor at Umeå University's Department of Nursing in Örnsköldsvik. Her research focuses on emergency medicine, disaster preparedness, and prehospital care, with particular emphasis on mass casualty incidents, chemical incidents, and tunnel safety protocols. She actively contributes to interdisciplinary emergency training programs and has published extensively on simulation-based learning and first responder decision-making. Research Interests: Dr. Gyllencreutz specializes in Emergency medical response Disaster preparedness Mass casualty incident management Chemical incident protocols Tunnel safety training Simulation-based education Publications Trends (2023-2025): Recent work demonstrates a strong focus on improving first responder capabilities through technology-enhanced training, developing assessment tools for disaster preparedness, and analyzing multi-agency collaboration in complex emergency scenarios. Key themes include tunnel incident decision-making, chemical incident response, and mixed reality training applications. Collaborative Networks: Dr. Gyllencreutz regularly collaborates with Umeå University's Department of Diagnostics and Intervention, Center of Disaster Medicine, and international researchers from institutions like Oslo University and Australian safety organizations.
Anton Cervin is a Senior Lecturer (on Leave of Absence) at the Department of Automatic Control, Lund University. He is affiliated with the LTH Profile Area: AI and Digitalization. His roles include Director of First and Second Cycle Studies, Deputy Head of the Department (2019–2022), and Director of the China Profile at LTH (2008–2012). Research focuses on real-time systems, control over cloud platforms, event-based control, and cyber-physical systems. Key projects include the Swedish Research Council-funded 'Event-Based Control of Stochastic Systems' and WASP-supported 'Event-Based Information Fusion for Self-Adaptive Cloud'. Developed software tools: TrueTime (real-time simulator), JitterTime, Jitterbug, and TinyRealTime. Recognized with multiple Best Paper Awards at ECRTS, RTNS, and RTCSA conferences. Supervised over 5 PhD students in real-time control and embedded systems. Teaching includes advanced courses on automatic control, systems engineering, and real-time systems. His work aligns with UN SDG 9 (Industry, Innovation, and Infrastructure) through contributions to smart infrastructure and cloud-based control systems.
Johan Jansson is an Associate Professor in Scientific Computing at KTH Royal Institute of Technology and BCAM (Basque Center for Applied Mathematics). He leads research in predictive Direct FEM Simulation (DFS) for aerodynamics and multiphase flows, and co-founded Icarus Digital Math as CEO. His work includes the FEniCS open-source finite element software project and MOOC-HPFEM educational initiatives. He holds roles as Director of the Center for Digital Math and collaborates internationally in computational science. Research focuses on high-performance computing (HPC), fluid-structure interaction (FSI), biomedical modeling, and renewable energy systems. Notable contributions include adaptive FEM frameworks for turbulent flow, vocal fold simulations, and wave energy converter modeling. His work bridges academic research with industrial applications, leveraging FEniCS-HPC and Unicorn solvers. Key achievements include election to the IVA Royal Swedish Academy of Sciences 100-list and securing the Severo Ochoa Center of Excellence Award. He has pioneered open-source tools like SimTek and contributed to major projects like the Salter Sink and vocal production modeling. Teaching responsibilities include courses on database technology, computational fluid mechanics, and research methodology. He actively engages in large-scale simulation projects involving marine energy, cardiac ablation protocols, and aerodynamic optimization.
Ali W. Elshaari is an Associate Professor at the Royal Institute of Technology (KTH) in Stockholm, Sweden. He holds a B.S. in Electrical Engineering from the University of Benghazi (2007) and a Ph.D. in photonics from the Rochester Institute of Technology (2011). His postdoctoral research at TU Delft’s Kavli Institute of Nanoscience focused on quantum transport. Currently, he leads the Quantum Nano Photonics Group, pioneering work in topological and quantum integrated photonics to develop high-performance circuits for communication, sensing, and metrology. His research spans hybrid quantum photonics, strain-tunable systems, and superconducting detectors, with applications in quantum communication and quantum materials characterization. Elshaari's research interests include integrating single-photon emitters into CMOS-compatible platforms, exploring quantum phenomena like entanglement and coherence, and developing advanced photonic materials (e.g., hexagonal boron nitride and Cu₂O). He has contributed to on-chip single-photon generation/filtering, strain-tunable photonic circuits, and slow-wave superconducting detectors. His work bridges experimental and theoretical approaches, leveraging imaging techniques and phase retrieval algorithms. Elshaari is an editorial board member for Nature Portfolio - Scientific Reports , Wiley Advanced Quantum Technologies , and EPJ Quantum Technology . He teaches courses in quantum technology, electromagnetism, and optical physics. His funding includes grants from the Wallenberg Foundation, Swedish Research Council, Vinnova, and the European Research Council. His lab actively recruits students for bachelor’s and master’s projects in quantum photonics and nanophotonics.
Martin Servin is an Associate Professor at the Department of Physics, Umeå University, and leads the Digital Physics research group within the UMIT Research Lab. His work focuses on computational modeling and simulation of granular materials, robots, and vehicles, with applications in AI-based control and perception. He holds a doctoral degree from Umeå University (2003) and has pioneered research in real-time physics simulation, particularly in the context of autonomous machinery and off-road robotics. Research Interests : Digital physics, granular materials simulation, autonomous systems, reinforcement learning, and simulation-to-reality transfer. His group develops advanced simulation tools for industries like forestry, mining, and construction. Key Projects : Mistra Digital Forest (2019–2026) AILUR (Digital Twin for AI-controlled Lunar Robotics) XSCAVE (Explainable, Safe Control for Heavy Machinery) Publications emphasize simulation methodologies, AI integration, and real-world validation across robotics, vehicle dynamics, and granular mechanics. Notable contributions include work on wheel loader dynamics, deep reinforcement learning for control systems, and terrain modeling. Awards include the Spin-off award for industry-grade physics in Unreal Engine (2018) , recognizing his role in Algoryx Simulations, a spin-off company commercializing his research. Labs/Teams : UMIT Research Lab, Digital Physics Group, and collaborations with Algoryx Simulations.
Valeria Castellucci is a Senior Lecturer and Associate Professor in the Department of Electrical Engineering at Uppsala University, Sweden, affiliated with the Division of Electricity. She holds the title of Docent in Engineering Science with Specialisation in Science of Electricity, reflecting her advanced academic standing and research contributions. Her research focuses on renewable energy systems, particularly wave energy and the integration of electric vehicles into power grids. Key areas include demand-side flexibility, peak load management, load shifting, and the optimization of wave energy parks. Her work combines theoretical modeling with real-world applications, often based on case studies in Uppsala, such as microgrid operations and EV charging infrastructure in parking garages. The recent publications highlight a strong trend toward smart grid technologies, grid stability, and the role of distributed energy resources in modern power systems. Her research emphasizes practical solutions for integrating variable renewable sources and managing electricity demand efficiently. Docent in Engineering Science with Specialisation in Science of Electricity Valeria Castellucci is actively involved in research collaboration, particularly with colleagues such as Carl Flygare, Alexander Wallberg, and Rafael Waters. Her work has been cited in policy sources and referenced in Wikipedia, indicating broader impact beyond academia. She contributes to both journal publications and conference proceedings, maintaining a high level of scholarly output in energy and electrical engineering. She is based at Ångströmlaboratoriet in Uppsala and is a key contributor to Uppsala University's wave energy research, including work at the Lysekil Research Site. Her doctoral thesis, Sea Level Compensation System for Wave Energy Converters (2016), laid the foundation for much of her ongoing research in marine renewable energy systems.
Marko Laaksonen is a Professor at the Department of Health Sciences (HOV) at Mid Sweden University, specializing in winter sports biomechanics and performance analysis. He is affiliated with the Swedish Winter Sports Research Centre, focusing on biathlon and cross-country skiing. His research examines physiological responses to training, rifle carriage effects on skiing mechanics, and performance indicators in biathlon. Key areas include exercise intensity distribution, shooting precision, and muscle metabolism during endurance activities. Recent publications analyze biathlon shooting performance under varying conditions, training load measurement, and equipment impacts on athlete efficiency. Over 15 articles demonstrate expertise in winter sports analytics and physiological monitoring.
Anders Forslund is a researcher at Chalmers University of Technology, specializing in Product Development with a focus on aerospace and mechanical engineering. His work bridges theoretical research and practical application in multidisciplinary design. Department: Product Development Key Collaborations: VINNOVA, EU Horizon 2020, AIAA, ASME His research interests revolve around robust design and uncertainty modeling for aerospace structures. He develops simulation platforms to minimize geometric variation in welded components and optimize turbine lifecycle robustness. His work integrates genetic algorithms , 3D scanning , and PLM systems for multidisciplinary convergence. The 15 most recent publications span 2011–2018, covering welding optimization , geometric robustness , simulation frameworks , and sustainable aerospace design . Key trends include bridging CAD/point cloud gaps , virtual trimming , and set-based design in collaborative platforms. Anders participates in grants and projects such as: TOICA (2013–2016): EU-funded thermal-driven aircraft design. ELISE (2018–2018): Vinnova-funded electric aviation. Design av de aerodynamiska egenskaperna för ett elektriskt flygplan (2021–2022): Chalmers-led aerodynamic R&D. He has contributed to research teams in propulsion, thermal sciences, and acoustic engineering, collaborating with experts like Rikard Söderberg and Lars Davidson.
Jiayao Lei is an Assistant Professor at Karolinska Institutet and a Visiting Senior Lecturer at Queen Mary University of London. Her work focuses on cancer epidemiology, particularly cervical cancer prevention through HPV vaccination and screening optimization. She is affiliated with the Department of Medical Epidemiology and Biostatistics, Department of Clinical Science, Intervention and Technology, and the Center for Cervical Cancer Elimination Modelling and simulation research group at KI. PhD in Medical Epidemiology and Biostatistics, Karolinska Institutet (2020) Master of Medical Science, Karolinska Institutet (2015) Her research spans cancer epidemiology, vaccine effectiveness, risk prediction modeling, and health economics. She leverages Swedish national registers and biobank data to evaluate HPV vaccination programs and cervical screening performance, contributing to WHO's cervical cancer elimination strategy. Her recent publications demonstrate a focus on HPV epidemiology, cervical cancer prevention, and infectious disease modeling. Key trends include population-based cohort studies, self-sampling methods, and cross-country SARS-CoV-2 transmission analyses. Scientific awards include the Dimitris N. Chorafas Prize 2020 for her thesis on cervical cancer prevention. Her work is funded by the Swedish Research Council, Forte, Swedish Cancer Society, and KI Strategic Research Area grants. As an educator, she teaches Clinical Cancer Epidemiology (KCL & KI) and Introduction to Epidemiology (Scandinavian Kiropractorhöskolan). Current team members include PhD student Eva Meglic, postdoc Yunyang Deng, and research assistants, with former advisees like Ana Martina Astorga Alsina.
