Mats Danielsson is a Professor at KTH Royal Institute of Technology, leading the Medical Imaging research group within the Department of Particle Astrophysics and Medical Imaging. He has coordinated major projects like the ERC Advanced Grant for the Si3 project (starting 2024) and the EIC Pathfinder's 1MICRON project (starting 2025). His work focuses on advancing photon-counting detectors, X-ray technologies, and medical imaging systems. Notable recognitions include the 2024 KTH Innovation Award and the 2022 Hans Wigzell Science Prize. Danielsson has co-founded companies such as Sectra Mamea AB and C-RAD AB, and holds 135 patents with over 150 scientific publications. Education: MSc (1990) and PhD (1996) from KTH, followed by postdoctoral research at Lawrence Berkeley National Lab (1996–1998). He joined KTH in 1999, where he has held his current professorship since then. His research spans medical imaging, detector innovation, and radiation physics applications in healthcare. Research Interests: Development of high-resolution CT detectors, photon-counting technologies, compact X-ray sources, and AI-driven image processing. His recent work emphasizes minimizing radiation exposure while enhancing diagnostic precision through novel detector designs and machine learning algorithms. Key Projects: ERC Si3 project (3D detector for nuclear medicine), EIC 1MICRON (micrometer-scale imaging), and MedTechLabs collaboration with Karolinska Institutet. He has pioneered innovations such as MicroDose mammography and advanced photon-counting spectral CT systems. Awards: KTH Innovation Award (2024), Hans Wigzell Prize (2022), IVA membership (2017), Polhem finalist (2014), and INGVAR Award (2004). Advising & Grants: Over 150 scientific publications, 135 patents, and leadership in multi-institutional projects. Teaches courses on medical imaging and modern physics at KTH. Labs/Teams: Director of the Medical Imaging Group at KTH, co-founder of MedTechLabs, and collaborator across academia and industry in medical imaging innovation.
Lars Engstrand is a Professor in infection control at Karolinska Institutet, heading the Translational Microbiome Research and Pandemic Preparedness group within the Department of Microbiology, Tumor and Cell Biology. His research spans multiple disciplines with a focus on translational microbiome research and pandemic preparedness. Engstrand's research interests center on understanding the human microbiome's role in health and disease, particularly in women's reproductive health and gastroenterology. His group has established multiple large-scale clinical studies including SweMaMi (Swedish Maternal Microbiome project), BASIC (associations between microbiota and preterm birth), VaMiGyn (Vaginal Microbiota in Gynaecological health), and several others investigating the vaginal microbiome's relationship to pregnancy outcomes, HPV infection, and cervical cancer. His team also conducts significant research on gut microbiome in inflammatory bowel disease and colorectal conditions through projects like PopCol and KOLBIBAKT. Analysis of Engstrand's most recent publications reveals a strong focus on the relationship between microbiome composition and women's health outcomes. His research consistently examines how vaginal, gut, and oral microbiomes influence pregnancy complications, preterm birth, HPV infection, and mental health during pregnancy. The work often employs large cohort studies with comprehensive sampling strategies across multiple body sites and time points, providing robust data for understanding microbiome dynamics in health and disease. Engstrand leads the Microbiome Exploration and Development for Intervention (MEDI) initiative and the National Pandemic Center (NPC) at Karolinska Institutet. The NPC conducted large-scale sequencing during the COVID-19 pandemic and has amassed over 1.5 million samples. His research group includes multiple specialized teams focusing on culturomics, bioinformatics, labcore operations, women's health research, and pandemic preparedness.
Jennifer K. Ryan is a Professor and Division Head for Numerical Analysis, Optimization & Systems Theory at the Department of Mathematics, KTH Royal Institute of Technology, Stockholm. She is affiliated with the Digital Futures Faculty, a cross-disciplinary research center jointly established by KTH, Stockholm University, and RISE Research Institutes of Sweden. Her research focuses on developing numerical schemes for extracting enhanced accuracy from simulations, with applications in imaging, data analysis, and fluid dynamics. Ryan’s work emphasizes improving computational efficiency through theoretical insights and practical algorithms. Her academic roles include teaching courses like Numerical Methods for Differential Equations II and supervising student projects in numerical analysis. She has contributed to the SIAC MAGIC toolbox, a software package for accuracy-enhancing filtering techniques. Ryan’s research group actively explores discontinuous Galerkin methods, SIAC filtering, and multi-resolution analysis, addressing challenges in computational physics and engineering. Her publications span high-order numerical methods, mesh adaptivity, and applications in plasma physics and wave equations. Projects include error estimation for boundary integral methods and developing filters for noisy data. Ryan collaborates internationally, contributing to both theoretical advancements and practical implementations in computational science.
Saurabh Amin is a Professor in the Department of Civil and Environmental Engineering at the Massachusetts Institute of Technology (MIT), where he also serves as the Edmund K. Turner Professor and Undergraduate Officer. He is a Principal Investigator at the Laboratory of Information and Decision Systems and holds affiliations with the Operations Research Center and the Center for Computational Science and Engineering. His educational background includes: B.Tech. 2002, Indian Institute of Technology (IIT) Roorkee M.S. 2004, University of Texas (UT) Austin Ph.D. 2011, University of California (UC) Berkeley Saurabh Amin's research focuses on the design and control of infrastructure systems using game theory and optimization in networks. His work spans three main areas: resilient network control, information systems and incentive design, and optimal resource allocation in large-scale infrastructure systems. By concentrating on critical infrastructure domains including highway transportation, electric power distribution, and urban water networks, his research develops innovative theory and tools to enhance system performance against both stochastic and adversarial disruptions. His approach involves modeling cyber-physical interactions in infrastructures to assess vulnerabilities, developing detection and response tools for failures at various scales, and designing economic incentive schemes that improve aggregate public good while accounting for dependencies and private information among strategic entities. Amin's work bridges mathematical systems theory with practical civil engineering applications, creating a rigorous theoretical foundation for infrastructure resilience that addresses diverse failure mechanisms from natural disasters to deliberate malicious actions. His recent publications demonstrate a strong focus on decarbonization of energy systems, resilient infrastructure planning under climate uncertainty, optimization methods for complex networked systems, and game-theoretic approaches to sustainable infrastructure management. His work increasingly integrates artificial intelligence and machine learning techniques with traditional control theory to address contemporary challenges in infrastructure resilience and sustainability. The research shows a clear trajectory toward addressing climate change impacts on infrastructure systems while maintaining economic efficiency and operational reliability. Professor Amin has received numerous prestigious awards and honors: Common Ground Excellence in Teaching Award, 2025 HSCC Test-of-Time Award, 2024 MIT CEE, Distinguished Service and Leadership Award, 2023 Samuel M. Seegal Prize (SoE) – inspiring students in pursuing and achieving excellence, 2022 Earll M. Murman for Excellence in Undergraduate Advising, 2022 C3.ai Digital Transformation Institute Research Award, 2020 MIT, Ole Madsen Mentoring Award, 2020 MIT, Energy Initiative Research Award, 2020 National Academy of Engineering, China-America Frontiers of Engineering Symposium speaker, 2019 MIT, Robert N. Noyce Career Development Professor, 2015-2018 Google Faculty Research Award, 2015 National Science Foundation CAREER Award, 2015 Siebel Energy Institute Research Award, 2015 MIT, Solomon Buchsbaum AT&T Research Fund Award, 2012 Professor Amin has been actively involved in significant research projects including the C3.ai DTI project on Causal Reasoning for Real-Time Attack Identification in Cyber-Physical Systems and another on Learning in Routing Games for Sustainable Electromobility. He serves as the chief scientist on multi-institutional NSF grants, including the $9 million Foundations of Resilient Cyber-Physical Systems (CPS) project. His teaching portfolio includes courses such as 1.008 Engineering for a Sustainable World, 1.104 Sensing and Intelligent Systems, 1.020 Engineering Sustainability: Analysis and Design, and 1.208 Resilient Networks. As Undergraduate Officer, he plays a key role in shaping the educational experience for civil and environmental engineering students at MIT. Professor Amin leads the Resilient Infrastructure Networks Lab at MIT, where his team develops theoretical foundations and practical tools for infrastructure resilience. The lab focuses on the intersection of control theory, game theory, and optimization applied to cyber-physical infrastructure systems. Current research directions include pandemic-resilient urban mobility and hurricane-resilient smart grid operations, reflecting the lab's commitment to addressing pressing societal challenges through rigorous systems engineering approaches.
Giuliano Di Baldassarre is a Professor of Hydrology and Environmental Analysis at the Department of Earth Sciences, Uppsala University , Sweden. He serves as Head of Division for LUVAL (Air, Water and Landscape Sciences) and directs the Centre of Natural Hazards and Disaster Science (CNDS) (2016–2025). His work bridges water, environment, and society through interdisciplinary methods , focusing on disaster risk reduction, climate adaptation, and sustainable development. Education : Details not explicitly provided in the text. His research examines feedbacks between human activities and hydrological processes , including floods, droughts, and reservoir management . Key themes include social-ecological systems , inequalities in water crises , and policy implications of hydrological extremes . He has pioneered sociohydrology and human-water system modeling . Recent articles highlight global drought-flood interactions , urban water inequality , climate service maladaptation , and sociohydrological modeling . His work spans Nature Sustainability , Science Advances , and Hydrological Sciences Journal . Scientific Awards : International Hydrology Prize (Volker Medal) Plinius Medal (EGU) Witherspoon Lecture Award (AGU) European Research Council Consolidator Grant He led Panta Rhei - Everything Flows (2013–2022), IAHS’s global initiative on water-society interactions. Current efforts include transdisciplinary praxis and climate risk reduction frameworks .
Jonas Bylander is a Professor at Chalmers University of Technology in the Department of Microtechnology and Nanoscience, specifically within the Quantum Technology division. He leads a research group focused on developing quantum computers using superconducting circuits.
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.
Harald Rohracher is a Professor at the Department of Theme (TEMA) , Linköping University , affiliated with the Theme Technology and Social Change (THEME) . His research focuses on sociotechnical transitions for climate-neutral cities , examining energy systems, digitalization, and governance strategies. Grants: Formas, Horizon Europe, Vinnova Labs: STRIPE (Sociotechnical Research on Infrastructures, Politics, and Environment), Biogas Solutions Research Center Students: Adam Svensson, Stella Huang, Gavin Nilsson Lewis, Giorgi Kankia Rohracher investigates how households , social movements , and policy frameworks interact in transformative processes. His recent work explores smart grid politics , decentralized energy systems , and urban food digitalization , emphasizing power dynamics and governance experiments. He leads projects on transdisciplinary education for climate governance, positive energy districts , and collective experimentation across Sweden and Spain. His scientific grants highlight institutional support for sustainability research, while his research teams bridge academic, governmental, and civil society actors.
Jonas Faleskog is a Professor in the Department of Materials and Structural Mechanics at KTH Royal Institute of Technology. His research focuses on mathematical modeling of material deformation and failure mechanisms, particularly in metallic and polymeric materials. Key areas include ductile and brittle fracture analysis, fracture mechanics, and computational modeling of material behavior under various stress conditions. He leads a research group collaborating internationally to develop models describing material failure at microscopic scales. Faleskog teaches courses such as Fracture Mechanics (SE2139) and Modeling in FEM (SE2860), emphasizing practical applications of theoretical models. His work spans experimental and numerical methods, addressing challenges in material heterogeneity, porosity effects, and environmental degradation. Notable contributions include advancements in weakest-link modeling for brittle failure, probabilistic fracture models, and strain gradient plasticity analysis. His research bridges material science, applied mechanics, and numerical methods to optimize material utilization in engineering systems like reactor tanks, aircraft, and vehicles. Key collaborations involve international teams exploring microstructural influences on fracture behavior. While no specific awards are listed, his extensive publication record reflects sustained contributions to mechanical and materials engineering.
Jessica Jewell is a Professor in Technology and Society at Chalmers University's Department of Space, Earth and Environment. She holds additional roles including Professor at the Centre for Climate and Energy Transformation (University of Bergen), Guest Research Scholar at IIASA, and Senior Fellow at the Breakthrough Institute. Her research focuses on climate action feasibility, energy transitions, and the political economy of decarbonization. She leads projects funded by the European Research Council (ERC), Norwegian Research Council, and EU initiatives like CINTRAN. Key achievements include an ERC Starting Grant and membership in the Swedish Young Academy. Her work spans interdisciplinary approaches to quantify energy transition dynamics, assess coal phase-out strategies, and analyze carbon capture deployment. She serves on editorial boards for journals like Energy Research and Social Science and Oxford Open Energy . Jewell’s recent articles highlight themes like climate justice in energy transitions, feasibility of rapid decarbonization, and global coal reduction pathways. Her research bridges technical, socio-economic, and political dimensions to inform actionable climate policies.
Stefano Markidis is a Professor of Computer Science at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Digital Futures Faculty. He holds a Ph.D. from the University of Illinois at Urbana-Champaign and an MS from Politecnico di Torino. His research focuses on high-performance computing systems, including supercomputers and quantum computers, with expertise in plasma simulations, quantum algorithms, and scalable computational frameworks. Markidis leads the development of the Neko framework for high-fidelity computational fluid dynamics and the iPIC3D particle-in-cell code for plasma physics. He teaches courses such as Quantum Computing for Computer Scientists, High-Performance Computing, and Applied GPU Programming. His work addresses exascale computing challenges, including optimizing algorithms for GPUs, quantum systems, and distributed architectures. Key research interests include: Parallel Programming Models and HPC Frameworks Quantum Computing Applications in Scientific Simulations Physics-Informed Machine Learning Exascale System Optimization Turbulence Modeling and Plasma Dynamics His publications span over 100 articles in journals like Journal of Computational Physics and Scientific Reports , focusing on topics such as scalable CFD, quantum neural networks, and plasma simulation techniques. He has advised numerous students in these areas. Markidis collaborates with institutions like Los Alamos National Laboratory and RISE Research Institutes of Sweden through the Digital Futures initiative, aiming to solve societal challenges via digital technologies.
Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.
Maricela De la Torre Castro is a Professor of Natural Resource Management at Stockholm University , affiliated with the Department of Physical Geography . Her research focuses on coastal and ocean governance through a social-ecological systems lens, emphasizing gender dynamics , seagrass conservation , and climate change adaptation in tropical coastal communities. BSc in Oceanology (Universidad Autonoma de Baja California) MSc, PhD, and Docent in Natural Resource Management (Stockholm University) Her work examines seagrass ecosystem services , small-scale fisheries governance , and gendered impacts of marine protected areas . Recent studies analyze: 2025: Habitat loss risks from seaweed cultivation 2024: Gender-poverty dynamics in Zanzibar MPAs 2022: Adaptive capacity differences between genders 2021: Blue Justice frameworks for fisheries governance Active projects include SEAgender (Swedish Research Council) analyzing gendered effects of MPAs . She supervises PhD candidates in tropical marine systems and has extensive experience with EU Erasmus programs and UNDP collaborations . Research emphasizes hybrid methods , cultural value mapping , and interdisciplinary monitoring of coastal initiatives.
Roland Larsson is a Professor and Head of Subject in Machine Elements at Luleå University of Technology, Sweden. His research focuses on Tribology, particularly lubrication regimes (boundary to elastohydrodynamic), contact mechanics, surface roughness effects, and applications in rolling element bearings, clutches, hydraulic systems, tires, and sports equipment. He has supervised over 20 doctoral and licentiate students, contributed to advanced courses, and developed teaching methods like Flipped Classroom and Constructive Alignment . Education: Ph.D. (1996, Luleå University of Technology), Docent (2001), M.Sc. in Mechanical Engineering (1988). Research: Central themes include elastohydrodynamic lubrication, surface roughness in contact interfaces, and sustainable lubricants. His work explores water-based lubricants, ionic liquids, and glycerol mixtures. Publications: Recent articles (2025) investigate water-based lubricants' film formation, ski-snow friction dynamics, and tribochemical properties of green lubricants. Earlier works (2024-2023) cover micropitting, wear models, and multi-scale contact analysis. Awards: Recipient of multiple tribology awards including ASME Best Paper, Nordea's Vetenskapliga Pris, and Venture Cup North. He has held leadership roles at Luleå University, including Dean and Vice-Dean of the Faculty of Engineering Board. Collaboration: Active in international research networks as peer-reviewer, faculty opponent, and external examiner. His post-doctoral work includes affiliations with Leeds University and SKF Engineering Research Centre.
Malin Göteman is an Associate Professor at the Department of Electrical Engineering, Uppsala University. Her research focuses on offshore renewable energy systems, particularly modeling and optimizing large-scale wave power farms and analyzing their resilience to extreme weather conditions. Deputy Director, Center for Natural Disaster Studies (CNDS), Sweden Specialized in wave energy converter dynamics and hybrid offshore energy systems Collaborates on SPH-based numerical wave-current tanks and CFD validation Research Interests: She investigates wave energy farm interactions, hydrodynamic performance of floating platforms, extreme wave load modeling, and survivability strategies using machine learning. Her work spans renewable energy integration, coastal protection, and power system stability under extreme conditions. Recent Publications: Her 2025 articles address resilience of offshore energy systems to metocean extremes and reduced-order modeling via Bayesian design. Earlier works (2023-2024) cover SPH validations for floating wind-wave systems, neural network survivability approaches, and hybrid energy-water supply solutions. Collaborations: She works with international teams on projects like Lysekil wave energy test sites and DeepCwind floating platforms. Key areas include grid-connected wave parks, multi-fidelity surrogate modeling, and comparative studies on offshore wind dependencies.
