Lars Nordström is a Professor at the Division of Electric Power and Energy Systems within KTH Royal Institute of Technology, Stockholm, Sweden. His work bridges control systems , communication networks , and power systems , with a focus on future architectures, functionality, and quality aspects of ICT for power grid operations. He has led initiatives such as the Swedish Centre of Electric Power Engineering and served as Thematic Leader for Smartgrids in KIC InnoEnergy. In 2014, he was a Visiting Professor at Washington State University. Education : Ph.D., MSc.EE Nordström's research explores the intersection of smart grids , machine learning , and cybersecurity for power systems. Key areas include: Wide-Area Monitoring and Control (WAMC) systems Decentralized control strategies for DC microgrids Impedance modeling using neural networks Data-driven methods for islanding detection ICT reliability and protocol design for grid operations His recent publications emphasize machine learning applications in power systems, including LSTM networks for EV charging management, graph attention networks for stability monitoring, and digital twin approaches for cyber-attack mitigation. These works span disciplines such as Smart Grids, Power Electronics, and Data Science. Scientific Recognitions : Senior Member, IEEE Senior Member, CIRED Senior Member, Cigre Past Chairman, Swedish IEC TC57 Mirror Committee Nordström actively teaches and examines graduate courses like Communication and Control in Electric Power Systems and Computer Applications and Machine Learning in Electric Power Systems . His work influences industry practices through collaborations on digital substations, energy market analysis, and resilience strategies.
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.
Robert Östling is a Professor of Economics at the Stockholm School of Economics (SSE), affiliated with the Department of Economics and the Karl-Adam Bonnier Center for Governance within the House of Governance and Public Policy. He holds a PhD from SSE (2008) and previously worked at Stockholm University's Institute for International Economic Studies until 2018. His research focuses on applied microeconomics and behavioral economics, particularly examining how wealth impacts attitudes, behavior, and life outcomes using Swedish lottery data. He teaches econometrics, behavioral economics, and economics for MBA students, and serves as program director for SSE's MSc in Economics. Key roles include board membership of the Swedish Economics Association and the Expert Group on Public Economics (ESO), and membership in the scientific advisory board of the Swedish Consumer Protection Agency. He co-founded the popular economics blog Ekonomistas , recognized as 'Swede of the Year' in 2017. Awards include the Assar Lindbeck Medal (2021) and the Arnberg Prize (2009). His research spans wealth effects on labor supply, health, child development, and political behavior. Notable projects include studying lottery winners' long-term well-being and portfolio decisions. Teaching innovations include using animated GIFs for econometrics instruction. He has contributed to policy debates on economic reforms, consumer protection, and pandemic responses. Outreach activities include public writing and policy advisory roles. His research has been featured in outlets like the New York Times and Swedish media. He remains active in academic networks, including the Network for Evidence-Based Policy.
Olle Eriksson is a Professor in the Department of Physics and Astronomy at Uppsala University, specifically affiliated with the Materials Theory division. His research focuses on theoretical and computational approaches to understanding magnetic materials and their properties. His primary research interests include first principles calculations of bulk materials and surfaces, with particular emphasis on magnetism and chemical bonding. His methodological expertise spans full-potential implementations of density functional theory, dynamical mean-field theory, and self-interaction correction. He also conducts calculations of finite temperature magnetism using Monte Carlo simulations and atomistic spin-dynamics simulations, as well as investigations into lattice dynamics and finite temperature effects on phase stability. Professor Eriksson's recent work demonstrates a strong focus on magnetocaloric materials for magnetic refrigeration applications, two-dimensional magnetic materials including van der Waals magnets, topological magnetic textures such as skyrmions, and computational methods for improving density functional theory. His research has significant implications for energy-efficient cooling technologies, next-generation spintronic devices, and fundamental understanding of quantum magnetic phenomena. Materials Science : Magnetocaloric materials, battery materials, 2D materials Computational Physics : Density functional theory, Monte Carlo simulations, spin dynamics Magnetism : Topological textures, chiral magnets, ultrafast dynamics His extensive publication record shows consistent contributions to high-impact journals across physics and materials science, with a notable increase in interdisciplinary work connecting computational physics with materials design for energy applications.
Cheuk Wai Tai is a Senior Staff Researcher at Stockholm University's Department of Environmental and Materials Chemistry since 2009. He manages the transmission electron microscopes and sample preparation equipment at the Electron Microscopy Center and serves as Section Editor for the Journal of Electronic Materials. His work focuses on quantitative structure characterization in functional materials research, particularly within nanoscience and nanotechnology contexts. Education: Ph.D. in Applied Physics, The Hong Kong Polytechnic University, 2004 M.Phil. in Applied Physics, The Hong Kong Polytechnic University, 2001 M.Sc. in Physics, The Chinese University of Hong Kong, 1998 B.Sc. (Hons) in Engineering Physics, The Hong Kong Polytechnic University, 1997 Dip. in Mechanical Engineering (Computer Aided Engineering), Institute of Vocational Education (formerly Haking Wong Technical Institute), Hong Kong, 1992 His research centers on structure-property relationships in functional materials through advanced electron microscopy techniques. Current specializations include Pair Distribution Function (ePDF) & Diffuse Scattering, Energy Materials characterization, and EM sample preparation methodology development. The group maintains strong focus on translating structural data into functional performance metrics for nanomaterials. Recent publications (2013-2019) demonstrate consistent emphasis on electron microscopy applications for energy storage materials (batteries, photocatalysts) and functional ceramics. Key trends include structural disorder analysis in piezoelectrics, development of quantitative TEM methods like SUePDF, and nanoscale characterization of electrocatalyst surface phases. His work bridges materials chemistry with advanced imaging techniques. Scientific recognition includes: Fellow of The Royal Microscopical Society (U.K.) Senior Member of IEEE Marie Curie Fellowship (2007-2009) from European Commission Sir Edward Youde Memorial Fellowship (2003/2004) from Hong Kong S.A.R. Government He teaches Solid State Chemistry (KZ7003) and leads Introduction to Analytical Electron Microscopy (KZ8009), having previously taught Advanced Transmission Electron Microscopy (KZ8010) before 2011. Major grants supporting his work include: "Quantitative structural characterisation using 3D electron-based pair distribution function" (Swedish Research Council) "A Multidimensional Toolkit for Modern Electron Microscopy" (Swedish Foundation for Strategic Research) "Mitigating Ni-rich Li-ion cathode side-reactions" (Swedish Energy Agency, Co-applicant) He leads the Cheuk-Wai Tai group within Stockholm University's chemistry department and oversees operations at the Electron Microscopy Center, where his team develops and applies advanced characterization techniques for functional materials research.
Matteo Magnani is a Professor in the Division of Computing Science at the Department of Information Technology, Uppsala University. He leads the Uppsala University Information Laboratory and is a founding member of the Uppsala University Computational Social Science Lab. His research spans network science, artificial intelligence, data science, and computational social science, with a focus on social data mining and multilayer networks. PhD in Computer Science, University of Bologna, 2006 Graduated with honours in Information Sciences, University of Bologna, 2002 Studies in Computer Science at University of Marne la Vallée and Imperial College London Matteo Magnani's research interests include social network analysis, multilayer and probabilistic networks, community detection, visual analytics, and the application of AI to digital media and climate communication. His work bridges computer science and social sciences, particularly in analyzing online discourse and digital intermediaries. He has contributed significantly to the understanding of network structures, uncertainty in networks, and the ethical dimensions of algorithmic analysis. His recent publications highlight trends in fairness in community detection, visual saliency in network layouts, emotional reactions to climate visuals online, and deep learning applications in social media. Topics frequently involve YouTube, Twitter, and online public debates, using advanced network and machine learning methods. Rotary Prize for best student of the Science Faculty Best Paper Award Funniest Presentation Award Best Poster Award Pedagogical Prize from UTN Distinguished University Teacher (Sweden) Docent title (Sweden) Magnani has supervised numerous students and collaborated widely, particularly with Luca Rossi, Alexandra Segerberg, and Davide Vega. He has secured funding from major sources including VR, H2020, STINT, and MIUR. He leads active research labs focused on information systems and computational social science, fostering interdisciplinary collaboration and innovation in network-based research.
Professor Ingrid Undeland leads the Marine research group at the Division of Food and Nutrition Science, Department of Life Sciences at Chalmers University of Technology. She is a distinguished researcher with expertise spanning marine food science, lipid chemistry, and blue biorefining, having established herself as a leading figure in sustainable seafood research and marine biotechnology. Her educational background includes food science studies from Linnaeus University and a PhD in bioscience from Chalmers University of Technology and SIK (now RISE). Between 1999-2002, she was a post-doctoral fellow at University of Massachusetts Marine Station, which significantly shaped her research trajectory in marine food science. Professor Undeland's research focuses on pioneering next-generation seafood through innovative value chains from seaweed, small pelagic fish, fish side streams, mussels, and microalgae. Her specialized expertise lies in marine lipids and proteins, particularly their stabilization, isolation from complex sources, and nutritional properties including digestibility. She has extensive experience with antioxidant strategies using plant-derived side streams or extracts and fundamental studies of fish hemoglobins as pro-oxidants. Her work also encompasses innovative technologies for biomass fractionation and nutrient recycling to build blue biorefineries, along with in vitro digestion models and general seafood analytics. Beyond marine research, she explores filamentous fungi as sustainable alternative food protein sources. The trends in her recent publications reveal a strong emphasis on valorizing marine resources through advanced processing techniques. Her work increasingly focuses on sustainable extraction methods for seaweed proteins, particularly Ulva fenestrata, and developing antioxidant strategies using berry side streams to stabilize fish proteins. There's a growing interest in understanding the nutritional properties and digestibility of alternative marine proteins, along with environmental assessments of processing technologies. Her research consistently bridges fundamental science with practical applications for creating sustainable seafood value chains. Swedish representative in Nordic Lipidforum, WEFTA, and EuCheMS Editorial board member of Journal of the Aquatic Food Product Technology Member of the National Committee for Nutrition and Food Science at the Royal Swedish Academy of Sciences Co-founder of the startup company AquaFood H-index of 47 according to Google Scholar Professor Undeland has an extensive record of academic mentorship, having supervised or currently supervising 23 PhD students, 14 postdoctoral researchers, and examining over 25 MSc students. Her research is supported by numerous grants, including the WaSeaBi Project which focuses on valorizing seafood side-streams through holistic value chain design. She collaborates with various industry partners and academic institutions across Europe. Her laboratory includes technicians Dr. Karin Larsson and Dr. Rikard Fristedt, and she leads a dynamic research team working on multiple projects related to marine biorefining and sustainable seafood development. Her research group operates within well-equipped facilities at Chalmers University, with specialized laboratories for marine food analysis, protein extraction, lipid oxidation studies, and in vitro digestion modeling. The team also maintains cultivation systems for seaweed and filamentous fungi, enabling integrated research from raw material production to final product development.
Gustav Amberg is a Professor at KTH Royal Institute of Technology, affiliated with the Flow Mechanics research group within the School of Engineering Sciences. His primary appointment is in the Department of Mechanics, where he focuses on fluid dynamics, multiphase flow, and interfacial phenomena. He holds a permanent full professorship with no indication of兼职 roles. Research interests center on dynamic wetting mechanisms, phase-field modeling, and computational fluid dynamics applied to complex fluid systems. His work explores contact line behavior, microstructured surface interactions, and material phase transformations. Notable areas include rapid droplet spreading, viscoelastic fluid dynamics, and boiling heat transfer on engineered surfaces. Recent studies investigate the interplay between surface topography and wetting dynamics, oscillatory contact line phenomena, and numerical benchmarking across molecular and continuum models. He has pioneered methods for simulating surfactant effects in multiphase flows and developed novel approaches for analyzing weld pool behavior during sintering processes. No academic awards or grants are explicitly listed in the provided materials. His advising record remains undisclosed, though his prolific publication history suggests active research supervision. Laboratory affiliations are not detailed, but his work aligns with KTH's broader initiatives in computational mechanics and materials science.
Aji Mathew is a Professor at the Department of Materials and Environmental Chemistry, Stockholm University. He holds a PhD in polymer chemistry from Mahatma Gandhi University (2001) and conducted postdoctoral research at CERMAV (Grenoble, France) and NTNU (Trondheim, Norway). His academic career includes roles as an assistant professor (2007–2011) and associate professor (2011–2015) at Luleå University of Technology before becoming an associate professor (2015) and subsequently a professor (2017) at Stockholm University. His research focuses on bio-based nanocomposites and sustainable materials, particularly nanocellulose and its applications in environmental remediation, advanced materials, and circular economy solutions. His group, the Aji Mathew Group , specializes in designing bio-based materials for diverse applications, including water treatment, 3D printing, and biomedical uses. Key projects involve upcycling textile waste, developing eco-friendly composites, and creating functional hydrogels. His work bridges fundamental polymer chemistry with practical sustainability challenges. Publications highlight innovations like nanocellulose-based foams, zeolitic frameworks for water purification, and bio-based coatings. While no awards are explicitly mentioned, his extensive peer-reviewed contributions reflect significant scholarly impact. His research emphasizes scalability and real-world applicability, addressing global environmental and material science challenges.
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.
Mischa Billing is a Senior Lecturer at Örebro University specializing in Culinary Arts and Meal Science. She is actively involved in research on sensory experiences, wine studies, and food pairing. Her work spans across multiple disciplines including haptics, olfaction, and culinary traditions. Her research interests focus on the intersection of sensory perception and culinary practices. Billing explores how sound affects taste perception, develops haptic attribute models for food design, and investigates improved sensory experiences for the elderly. Her work in sommelier training and critical attribute techniques bridges traditional culinary knowledge with scientific approaches to sensory evaluation. Analysis of her publications reveals a strong focus on practical applications of sensory science in culinary contexts. Her work spans from theoretical explorations of wine tasting as embodied knowledge to practical guides for food and beverage pairing. The recurring themes include sensory integration, cultural contexts of food consumption, and innovative methods for enhancing meal experiences. Gastronomic Academy's Silver Medal Wine Profile of the Year Nose of the Year Honorary Truffle of the Year Billing has served as general secretary of the International Sommelier Association (ASI) and is a member of the Wine Academy in Sweden. She has extensive experience in evaluating diverse products including Swedish tap water and apple juice. Her media presence includes serving as a jury member on TV4's Sweden's Master Chef and delivering radio talks for Sveriges Radio. She leads several research initiatives including the Sense Lab, which focuses on future sensory experiences, and participates in research groups examining meals from social and cultural perspectives. Her projects like 'Rewine The World' demonstrate interdisciplinary approaches to reducing food waste through innovative culinary methods.
Paul Erhart is a Professor in Condensed Matter and Materials Theory at the Department of Physics, Chalmers University. He received his PhD from Technische Universität Darmstadt in 2006, followed by postdoctoral and staff positions at Lawrence Livermore National Laboratory from 2007, before joining Chalmers in 2011. His research bridges computational physics, materials science, and machine learning to tackle fundamental problems in materials design and characterization. Dr. Erhart's research focuses on computational materials science with particular emphasis on condensed matter physics, nanomaterials, and quantum materials. His work spans from developing computational methods like machine-learned potentials (GPUMD, neuroevolution potentials) to studying fundamental phenomena in perovskites, 2D materials, thermal transport, and plasmonics. He has pioneered approaches connecting simulation with experimental techniques through correlation functions and has made significant contributions to understanding phase transitions, defect physics, and electronic structure in complex materials systems. Analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional computational physics methods. His work increasingly focuses on developing and applying neuroevolution potentials to study thermal properties, phase transitions, and optical phenomena in materials. There's also a clear emphasis on connecting computational results with experimental observations, particularly in neutron scattering, Raman spectroscopy, and plasmonic sensing applications. His research spans fundamental materials physics to applied areas like hydrogen sensing and sustainable materials development. Dr. Erhart has contributed to numerous software packages essential to the computational materials science community, including WulffPack for Wulff constructions, Dynasor for extracting dynamical structure factors, calorine for neuroevolution potential models, and ICET for alloy cluster expansions. His collaborative work spans multiple institutions and disciplines, reflecting the interdisciplinary nature of modern materials research. His contributions to understanding perovskite materials, thermal transport phenomena, and plasmonic systems have established him as a leading researcher in computational materials science.
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.
Xiongfei Wang is a Visiting Professor at KTH Royal Institute of Technology in Stockholm, Sweden, and a Digital Futures Fellow. He holds academic leadership roles, including Editor-in-Chief of IEEE Transactions on Power Electronics and chairs in IEEE committees. His research focuses on power electronics systems, stability analysis, and data-driven approaches for energy systems. Previously, he served as a Professor at Aalborg University (2009–2022). His work addresses challenges in power system stability, converter dynamics, and renewable integration. He leads projects like 'Machine Learning for Dynamics Analysis of Power Electronic Systems,' aiming to enhance grid resilience through AI-driven methods. Notable awards include IEEE Fellow (2023), Isao Takahashi Award (2022), and multiple best paper awards. Wang collaborates extensively, organizing conferences and editing journals. His research spans power electronics, grid stability, and smart grid technologies, with a focus on practical applications in energy transition.
