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.
Ola Carlson is a Professor in Sustainable Electric Power Production at Chalmers University of Technology. He specializes in electrical systems for renewable power production and hybrid electric vehicles. Since 2022, he serves as a senior advisor to the Swedish Wind Centre, focusing on island operation with Chalmers wind turbine and battery systems. Research Interests His research spans renewable power systems, wind energy integration, grid stability, and microgrid optimization. Key projects include modeling Nordic transmission systems, analyzing wind turbine bearing currents, and developing maintenance schedules for aging components. Article Trends Recent publications emphasize wind turbine design, microgrid stochastic optimization, and dynamic state estimation for transmission protection. Topics cover machine learning applications in forecasting, fault handling, and battery degradation impacts on energy systems. Projects & Collaborations RESIST - Energy islanding for resilient systems (2026–2027) COSPACT - Nordic-Baltic co-simulation platform (2020–2023) Fossil Free Energy Districts (2016–2019) Collaborations with ABB, Swedish Energy Agency, and European Commission Labs & Teams Works with Power Grids and Components at Chalmers, leading projects like 'Detecting and eliminating bearing currents' (2018–2023) funded by the Swedish Energy Agency. Involved in Chalmers Campus as a testbed for intelligent grids.
Sigrid Källblad Nordin is an Associate Professor at KTH Royal Institute of Technology, affiliated with the Department of Mathematics (Division of Probability, Mathematical Physics, and Statistics). Her research focuses on Mathematical Finance, Probability Theory, and Stochastic Analysis, with an emphasis on measure-valued processes, martingale optimal transport, and model uncertainty. She holds a DPhil from the University of Oxford (2014). Her work bridges theoretical advancements in stochastic control, optimization, and financial applications. Recent research includes Bayesian optimal adaptive control, robust option pricing, and dynamically consistent investment strategies under uncertainty. She teaches courses such as Financial Mathematics and Financial Derivatives, and supervises PhD students Linn Engström and Chaorui Wang. Publications span journals like Annals of Applied Probability , Finance and Stochastics , and SIAM Journal on Control and Optimization , reflecting contributions to optimal transport, stochastic processes, and financial modeling. She is currently hiring a new PhD student and welcomes inquiries about master thesis supervision.
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.
Nikolaos Kolomvakis is a researcher in the Division of Communication Systems at KTH Royal Institute of Technology in Sweden. He is also a visiting researcher at Ericsson AB in Stockholm. Previously, from 2017 to 2023, he held positions as Systems Engineer and Senior Researcher at Ericsson. His research focuses on wireless communications and signal processing, particularly on developing baseband physical-layer algorithms for distributed/cell-free massive MIMO, holographic MIMO, and large intelligent surfaces. Education: Ph.D. in wireless communications from Chalmers University of Technology , supervised by Prof. Mats Viberg with co-supervision from Prof. Thomas Eriksson and Prof. Michail Matthaiou M.Sc. in information technology & electrical engineering from ETH Zurich (2012) Research Interests: Wireless communications Signal processing Distributed/cell-free massive MIMO Holographic MIMO Large intelligent surfaces Publications: Recent work includes analyzing nonlinear distortion in large arrays and active reconfigurable intelligent surfaces (2025) Exploring spatial frequencies in near-field communications (2025) Investigating 6G performance through gigantic MIMO (2025)
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.
Tobias Oechtering is a Professor at the Division of Information Science and Engineering within the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology. His research focuses on information theory, privacy-preserving technologies, statistical signal processing, machine learning, and smart grid systems. He has held academic positions at KTH since 2008, advancing from Post-Doctoral Researcher to Assistant Professor (2010–2013), Associate Professor (2013–2018), and Professor (2018-present). He has supervised over 20 PhD students and contributed to numerous postdoctoral programs. Research Interests: - Network information theory and physical-layer security - Privacy mechanisms with provable guarantees - Distributed statistical inference and sensor calibration - Reinforcement learning and privacy-aware machine learning - Smart grid privacy and energy management - Wireless communication algorithms and signal processing - Networked control systems and stability analysis He currently supervises 7 PhD students and hosts 3 postdocs. His work has led to over 150 peer-reviewed publications, with recent contributions in privacy-preserving smart grid strategies, adversarial inference control, and information-theoretic security. He has served as editor for IEEE Transactions on Information Forensics and Security and held leadership roles in KTH's Digitalisation Research Platform.
Monowar Bhuyan is an Associate Professor in the Department of Computing Science at Umeå University, Sweden, leading the Cyber Analytics and Learning Group within ADSLab. He holds a Ph.D. in Computer Science from Tezpur University and has held academic positions at Assam Kaziranga University and Umeå University. His research focuses on machine learning, anomaly detection, edge AI, and distributed systems security. He has secured over 35 MSEK in grants from WASP, STINT, and EU Horizon programs. Education Ph.D. in Computer Science and Engineering, Tezpur University (2014) M.Tech. in Information Technology, Tezpur University (2009) B.E. in Computer Science and Engineering, IETE (2007) Research Interests Distributed/Federated/Responsible Machine Learning Cybersecurity and Anomaly Detection in Edge Clouds AI for DDoS Defense and Cyber Resilience Edge AI and Serverless Computing Recent Contributions His recent work addresses secure federated learning, DDoS attack detection in cloud-edge systems, and responsible AI. Key publications include novel frameworks for VSI-DDoS detection and federated learning optimizations. Awards & Grants Best Paper Awards at ICONIP 2023 and ACM ICACCI 2012 WASP NEST Grant (AIR2 Project, 5 MSEK) EU Horizon Europe Grant (SovereignEdge.Cognit, 8.27 MSEK) Lab & Collaborations He leads the Cyber Analytics and Learning Group (ADSlab), collaborating with institutions like KTH, Linköping University, and Nara Institute of Science and Technology (NAIST). The lab focuses on AI-driven security solutions for distributed systems.
Anna Gautier is an Assistant Professor in the Department of Computer Science at Chalmers University of Technology, affiliated with the Division of Data Science and AI. Previously, she was a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology (2023–2025), focusing on mechanism design for multi-robot systems. Her research emphasizes planning under uncertainty, multi-agent systems, and human-robot interaction. She holds a PhD from the University of Oxford (2023), an MSc from the London School of Economics, and dual undergraduate degrees from Washington University in St. Louis. Education Background: PhD in Computer Science, University of Oxford (2023) MSc in Applied Mathematics, London School of Economics BA in Mathematics and BS in Computer Science, Washington University in St. Louis Research Interests: Dr. Gautier explores planning algorithms for multi-agent systems, particularly in uncertain environments. She designs mechanisms to coordinate robots and humans, leveraging game theory and formal methods. Her work addresses challenges like resource allocation, risk-aware decision-making, and trust in autonomous systems. Recent projects include contingency planning for autonomous vehicles and auction-based resource distribution. Professional Activities: She co-chairs the ECAI 2025 Demonstration Track and teaches the course Safe Robot Planning and Control at KTH. Her projects include collaborations with WASP-Nest (PerCorSo) and TECoSA on trustworthy autonomy. She actively publishes in top venues like AAMAS and AAAI. Labs and Teams: Affiliated with Chalmers' Data Science and AI division, she leads research in multi-agent systems and human-AI collaboration.
Kurt Mitman is a Lecturer at the Institute for International Economic Studies (IIES) at Stockholm University. He holds a Professor position at CEMFI and is an Associate Professor at IIES (on leave). His research spans macroeconomics , with a focus on household economics , housing , labor market dynamics , and monetary/fiscal policy . He served as Managing Editor of the Review of Economic Studies (2019-2024) and received an ERC Consolidator Grant for his project HIPSTERMacro . Key research areas: Macroeconomics, Household Debt and Default, Housing Market Shocks Major contributions: Studying unemployment insurance effects, debt-relief policies, and heterogeneous-agent models His work has been widely covered in media outlets including The Wall Street Journal , Bloomberg , and The Economist . He co-organizes the VMACS seminar series and academic conferences like the SITE Session on Macroeconomics and Inequality .
Nikolce Murgovski is an Assistant Professor at Chalmers University of Technology, specializing in Mechatronics . He focuses on electric and hybrid vehicle energy management , autonomous driving systems , and optimization algorithms for powertrain design. His work bridges control theory , battery technology , and transport electrification . Current projects include CHARGE (2023–2026) for charging and trip planning , and EcoPilot (2022–2026) for energy-efficient autopilot development. Collaborates with institutions like Volvo Cars , Swedish Electromobility Centre , and VINNOVA on autonomous vehicle control and thermal energy systems . His recent publications emphasize convex optimization , eco-driving strategies , and collision avoidance in complex environments. He has contributed to tools like CONES for electromobility studies and has led research on hybrid powertrains and predictive energy management .
Urban Persson is a Professor at Halmstad University's Academy of Entrepreneurship, Innovation and Sustainability. He holds a Tech. Dr. in Energy and Environmental Technology from Chalmers University of Technology. His research focuses on energy efficiency, renewable energy resources, and district heating systems, particularly in European contexts. Key projects include Heat Roadmap Europe, Decarb City Pipes 2050, and Pan-European Thermal Atlas. Persson has authored over 30 publications on district heating optimization, GIS-driven energy planning, and heat resource assessments. His work emphasizes sustainable energy transitions and leveraging spatial data for infrastructure design. Education: Technical Doctorate (Energy & Environmental Technology), Chalmers University of Technology. Research Projects: Solar-powered district heating with pit storage for Swedish conditions Heat Roadmap Europe Decarb City Pipes 2050 Pan-European Thermal Atlas Research Interests: District heating economics, GIS applications in energy systems, waste heat utilization, and decarbonization pathways.
Saleh Javadi is a Senior Lecturer at the Department of Mathematics and Natural Sciences at Blekinge Institute of Technology (BTH) in Karlskrona, Sweden. He is actively engaged in research and teaching within the field of systems engineering. His educational background includes: B.Sc. in Electrical-Control Engineering from Amirkabir University of Technology (2009) M.Sc. in Electrical, Electronic and Systems Engineering from The National University of Malaysia (2013) Ph.D. in Systems Engineering from Blekinge Institute of Technology (BTH) (2021) Saleh Javadi's research focuses on signal processing, machine learning, and computer vision , with applications spanning remote sensing, intelligent transportation systems, and AI-driven industrial optimization. His work bridges theoretical advancements with practical implementations, particularly in SAR imagery analysis, drone-based agricultural monitoring, and traffic surveillance systems. His recent publications demonstrate a strong focus on remote sensing technologies, particularly Synthetic Aperture Radar (SAR) image processing and analysis. There's a clear trend toward applying machine learning techniques to solve complex problems in aerial and satellite imagery, traffic monitoring, and agricultural applications. His research shows interdisciplinary connections between computer vision, signal processing, and practical engineering applications. Saleh Javadi has received significant recognition for his innovative work: Innovator of the Year award (SKAPA – Innovation Prize in Memory of Alfred Nobel) in Blekinge for innovative efforts in optimizing and reducing energy consumption in industries by using artificial intelligence ÅForsk Entrepreneur's prize at the Swedish Innovation Council Day – Swedish Incubators & Science Park's annual conference in May 2019 Dr. Javadi is involved in practical applications of his research through projects such as "Artificiell intelligens AI kan reducera ogräsfrön i utsäde" (ongoing) and "Bekämpa Renkavle med hjälp av drönare och Artificiell Intelligens (AI)" (completed). His work demonstrates a strong commitment to translating academic research into real-world solutions that address industrial and environmental challenges. His research appears to be conducted within a collaborative framework, working with colleagues on drone technology, SAR image analysis, and AI applications across multiple domains including agriculture, maritime monitoring, and transportation systems.
Steven Haberman is a Professor of Actuarial Science at Bayes Business School, City, University of London. He has held senior leadership roles, including Deputy Dean, Director, and Dean of Bayes Business School until 2015. Prior to this, he was Dean of the School of Mathematics (1995–2002). His academic journey began at the University of Cambridge (BA in Mathematics), followed by PhD and DSc in Actuarial Science from City University. He has served as a Lecturer in Actuarial Science since 1974 and worked part-time at the Government Actuary's Department (1986–2006). He is a Fellow of the Institute of Actuaries and Royal Statistical Society. Research focuses on mortality modeling (e.g., the Renshaw-Haberman model), longevity risk, pensions, and annuities. He has authored/co-authored 5 books and over 180 papers, and edited journals like Journal of Pension Economics and Finance . Awards include an honorary doctorate from the University of Haifa (2018) and research prizes from the Institute of Actuaries. He has supervised 33 doctoral students and served on professional bodies like the Institute and Faculty of Actuaries and the Financial Reporting Council’s Board for Actuarial Standards. Current roles include Editor-in-Chief of Risks and Chair of the Board of Governors of the London Foundation for Banking and Finance.
Erik Prytz is a Senior Associate Professor in Cognitive Science at the Department of Computer and Information Science (IDA) at Linköping University. His research focuses on applying human factors principles to improve safety-critical systems, particularly in emergency response domains such as first aid, disaster medicine, and prehospital care. He holds a PhD in Human Factors Psychology and has served in roles including Director of the Forum Securitatis graduate school and Program Chair for the Cognitive Science BSc program. Education: PhD in Human Factors Psychology (Old Dominion University, 2014), MSc in Cognitive Science (LiU, 2010). Research Interests: Simulation-based training, stress and mental workload, emergency responder teamwork, and human-system interaction in crisis scenarios. His work emphasizes interdisciplinary collaboration, combining cognitive science, computer science, and medicine to enhance emergency response systems. Recent projects explore driver behavior toward emergency vehicles, ad-hoc responder group dynamics, and optimal placement of bleeding control kits in public spaces. He contributes to initiatives like the Center for Advanced Research in Emergency Response (CARER) and the Forum Securitatis graduate school. Erik’s teaching includes courses on human factors, distributed cognition, and emergency response systems. He actively participates in curriculum development and quality assurance committees within the Faculty of Arts and Sciences.
