جستجوی استاد راهنمای دانشگاهی

• Control Theory
• Distributed Control
• Networked Systems
• +۱۲ مورد دیگر

Emma Tegling is a Senior Lecturer (Associate Professor) at the Department of Automatic Control, Faculty of Engineering (LTH), Lund University, Sweden. She joined the department in January 2021 and holds a prestigious WASP (Wallenberg AI, Autonomous Systems and Software Program) professorship. Her research focuses on the analysis and control of large-scale networked systems, with applications in distributed electric power networks and socio-epidemiological networks. She is actively involved in multiple research projects, supervises several PhD students, and contributes to major academic events in control theory. Education: Ph.D. in Electrical Engineering, KTH Royal Institute of Technology (2019) M.Sc. in Engineering Physics, KTH Royal Institute of Technology (2013) B.Sc. in Engineering Physics, KTH Royal Institute of Technology (2011) Emma Tegling's research centers on the fundamental limitations of distributed control, particularly in large-scale and non-normal network systems. Her work addresses critical challenges in vehicular formations, power grids, and social networks. She develops scalable control designs, consensus protocols, and optimal control strategies for complex networked environments. Her recent publications highlight breakthroughs in string stability, transient performance, and distributed optimization. The trend in her articles shows a strong focus on mathematical control theory, network dynamics, and real-world applications in socio-technical systems. Scientific Awards: WASP professorship (Wallenberg AI, Autonomous Systems and Software Program) Emma Tegling leads and co-leads several significant research grants, including WASP NEST: Learning in Networks and Dynamics of Complex Socio-Technological Network Systems. She actively supervises PhD students such as Jonas Hansson and David Ohlin, whose work has led to novel consensus protocols and optimal control formulations. Her academic leadership extends to organizing the European Control Conference and co-organizing interdisciplinary workshops on power and democracy in modern societies. She is also involved in public engagement and academic service through supervision and project coordination. Emma Tegling is a key member of the Department of Automatic Control at Lund University, contributing to research teams focused on networked systems, control theory, and AI integration. She collaborates extensively within ELLIIT (the Linköping-Lund initiative on IT and mobile communication) and participates in cross-disciplinary labs working on AI, digitalization, and natural/artificial cognition. Her work is aligned with UN Sustainable Development Goals related to sustainable energy and resilient infrastructure.

Anna Singerمشاهده پروفایل

استاد

• Family Law
• Inheritance Law
• Children's Rights
• +۳ مورد دیگر

Anna Singer is a Professor of Civil Law, specializing in Family Law , at the Department of Law , Uppsala University . She serves as Dean of the Faculty of Law and contributes extensively to research on children's rights , inheritance law , and legal challenges in reproductive technology . Contact: Anna.Singer@jur.uu.se | Phone: 018-471 20 35 | Address: Trädgårdsgatan 1, Uppsala. Education: Juris Doctor (JD), Doctor of Juridical Science (doc) Research Interests: Cultural tensions in family law, Nordic inheritance systems, children's legal status, DNA technology in parenthood, international family law comparisons, and postmodern legal reforms. Publication Trends: Recent works emphasize Nordic legal harmonization , children's autonomy , and ethical dilemmas in reproductive law , with a focus on Scandinavia and cross-cultural analysis. Advising & Grants: No explicit student advising details. Collaborated on EU family law reports and Nordic cohabitation law projects.

Liane Colonnaمشاهده پروفایل

استادیار

• AI Ethics
• Data Protection Law
• Algorithmic Regulation
• +۲ مورد دیگر

Liane Colonna is an Assistant Professor in Law and Information Technology at the Department of Law, Stockholm University , where she investigates ethical and legal challenges arising from AI-driven practices in higher education. She also engages in methodologically oriented research at the intersection of AI and Law, contributing to the Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society. Additionally, Liane serves as the director of the Swedish Law and Informatics Research Institute (IRI) and is a member of the New York Bar since 2008. Primary Affiliation: Department of Law, Stockholm University Institute Leadership: Director, Swedish Law and Informatics Research Institute (IRI) Professional Status: Member of the New York Bar Research Interests: Ethical and legal challenges of AI in higher education Methodological approaches in AI and Law Data protection and privacy by design Regulatory frameworks for AI and emerging technologies Privacy implications of lifelogging and health IoT International data governance and surveillance law Publications demonstrate expertise in AI regulation, GDPR compliance, and privacy-preserving technologies, particularly for assisted living and educational contexts. Her work bridges technical implementation with legal accountability, emphasizing human oversight and ethical design.

• Control Systems
• Electric Vehicles
• Hybrid Electric Vehicles
• +۴ مورد دیگر

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 .

Roland Larssonمشاهده پروفایل

استاد

• Tribology
• Lubrication
• Contact Mechanics
• +۲ مورد دیگر

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.

• Energy Efficiency
• Renewable Energy Resources
• District Heating Systems
• +۳ مورد دیگر

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.

Panagiotis Papapetrouمشاهده پروفایل

استاد

• Data Science
• Machine Learning
• Time Series Analysis
• +۵ مورد دیگر

Panagiotis Papapetrou is a Professor of Data Science and Deputy Head of Department at the Department of Computer and Systems Science , Stockholm University (since 2017). He also serves as Head of the Data Science Research Group and holds an Adjunct Professor position at Aalto University (Finland). As a Board Member of the Swedish Association for Artificial Intelligence (SAIS) , he contributes to shaping AI research directions in Sweden. Research Pillars: Algorithmic data mining, interpretable machine learning, time series classification, and health informatics Key Projects: AI for societal fairness, digital twins for smart buildings, EXTREMUM for explainable medical AI, and e-learning personalization Teaching Legacy: Developed courses in Data Mining (HT2013-2022), Machine Learning (VT2022-2024), and Health Informatics (VT2018-2021) His work focuses on interpretable AI for healthcare applications, particularly through counterfactual explanations for time series classification and forecasting. This includes developing methods like Glacier for constrained counterfactuals and Ijuice for k-justified explanations. His research also explores multimodal clustering of sepsis patient records and federated learning approaches for ICU mortality prediction. Recent scientific contributions include: CounterFair (2024): Group fairness analysis via counterfactual burden metrics M-ClustEHR (2024): Multimodal clustering for electronic health records COMET (2024): Constraint-based glucose forecasting explanations Temporal pattern mining (2024-2025): Enhanced forecasting models through decomposition Z-Time (2024): Interpretable multivariate time series classification His editorial leadership includes: Action Editor at Machine Learning Journal (since 2024) Action Editor at Data Mining and Knowledge Discovery (since 2018) Guest Editorial Board for ECML/PKDD Journal Track (2014-2019)

Eva Ermanمشاهده پروفایل

استاد

• Political Philosophy
• Democratic Theory
• Global Democracy
• +۵ مورد دیگر

Eva Erman is Professor of Political Science at Stockholm University and Deputy Head of the Department of Political Science. She serves as Chief Editor of Ethics & Global Politics and has held visiting scholar positions at institutions including the University of Melbourne, London School of Economics, and George Mason University. Her research bridges political philosophy, global democracy, and the ethical implications of artificial intelligence governance. Her scholarly work emphasizes meta-theoretical and methodological questions in political theory, focusing on feasibility, epistemic norms, and the interplay between moral and political legitimacy. She explores the democratization of global governance structures and the role of civil society actors in transnational decision-making processes. Key article themes since 2025 include algorithmic fairness, moral norms in AI governance, and democratic challenges in transnational AI frameworks 2024 contributions analyze legitimacy, behaviorism in political realism, and function-sensitive approaches to global governance 2023 research expands on empirical and normative AI governance, political normativity definitions, and behavioral theory critiques Erman's academic leadership extends to organizing international workshops and refereeing for top journals like Journal of Philosophy , American Political Science Review , and Political Studies . Her projects address critical intersections of technology, democracy, and justice in the 21st century.

Saleh Javadiمشاهده پروفایل

مدرس ارشد

• Systems engineering
• Signal processing
• Machine learning
• +۱ مورد دیگر

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.

• Information Theory
• Privacy (Data Disclosure)
• Statistical Signal Processing
• +۴ مورد دیگر

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.

Erik Prytzمشاهده پروفایل

دانشگاهی

• Human Factors
• Emergency Response Systems
• Stress Management
• +۳ مورد دیگر

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.

Ahmed Hemaniمشاهده پروفایل

استاد

• Computer Engineering
• Embedded Systems
• Hardware Acceleration
• +۵ مورد دیگر

Professor Ahmed Hemani is a faculty member at the Division of Electronics and Embedded Systems, KTH Royal Institute of Technology, affiliated with the Digital Futures Faculty. He holds the role of PI for the project 'New Chip Architectures for Industrial Vision' and leads research in reconfigurable computing, memristor-based systems, and hardware acceleration for AI and edge computing. His work bridges theoretical computer science with practical VLSI design and embedded systems development. He actively contributes to cross-disciplinary initiatives at Digital Futures, a joint center with Stockholm University and RISE Research Institutes of Sweden focused on digital innovation. His research emphasizes scalable FPGA/HPC architectures, low-power neuromorphic systems, and optimization techniques for custom silicon solutions. Current projects include a Lego-inspired edge AI framework and memristor-driven MIMO acceleration. Teaching responsibilities span advanced courses in SOC design, digital system verification, and embedded systems. He supervises advanced-level degree projects across computer engineering and ICT innovation specializations, emphasizing hands-on hardware-software co-design methodologies. Recent publications highlight innovations in memristor applications, FPGA-based acceleration, and reconfigurable architectures for neural networks and bioinformatics. His work addresses challenges in dark silicon utilization, energy-efficient computation, and high-performance embedded systems.

Roger Herbertمشاهده پروفایل

مدرس ارشد

• Hydrology
• Hydrogeology
• Biogeochemistry
• +۹ مورد دیگر

Roger Herbert is a Senior Lecturer in Hydrology and Associate Professor in Biogeochemistry at the Department of Earth Sciences, Uppsala University, where he also serves as Director of the Civil Engineering program in Environmental and Water Engineering. His research is centered on biogeochemical processes in water-saturated systems, particularly focusing on denitrification in bioreactors, groundwater remediation, and contaminant transport in double porosity media. His research interests include: Denitrification in woodchip and biochar bioreactors Groundwater and mine drainage treatment Reactive transport modeling in porous media Arsenic speciation and uptake in plants Silica nanoparticle interactions in soil-plant-water systems Microbial controls on nitrogen cycling and greenhouse gas emissions His recent publications (2023–2025) demonstrate a strong focus on innovative bioremediation technologies for wastewater and mine drainage, particularly using biochar and woodchip systems. These works emphasize modeling, microbial ecology, and field-scale applications, showing a consistent trend toward sustainable and scalable solutions for water quality challenges in cold climates and industrial settings. Roger Herbert leads the EIT RawMaterials project NITREM, which aims to upscale bioreactor technology for the mining and quarrying industry. He has supervised or collaborated on numerous studies related to mine waste treatment and environmental impact mitigation. He is actively involved in collaborative research projects and has published extensively in high-impact journals such as Water Research , Journal of Environmental Quality , and Environmental Science & Technology . His work bridges experimental studies, field applications, and numerical modeling, contributing significantly to environmental engineering and hydrogeology.

Franziska Klüglمشاهده پروفایل

استاد

• Multi-Agent Systems
• Agent-Based Simulation
• Artificial Intelligence
• +۴ مورد دیگر

Franziska Klügl is a Professor in Computer Science at Örebro University's Faculty of Business, Science and Engineering, affiliated with the Center for Applied Autonomous Sensor Systems (AASS). She currently leads the KKS-funded TeamRob project on Human-Robot Teamwork and serves as Deputy Dean of the faculty since January 2023, chairing the academic appointment committee. Previously, she headed the Computer Science department (2020-2022) and served on the faculty board (2019-2022). Her research focuses on: Multi-agent systems : Development of languages, processes, and tools for agent-based simulation Interdisciplinary applications : Transportation, economics, epidemics, production, and mining simulations Simulation engineering : Integrating AI, machine learning, and formal methods to create accessible modeling tools for domain experts She created SeSAm , a visual programming tool for agent-based simulation that enables rapid prototyping of complex models. Analysis of her recent publications reveals three dominant themes: Human-robot collaboration frameworks and intention recognition systems Economic impacts of automation on labor markets and engineering services Advanced simulation methodologies using affordance theory and reinforcement learning She teaches software engineering, multi-agent systems, and agent-based modeling across multiple programs, including the WASP AI&ML PhD course. She leads research groups at the Machine Perception and Interaction Lab and oversees the TeamRob human-robot teamwork project.

• Offshore Renewable Energy Systems
• Wave Power Farm Modeling
• Extreme Weather Resilience
• +۳ مورد دیگر

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.