جستجوی استاد راهنمای دانشگاهی

Eduardo Gill-Pedroمشاهده پروفایل

استادیار

• Artificial Intelligence Law and Governance
• EU Law
• Human Rights
• +۵ مورد دیگر

Eduardo Gill-Pedro is an Assistant Professor at Lund University's Department of Law, where he serves as an Associate Senior Lecturer in Law and AI. His work focuses on the intersection of artificial intelligence, corporate law, and human rights within the European legal framework. Education: LL.B from the University of Essex LL.M from Stockholm University LL.D from Lund University Dr. Gill-Pedro's research centers on the role of companies in AI governance, particularly examining how artificial persons (corporations) influence the development of AI entities and how these interactions affect legal order and human control. His work bridges EU law, technology governance, and human rights, with special attention to constitutional identity and democratic practice in the digital age. He has made significant contributions to understanding corporate rights within European legal frameworks. His recent publications demonstrate a clear trend toward examining the legal implications of AI systems, particularly focusing on corporate responsibility, democratic practice, and human rights in technological contexts. Gill-Pedro's work increasingly addresses real-world applications of AI governance, as evidenced by his 2025 reference statement on police use of AI for facial recognition. Scientific Awards: René Cassin Thesis Prize 2017 for his doctoral thesis "EU Law, Fundamental Rights and National Democracy" Oscar II award (2017) Dr. Gill-Pedro has directed courses including Internal Market Law, Methodology and Argumentation, and Enforcement of EU Law. He has served as a principal investigator for multiple research projects, including "The Company as a European Supercitizen?" which examined corporate human rights in European law. His research has been supported by various grants, including the Ragnar Söderberg Senior Research Fellowship. He leads research initiatives examining the governance of artificial intelligence and has participated in advanced study groups at the Pufendorf IAS. His current work focuses on the role of companies in AI governance and the fundamental rights of corporate entities within European legal frameworks.

David Bastvikenمشاهده پروفایل

استاد

• Environmental Science
• Climate Change
• Biogeochemistry
• +۷ مورد دیگر

David Bastviken is a Professor at the Environmental Change Theme (TEMAM), Linköping University , specializing in environmental science and biogeochemical cycles. His research focuses on greenhouse gas emissions, particularly methane and carbon dioxide, from freshwater systems and human activities, with implications for climate policy and pollution management. Research Pillars : Aquatic greenhouse gas dynamics, chlorine cycling in soils, drinking water disinfection by-products, landscape-scale carbon budgets Methodologies : Drone-based sensing, hyperspectral imaging, sensor networks, cross-disciplinary ecosystem experiments Notable findings include the discovery of underestimated methane emissions from lakes and rivers, the role of trees in methane uptake , and natural chlorine production in boreal forests. His work has been funded by ERC , Formas , VINNOVA , and The Swedish Research Council . Recent publications highlight climate sensitivity of methane emissions, day-night emission patterns , and global methane budget modeling. He leads international collaborations across Amazonas , Arctic , and Boreal regions.

• Robotics
• Human-Robot Interaction
• Machine Learning
• +۷ مورد دیگر

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.

• 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.

• 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.

Morteza Haghir Chehreghaniمشاهده پروفایل

استاد

• Machine Learning
• Decision Making
• Reinforcement Learning
• +۱۷ مورد دیگر

Morteza Haghir Chehreghani is a Professor of Artificial Intelligence and Machine Learning at the Data Science and AI Division of Chalmers University of Technology , Sweden. He leads the Machine Learning and Decision Making Lab and is affiliated with WASP , CHAIR , and ELLIS . Education : PhD in Computer Science (2014) from ETH Zurich under Prof. Dr. Joachim M. Buhmann Prior Roles : Staff Research Scientist at Naver Labs Europe (2014-2018) Research spans Interactive Machine Learning , Sequential Decision Making , Federated Learning , Efficient Deep Learning , and Graph-Based Learning . Key application areas include Transport , Autonomous Systems , Energy , Drug Discovery , and Computational Biology . Selected Publications (2020-2025) demonstrate expertise in Reinforcement Learning for drug design, Minimax Distance Measures for clustering, and Graph Neural Networks for trajectory analysis. Current work focuses on Combinatorial Bandits and Human-in-the-loop AI . Teaching includes graduate courses like Advanced Topics in Machine Learning (DAT441/DIT41), Algorithms for Machine Learning (TDA233/DIT382), and PhD-level Advanced Reinforcement Learning . He has also taught Statistical Methods for Data Science and Theoretical Foundations of ML . Patents include systems for Autonomous Vehicle Motion Control , K-NN Search via Minimax Distances , and Trip Prediction Algorithms . Collaborative projects involve Nature Communications (2022) and multiple ICML / CVPR publications.

• Total Productive Maintenance
• Artificial Intelligence
• Multi-Criteria Decision Making
• +۳ مورد دیگر

Ebru Turanoglu Bekar is a Senior Lecturer at the Department of Industrial and Materials Science, Chalmers University of Technology, specializing in Smart Maintenance and Production Systems. She contributes to the Production Service Systems & Maintenance research group. Research Interests: Total Productive Maintenance (TPM), Artificial Intelligence applications in manufacturing, Multi-Criteria Decision Making, Performance Measurement systems Recent Focus: Development of data-driven algorithms for predictive maintenance, integration of digital twins in industrial contexts Key Projects: Factory SensAI (2025–2028) - Data integration for AI in manufacturing Trustworthy Predictive Maintenance TPdM (2022–2025)

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.

• Process Technology
• Device Design
• Silicon Carbide (SiC) Electronics
• +۳ مورد دیگر

Carl-Mikael Zetterling is a Professor and Head of Department at Kungliga Tekniska Högskolan (KTH) in Stockholm, Sweden, affiliated with the School of Electrical Engineering and Computer Science (ICT) and the Electronics and Embedded Systems department. His research focuses on process technology and device design for high-temperature, high-power silicon carbide (SiC) electronics, expanding into SiC-based analog and integrated circuits. He has authored over 300 publications, including books on SiC process technology and plagiarism prevention. Dr. Zetterling has held leadership roles such as Vice Dean of the School of ICT (2013–2017) and teacher representative on KTH's faculty board. He has collaborated internationally at Stanford University, Kyoto University, and Kyoto Institute of Technology. His work addresses applications in extreme environments, including Venus exploration and fusion reactor monitoring, with a focus on radiation tolerance and thermal resilience. The 15 most recent publications highlight trends in wide bandgap semiconductors, gamma irradiation effects on SiC devices, and high-temperature integrated circuits. His articles span structural health monitoring with machine learning, novel SiC diode designs, and radiation-hardened electronics. Key contributions include advancements in self-aligned contacts, trench MOSFETs, and compact modeling for extreme conditions. While no formal awards are listed, his roles in technical program committees (TMS Electronic Materials Conference, IEEE SISC Conference) and editorial work demonstrate significant academic service. He teaches courses ranging from digital design to high-temperature electronics, overseeing degree projects in embedded systems, communication, and nanotechnology.

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.

Gustav Henterمشاهده پروفایل

استادیار

• Deep Generative Models
• Speech Synthesis
• 3D Character Animation
• +۳ مورد دیگر

Gustav Henter is an Assistant Professor in Intelligent Systems at KTH Royal Institute of Technology, specializing in Machine Learning. He is affiliated with the Division of Speech, Music and Hearing (TMH) within the School of Electrical Engineering and Computer Science. His research focuses on deep generative models for applications like speech synthesis, 3D character animation, and human-computer interaction. He holds a Docent degree from KTH and has held post-doctoral positions at the University of Edinburgh and the National Institute of Informatics in Tokyo. Education: PhD in Electrical Engineering (KTH, 2013), MSc in Engineering Physics (KTH, 2007). He supervises doctoral students in areas like gesture synthesis and multimodal interaction. His work is supported by grants from the Wallenberg AI, Autonomous Systems, and Software Program (WASP) and South Korea's MOTIE. He co-founded Motorica AB to commercialize motion synthesis research. Awards include Best Paper Awards at ICMI 2020 and IVA 2020, and recognition for student theses. His research spans generative AI, perceptual evaluation, and robust statistical models. He organizes the GENEA Challenge and Workshop series for gesture generation benchmarking.

• Biomaterials
• Biomechanics
• Materials Science
• +۴ مورد دیگر

Cecilia Persson is a Professor at Uppsala University in the Department of Materials Science and Engineering; Biomedical Engineering. She leads the BioMaterial Systems (BMS) research group within the Division of Biomedical Engineering, focusing on the development of new biomaterials through additive manufacturing. She also directs a Competence Centre in Additive Manufacturing for the Life Sciences and the national Research Technology Platform WISE Additive. 2018, Professor in Materials Science, Uppsala University 2015, Docent (Assoc. Prof.) in Engineering Science with Specialization in Materials Science, Uppsala University 2009, PhD in Mechanical Engineering, University of Leeds 2004, MSc in Materials Engineering, European degree (EEIGM) with triple diploma Persson's research focuses on biomaterials, biomechanics, materials science, and additive manufacturing. Her work takes an integrated approach to solving clinical and sustainability problems, combining materials science, mechanical and biological engineering with new technologies like 3D printing and machine learning. Key research areas include magnesium-based alloys for bone substitutes, titanium-based alloys for permanent implants, and machine learning methods to enhance manufacturing efficiency. Analysis of her recent publications shows a strong emphasis on additive manufacturing of biomaterials, particularly magnesium and titanium alloys. Her work explores microstructure control, mechanical properties optimization, antibacterial properties, and patient-specific implant design. The research demonstrates a clear trajectory toward more sustainable, patient-adapted medical solutions using advanced manufacturing techniques. Persson has received funding from prestigious organizations including the Swedish Research Council (VR), the Knut and Alice Wallenberg Foundation (KAW), the Swedish Foundation for Strategic Research (SSF), Sweden's Innovation Agency (VINNOVA), and the EU. As an academic leader, Persson has served as Section Dean of Engineering (2020-2023), President of the Scandinavian Society of Biomaterials (2019-2023), and Coordinator of EU Innovative Training Network NU-SPINE (2019-2023). Her BioMaterial Systems research group takes an integrated approach to solving clinical and sustainability problems, bridging fundamental scientific mechanisms with high societal relevance.

• Turbulence Modeling
• Computational Fluid Dynamics (CFD)
• Large Eddy Simulation (LES)
• +۷ مورد دیگر

Lars Davidson is a Professor in the Department of Fluid Dynamics at Chalmers University of Technology. His research focuses on numerical simulations of fluid flow and heat transfer, with an emphasis on turbulence modeling for Large Eddy Simulation (LES) and hybrid LES/RANS methods. He has developed computational codes CALC-BFC and CALC-LES based on finite-volume techniques, and recently integrated machine learning to enhance wall functions and turbulence models. Key projects include Hybrid LES/RANS for wall-bounded flows Machine learning applications in fluid dynamics Aeroacoustic noise reduction in automotive and aerospace systems Wind turbine load analysis in forested regions . His publications span 302 articles in journals and conferences, with recent work on Neural networks for turbulence closure Plasma actuators for drag reduction Lattice Boltzmann wall-modeled LES . Collaborations include teams at Volvo, Siemens, and international research groups.

• 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.

Leila Methnaniمشاهده پروفایل

پژوهشگر

• Artificial Intelligence Ethics
• Explainable AI (XAI)
• Trustworthy AI
• +۵ مورد دیگر

Leila Methnani is a doctoral student at the Department of Computing Science at Umeå University . Her research focuses on ethical and sociotechnical challenges in artificial intelligence, particularly in areas such as AI alignment , trustworthy AI , and human-AI collaboration . She has published extensively on topics including Explainable AI (XAI) , MLOps , and hybrid human-AI systems . Her recent work explores: Trustworthy AI in variable autonomy robotic systems Explainable and counterfactual-based AI interfaces for industrial operators Operationalizing AI ethics through socio-technical assessments Real-time reactive planning with social norms in multi-agent systems She has co-authored publications in journals such as Ethics and Information Technology , ACM Computing Surveys , and Frontiers in Artificial Intelligence . She is reachable via email at leila.methnani@umu.se .