Find Academic Supervisors

Åsa Carlsson TedgrenView profile

Associate Professor

• Medical Radiation Physics
• Brachytherapy
• Radiation Dosimetry
• +4 more

Åsa Carlsson Tedgren is an Associate Professor of Medical Radiophysics at Linköping University and holds a Senior Clinical Investigator Award from the Swedish Cancer Society (2018–2024). She combines research in radiation dosimetry and brachytherapy with clinical work as a medical physicist at Karolinska University Hospital. Her affiliations include the Centre for Medical Image Visualization (CMIV) at LiU and the Department of Oncology-Pathology at Karolinska Institute. Her research focuses on advancing quantitative imaging techniques for radiotherapy, particularly dual-energy CT for atomic composition analysis. She teaches medical radiation physics at LiU and Stockholm University, and contributes to ESTRO brachytherapy courses. Key awards include the Swedish Cancer Society’s Senior Clinical Investigator Award, supporting her 70% research time. Her work spans brachytherapy innovations, dosimetry advancements, and clinical translation. Recent publications highlight breakthroughs in heterogeneous tissue handling, detector calibration, and treatment planning algorithms. She supervises PhD students and actively collaborates in multidisciplinary teams across institutions.

Olof Dahlqvist LeinhardView profile

Associate Professor

• Magnetic Resonance Imaging (MRI)
• Muscle Health
• Metabolic Disorders
• +5 more

Olof Dahlqvist Leinhard is an Associate Professor at Linköping University, affiliated with the Faculty of Medicine and Health Sciences and the Department of Health, Medicine and Caring Sciences. He is part of the Division of Diagnostics and Specialist Medicine (DISP) and the Unit of Radiological Sciences (RAD). His research focuses on advancing MRI techniques to study fat and muscle tissue in health and disease, particularly examining the impact of metabolic disorders, aging, and treatments on muscle and fat composition. Research interests include the development of MRI-based methods for quantifying skeletal muscle health, adipose tissue distribution, and their associations with cardiometabolic outcomes. He investigates conditions such as type 2 diabetes, muscle diseases (e.g., Duchenne Muscular Dystrophy, FSHD), liver cirrhosis, and the effects of hormone therapy in transgender populations. His work also addresses the role of muscle composition in frailty, physical performance, and mortality risk across diverse patient groups. His publications explore topics like the efficacy of drugs (e.g., tirzepatide, liraglutide) on muscle health, longitudinal changes in body composition after interventions, and imaging applications in neuromuscular and metabolic disorders. He emphasizes translating imaging innovations into clinical practice for better disease assessment and patient management. Scientific awards: None explicitly listed in the provided texts. Advising and grants: No formal advisees or grant details are mentioned. His research collaborations include studies on fibromyalgia, COPD, and liver transplant recipients, reflecting a focus on interdisciplinary projects. Labs/Teams: Active within the Division of Diagnostics and Specialist Medicine (DISP) and the Unit of Radiological Sciences (RAD), contributing to clinical and experimental studies in radiology and metabolic medicine.

Niklas CarlssonView profile

Professor

• Distributed Systems
• Network Security
• Streaming Media Technologies
• +4 more

Niklas Carlsson is a Professor at Linköping University's Department of Computer and Information Science (IDA), where he leads research in distributed systems, network security, and multimedia streaming. He holds a M.Sc. in Engineering Physics from Umeå University and a Ph.D. in Computer Science from the University of Saskatchewan, with postdoctoral experience in Canada. His research spans adaptive streaming technologies, privacy-preserving systems, and sports analytics. Notable projects include the ASTECC initiative on edge-cloud systems and collaborations with Linköping Ice Hockey Club on strategy analysis. He has authored over 150 publications, including works on video fingerprinting, homomorphic encryption, and social media dynamics. Carlsson actively serves on editorial boards and conference committees (e.g., ACM SIGMETRICS, MASCOTS) and has received awards for best papers (2022, 2023) and innovative frameworks like AnonFACES. His lab focuses on real-world applications of theoretical insights, emphasizing measurable performance improvements.

Martin FalkView profile

Senior Lecturer

• Scientific Visualization
• Molecular Visualization
• Volume Rendering
• +4 more

Martin Falk is a Senior Lecturer in the Scientific Visualization Group at Linköping University's Department of Science and Technology (ITN). He holds a Ph.D. (Dr. rer. nat.) from the University of Stuttgart (2013). His research focuses on molecular visualization, large-scale volume rendering, cryoEM visualization, and systems biology, with expertise in uncertainty visualization and spatio-temporal data analysis. Falk co-organized the Eurographics and EuroVis conferences in 2020, which attracted over 2,300 participants and 100 video sessions viewed nearly 38,000 times. Research interests span medical imaging (e.g., histological analysis of vascular specimens) and plasma physics (e.g., studying plasma instabilities and boundary dynamics). He collaborates across disciplines, contributing to tools like the Topology ToolKit and Inviwo visualization frameworks. His work bridges computational methods with biomedical and physical sciences, emphasizing scalable visualization techniques for complex datasets. Key contributions include developing visual environments for protein modeling validation and advancing topological data analysis methodologies. Falk’s research is published in journals like IEEE Transactions on Visualization and Computer Graphics and New Journal of Physics, reflecting his dual expertise in visualization and applied physics.

Sören AnderssonView profile

Professor

• Infectious Diseases
• Vaccine Development
• Laboratory Diagnostics
• +3 more

Sören Andersson is a Professor of Medical Science at Örebro University, affiliated with the School of Medical Sciences and the Department of Medical Sciences. He holds a PhD in Medicine from Karolinska Institutet (1999) and was promoted to Docent (2006) and Professor at Örebro University (2015). His career includes roles at the World Health Organization, Swedish Institute for Communicable Disease Control (Smi), and Örebro University Hospital, where he led the Department of Laboratory Medicine until 2020. He currently advises the Public Health Agency of Sweden on national vaccination programs, including the introduction of COVID-19 vaccines. Education: PhD in Medicine, Karolinska Institutet (1999) Docent of Medical Science, Örebro University (2006) Professor of Medical Science, Örebro University (2015) Research Interests: Focuses on global health, infectious diseases, and vaccine development. Key areas include HIV/AIDS epidemiology, diagnostics, and vaccine trials; sexually transmitted infections (STIs) such as chlamydia; and plant-based vaccine production. His work emphasizes practical solutions for resource-limited settings, including edible vaccines and diagnostic strategies. Publications: Recent work explores HIV testing accuracy, probiotic-based vaccines, and co-infection dynamics in Africa. Highlights include studies on Chlamydia vaccines and HPV genotyping in Mozambique and Uganda. Awards & Grants: No explicit awards listed, but his research has been supported by international collaborations (e.g., WHO, UNAIDS) and grants for vaccine development projects like 'Developvaccines@oru.' Advising & Teams: Leads research groups such as the Inflammatory Response and Infection Susceptibility Center (iRiSC) and Molecular Biochemistry. His lab focuses on mucosal vaccine delivery, molecular epidemiology, and diagnostic reference functions for blood-borne/STIs. Labs/Teams: Active in the Life Science Centre and collaborates with global networks, including Mozambican and Ugandan research partners.

Amy LoutfiView profile

Professor

• Artificial Intelligence
• Robotics
• Human-Robot Interaction
• +5 more

Amy Loutfi is a Professor of Information Technology at Örebro University, where she leads the AI, Robotics and Cybersecurity Center (ARC), and serves as Program Director for the Wallenberg AI, Autonomous Systems and Software Program (WASP) at Linköping University. Born in Saint John, Canada (1978), she earned her PhD in Computer Science from Örebro University (2006) and became a Docent (2011) and Professor (2015) in Information Technology there. Her research focuses on intelligent sensor systems, particularly their integration with artificial intelligence to convert raw data (e.g., from robotic olfaction or vision sensors) into human-interpretable semantic information. She explores human-robot interaction dynamics, emphasizing safety, collaboration, and usability across diverse environments like homes and industries. Key projects include BioLearning (water quality analysis), MicroSens (taste perception via microbiota), and TeamRob (robot teams working with humans). Amy’s work bridges technical innovation with societal impact, addressing challenges in healthcare, elder care, and smart home technologies. She advocates for Sweden’s national AI strategy and emphasizes ethical considerations in emerging robotics. Her research also involves collaboration with industry and public sectors, as seen in the E-care@home and Mednose initiatives. In 2020, she was elected to the Royal Swedish Academy of Engineering Sciences (IVA) for her contributions. Her grants and projects include strategic funding for AI applications and interdisciplinary collaborations. She collaborates with global teams and contributes to conferences like ICSR (Social Robotics) and ECAI (Artificial Intelligence).

• Self-Adaptive Systems
• Cyber-Physical Systems
• Software Engineering
• +4 more

Danny Weyns is a Professor at Linnaeus University's Department of Computer Science and Media Technology, Faculty of Technology. He leads the AdaptWise research group focusing on self-adaptive software systems and contributes to the Linnaeus University Centre for Data Intensive Sciences and Applications. His work spans cyber-physical systems, digital twins, and formal methods for system adaptation. Education: Extensive academic background in computer science, with a focus on multi-agent systems and distributed computing. Notable projects include the Aladino project on digital twins and PROSSES on secure systems. Research interests emphasize self-adaptive systems, runtime decision-making, and integrating AI with adaptive mechanisms. His publications address challenges like adaptation space reduction, uncertainty management, and industry applications of self-adaptation. Key contributions include the ActivFORMS framework for model-based adaptation and the development of methodologies like ASPLe for systematic reuse in self-adaptive systems. He collaborates internationally and chairs conferences like SASO and SEAMS.

Ove EdforsView profile

Professor

• Radio Systems
• Statistical Signal Processing
• Massive MIMO
• +5 more

Ove Edfors is a Professor at the Department of Electrical and Information Technology, Lund University, affiliated with the Faculty of Engineering (LTH). His primary research focuses on radio systems, statistical signal processing, and massive MIMO technologies. He is a core member of the LTH Profile Area: AI and Digitalization and the LU Profile Area: Natural and Artificial Cognition. Edfors leads the NEXTG2COM Vinnova Competence Centre and contributes to ELLIIT initiatives. His research spans multi-carrier systems, low-complexity algorithms, and wireless communication applications. Key projects include 6G radio testbed development and millimeter-wave channel characterization. He has co-authored over 225 publications and supervised 22 graduate students. Notable achievements include the IEEE Signal Processing Society Donald G. Fink Award (2023) and the IEEE Communications Society Best Tutorial Paper Award (2018). Recent work emphasizes indoor localization via multi-sensor fusion (LuViRA Dataset) and energy-efficient MIMO processors. Active collaborations involve global institutions and industry partners in 5G/6G infrastructure. Edfors' contributions align with UN SDGs for affordable and clean energy (Goal 7) through energy-efficient wireless systems and innovation (Goal 9).

Anders WåhlinView profile

Associate Professor

• Cerebral Hemodynamics
• Neuroimaging
• Aging Neuroscience
• +2 more

Anders Wåhlin is Associate Professor at Umeå universitet's Department of Applied Physics and Electronics, with additional affiliations in Biomedical Engineering and Functional Brain Imaging where he serves as Director of the Umeå Centre for Functional Brain Imaging (UFBI). His multidisciplinary research integrates neuroimaging, hemodynamics, and aging neuroscience. Research focuses on cerebrovascular physiology using advanced 4D flow MRI techniques to investigate cerebral blood flow regulation, vascular stiffness, and blood-brain barrier integrity in aging populations. Additional work explores neurochemical pathways linking dopamine receptor availability to cognitive decline. Publications demonstrate consistent emphasis on neurovascular coupling mechanisms, with methodological innovations in MRI quantification and computational fluid dynamics modeling. Recent work establishes connections between vascular pathology, neuroinflammation, and neurodegenerative processes. Leads multiple research groups in Biomedical Engineering and coordinates the MT4North project developing medical technology business models.

Joacim RocklövView profile

Visiting Professor

• Climate Change and Health
• Infectious Disease Epidemiology
• Global Health
• +3 more

Joacim Rocklöv is a Visiting Professor at Umeå University's Department of Epidemiology and Global Health and an Alexander von Humboldt Professor at Heidelberg University's CSID Lab. His research focuses on the intersection of climate change, global health, and infectious disease epidemiology. He leads projects on predictive modeling for emerging diseases, early warning systems, and climate-driven health impacts. As a Docent, he emphasizes using climate information for public health prevention, with a focus on vector-borne diseases like dengue and West Nile virus. Research Projects: BEPREP (2022–2027) IDAlert: Infectious Disease Decision-Support Tools (2022–2027) Zika Preparedness Latin American Network (2016–2020) Key Research Interests: Climate change impacts on disease transmission, vector ecology (Aedes mosquitoes), and developing predictive algorithms for public health preparedness. His work spans global regions, including Southeast Asia, Africa, and Europe. Awards: Docent (Swedish Higher Academic Title) Grants & Collaborations: Leads international projects funded by the EU, WHO, and the Lancet Countdown. His lab develops tools for climate resilience and health policymaking. Labs/Teams: Heads the Joacim Rocklöv Lab Group at Umeå and collaborates with the CSID Lab at Heidelberg University.

• Quantum Chemistry
• Computer Science
• Computational Physics
• +3 more

Kerstin Andersson is an Associate Professor in Computer Science at Karlstad University. Her research focuses on quantum chemical calculations, particularly using the MOLCAS software to explore organic solar cells and molecular properties. She has held roles including postdoc at IBM (California), assistant professor in theoretical chemistry at Lund University, and visiting professor in computational physics at Linköping University. Her academic journey includes undergraduate studies in engineering physics and graduate work in theoretical chemistry at Lund University, supervised by Björn Roos. Teaching spans foundational computer science, programming languages, and societal impacts of technology. Research interests blend computational chemistry and theoretical computer science, with key contributions to CASPT2 method development, electronic spectra analysis (e.g., Cr₂, C60), and entropy-related mathematical modeling. Notable publications include studies on molecular properties (TCNQ, VCr), cellular automata theory, and epistemological reflections in education (in Swedish). Her work bridges quantum chemistry and computer science through algorithmic advancements in molecular simulations and information theory. Grants and collaborations are implied through her diverse postdoctoral and visiting roles. No lab/teams explicitly mentioned, but MOLCAS software usage suggests computational infrastructure involvement.

Stefan LindskogView profile

Professor

• Cybersecurity
• Network Security
• Intrusion Detection Systems
• +7 more

Stefan Lindskog is a full Professor at the Department of Computer Science, Karlstad University, Sweden. His research focuses on tunable security services, network security protocols, intrusion detection systems, and encryption methodologies. He has held academic positions at Karlstad University since 1990 and holds a PhD in Computer Engineering from Chalmers University (2005) and a Docent degree in Computer Science from Karlstad University (2008). His work emphasizes practical cybersecurity solutions, including firewall usability, multipath TCP security, and privacy-preserving technologies. Lindskog has authored over 60 peer-reviewed publications, including studies on encrypted network traffic analysis, Tor anonymity vulnerabilities, and firewall rule optimization. He collaborates extensively with industry partners and academic networks, contributing to projects like the EU-funded NEWCOM++ initiative. Teaching: Real-Time Systems (7.5 ECTS) Key Research Themes: Security service tunability, adaptive intrusion detection, and secure communication protocols Collaborations: HITS project (High Quality Networked Services in a Mobile World) Publications span topics from malware detection in encrypted traffic to systematic reviews of firewall usability. Lindskog’s work bridges theoretical security models and operational system implementation, with a focus on real-world applicability in industries like offshore energy and mobile communications.

Sindri MagnússonView profile

Associate Professor

• Distributed Optimization
• Machine Learning
• Artificial Intelligence
• +4 more

Sindri Magnússon is an Associate Professor and Senior Lecturer at Stockholm University's Department of Computer and Systems Sciences (DSV), part of the Data Science Research Group. He holds a B.Sc. in Mathematics from the University of Iceland (2011), a Master’s in Applied Mathematics (Optimization and Systems Theory) from KTH Royal Institute of Technology (2013), and a Ph.D. in Electrical Engineering from KTH (2017). He completed a postdoctoral fellowship at Harvard University (2018–2019) and was a visiting PhD student there in 2015–2016. His research focuses on distributed optimization, decision-making, and machine learning in cyber-physical systems and IoT. Key projects include AI-driven equitable decision-making, smart converter control for renewable energy systems, federated reinforcement learning, and sustainable data-driven algorithms. His work bridges core data science with applications in critical infrastructures, energy systems, and societal challenges. Recent articles explore multi-objective optimization for satellite scheduling, federated learning for privacy-preserving AI, and reinforcement learning in non-stationary environments. His contributions span theory and practice, addressing scalability, sustainability, and ethical AI. He is actively involved in the Data Science Research Group, which develops algorithmic methods for decision-making in smart cities and energy systems. No awards or grants are explicitly listed, but his projects suggest significant research funding and collaboration.

Truls NybergView profile

Researcher

• Autonomous Vehicles
• Motion Planning
• Risk-aware Planning
• +5 more

Truls Nyberg is an Industrial Postdoc at TRATON Group, affiliated with the Division of Robotics, Perception and Learning (RPL) at KTH Royal Institute of Technology. His research focuses on foundation models and vision-language models for decision-making and motion planning in autonomous vehicles, addressing critical challenges in occlusion handling and risk assessment. His academic background includes: PhD in Computer Science (Robotics, Perception and Learning) from KTH Royal Institute of Technology (2025), with thesis "Mind the Unknown: Risk- and occlusion-aware motion planning for autonomous vehicles" supervised by Jana Tumova and co-supervised by Patric Jensfelt MSc in Control and Information Systems from Linköping University BSc in Applied Physics and Electrical Engineering from Linköping University Nyberg's research centers on autonomous driving systems where occlusions create safety risks. He develops risk-aware motion planning algorithms using sequential reasoning about hidden objects, vehicle-to-everything (V2X) communication, and foundation models to enhance decision-making in complex traffic. His work bridges theoretical robotics with industrial applications, emphasizing real-world safety specifications and uncertainty handling in urban and highway scenarios. Analysis of his publications reveals a clear trajectory from fundamental risk-aware planning (2021) to advanced occlusion reasoning using V2X (2024). His research consistently targets safety-critical gaps in autonomous driving, with growing emphasis on cooperative perception and language-integrated vision models. Key trends include formal safety guarantees, real-time contingency planning, and leveraging hidden object predictions for proactive vehicle control. Nyberg was funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP) during his doctoral studies. While no current student advising is documented, his industry-academia role at TRATON Group demonstrates strong collaboration between KTH and automotive manufacturing. His research directly addresses industrial challenges in commercial vehicle automation. As part of KTH's Robotics, Perception and Learning division, Nyberg contributes to Sweden's leading autonomous systems research environment. His work leverages state-of-the-art robotics labs and industry partnerships to translate academic innovation into practical solutions for next-generation autonomous vehicles.

Florian T. PokornyView profile

Associate Professor

• Robotics
• Machine Learning
• Artificial Intelligence
• +5 more

Florian T. Pokorny is an Associate Professor in Machine Learning at the Division of Robotics, Perception and Learning (RPL), Department of Electrical Engineering and Computer Science (EECS), KTH Royal Institute of Technology. He coordinates research projects such as the Horizon Europe-funded SoftEnable and the WASP-funded Intelligent Cloud Robotics for Real-Time Manipulation at Scale . His research focuses on data-driven methods for robotic manipulation, including transfer learning, cloud robotics, and caging-based manipulation of rigid and deformable objects. Education: PhD in Mathematics, University of Edinburgh (supervisor: Michael Singer) MSc in Advanced Study in Mathematics (Part III), University of Cambridge BSc in Mathematics, University of Edinburgh Research Interests: His work emphasizes scalable robotic manipulation, leveraging deep learning and geometric/topological methods. Key areas include training data requirements, transfer learning, and cloud robotics paradigms for manipulation at scale. Recent projects explore energy margin analysis, caging-guided morphology optimization, and robust policy learning. Publications: His recent work spans topics like caging-based manipulation, federated learning, and cloud robotics infrastructure. Notable contributions include CageCoOpt (manipulation robustness), CloudGripper (open-source testbed), and RealCraft (zero-shot video editing). Awards & Grants: Funded by WASP, Horizon Europe, and the Knut and Alice Wallenberg Foundation. His group hosts the CloudGripper platform and collaborates on benchmarks like DLO@Scale. Advising & Labs: Supervises multiple PhD students and research engineers. Alumni include Robert Gieselmann (Amazon Robotics), Yiannis Karayiannidis (Chalmers University), and Anastasiia Varava (Postdoc at KTH). Active in organizing workshops like RoDGE (IROS 2025) and ICRA 2025 robotics learning events.