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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.

Jonas Hultin RosenbergView profile

Associate Professor

• Political Philosophy
• Political Sociology
• Democratic Inclusion
• +4 more

Jonas Hultin Rosenberg is an Associate Professor of Political Science at Mälardalen University's School of Business, Society and Engineering (Division of Economy and Political Science). He holds a PhD from Uppsala University (2017) and was appointed docent (associate professor) there in 2023. His research focuses on political philosophy, political sociology, and the intersection of AI with democratic systems. Current roles include Guest Researcher at Uppsala University's Centre for Multidisciplinary Research on Religion and Society (CRS) and associate editor of Philosophy & Technology . Research interests emphasize democratic inclusion criteria, political equality, AI's societal impact, and citizenship. Key themes include justification of democracy, voter turnout among marginalized groups (notably people with intellectual disabilities), and the ethical implications of algorithmic governance. His work bridges normative theory with empirical analysis, addressing questions like 'Who should be included in democratic processes?' and 'How does technology reshape political legitimacy?' Publications since 2012 reflect a trajectory from foundational democratic theory to contemporary challenges posed by AI and disability inclusion. Recent work explores AI's potential as both a disruptor and enabler of democratic values, alongside reinterpreting classical principles like the 'all-affected' criterion in modern contexts. He employs mixed methods, including conjoint experiments and longitudinal data analysis. Professional service includes editorial work for peer-reviewed journals and advisory roles in multidisciplinary research centers. Current projects likely continue investigating AI's socio-political dimensions and expanding inclusion frameworks to non-human actors (e.g., nature, AI systems).

• Infection Medicine
• Immunology
• Coagulation
• +5 more

Praveen Papareddy is an Associate Professor in Infection Medicine at Lund University (BMC). His research focuses on host defense mechanisms against infections, coagulation pathways, and systemic inflammation. He investigates antimicrobial peptides, innate immunity, and the interplay between inflammation and infectious diseases. His work contributes to UN Sustainable Development Goals related to health and well-being. He leads the project 'Consumption of antithrombin in patients suffering from severe COVID-19-infections' (2020–present), exploring coagulation disorders in critical illness. Collaborations span institutions globally, including studies on bacterial sepsis, thrombin-derived peptides, and inflammatory biomarkers. Expertise: Innate immunity, coagulation, antimicrobial peptides, sepsis Key Projects: Antithrombin in severe infections, nitroxoline repurposing His research highlights include discovering factor XII's role in trapping bacterial infections and elucidating serum amyloid A proteins' dual roles in inflammation. Articles emphasize translational potential for novel therapeutics in infection and cancer.

• Breast cancer research
• Translational oncology
• Molecular analyses of tumor tissue
• +7 more

Theodoros Foukakis serves as Associate Professor and Senior Physician at Karolinska Institutet's Department of Oncology-Pathology in Stockholm, Sweden. He leads the Translational Breast Cancer Research Group, a multidisciplinary team comprising clinicians, bioinformaticians, epidemiologists, biostatisticians, AI engineers, and molecular biologists. His research focuses on understanding treatment resistance mechanisms in breast cancer through molecular analyses of tumor tissue and blood samples, with the goal of developing new predictive biomarkers for treatment response. Foukakis' research interests center on translational breast cancer research, particularly in the areas of neoadjuvant therapy, treatment resistance mechanisms, and biomarker development. His work spans both HER2-positive and triple-negative breast cancer subtypes, with significant contributions to clinical trials investigating novel treatment approaches including immunotherapy combinations and antibody-drug conjugates. He has pioneered research in applying machine learning and AI techniques to analyze tumor microenvironment characteristics and optimize treatment selection based on molecular profiles. His work bridges clinical practice with cutting-edge genomic and computational approaches to personalize breast cancer treatment. Analysis of his recent publications (2024-2025) reveals a strong focus on precision oncology approaches, with particular emphasis on biomarker development, treatment response prediction, and optimizing therapeutic strategies through AI applications. His work spans clinical trials (PANTHER, KEYNOTE, ARIADNE), biomarker discovery (SAMHD1, immune microenvironment characterization), and implementation of machine learning models for treatment optimization. A significant portion of his research addresses the critical challenge of balancing treatment efficacy with minimizing toxicity through tailored approaches. Foukakis actively mentors doctoral students and postdoctoral researchers in his translational breast cancer research group. His grant portfolio includes leadership of the ARIADNE trial, a randomized phase IIB study investigating trastuzumab deruxtecan and biology-driven selection of neoadjuvant treatment for HER2-positive breast cancer. His research has been supported by multiple national and international funding sources focused on advancing precision medicine in breast cancer care. The Translational Breast Cancer Research Group led by Foukakis operates as a comprehensive research ecosystem that integrates clinical data with molecular and computational analyses. The group collaborates extensively with other research teams at Karolinska Institutet and participates in numerous international clinical trials. Their work on the ARIADNE study represents a novel approach to treatment selection based on intrinsic molecular subtypes as determined by Prosigna® analysis, potentially enabling both treatment de-escalation for some patients and escalation for others based on molecular characteristics.

Petter EricsonView profile

Researcher

• Responsible AI
• Graph Theory
• Formal Grammars
• +4 more

Petter Ericson is a Researcher at the Department of Computer Science , Umeå University , specializing in Responsible AI . His work bridges graph theory , formal grammars , and ethics , with interdisciplinary interests in music and sociotechnical systems . Affiliated with the Responsible AI Research Group , he explores the alignment of AI with human values. Ericson’s research spans formal computational models , including hyperedge replacement grammars and order-preserving DAGs , alongside AI ethics and fairness frameworks . His publications address sociotechnical limits in AI safety, artistic shifts through AI, and graph language learnability. He has contributed to interdisciplinary projects like Concordia , a musical XR instrument for planetary data sonification, and Musereduce , a hierarchical music analysis framework. Ericson applies computational methods to Bayesian music theory and jazz harmony datasets.

Mattias EkstedtView profile

Assistant Professor

• Fatty Liver Disease
• Medical Education
• Cardiovascular Disease
• +5 more

Mattias Ekstedt is an Assistant Professor at Linköping University's Department of Health, Medicine and Care (HMV), Faculty of Medicine. As a Senior Physician and Docent in Gastroenterology and Hepatology, his work focuses on improving fatty liver disease diagnostics and patient quality of life through innovative techniques. Medical Degree (2003) PhD (2008) Specialist in Internal Medicine (2011) Docent in Gastroenterology (2020) Ekstedt leads research on metabolic dysfunction-associated steatotic liver disease (MASLD) and its cardiovascular links, co-supervising 15+ doctoral students. His projects include DETECT-HCC-ESLD (non-invasive liver cancer detection), EPSOMiP (epicardial fat and diabetes), and ACCESS (muscle degeneration prediction). He founded the Research Network for Studies of Ectopic Fat Storage and serves in organizations like the Gastrointestinal Foundation and EASL International Liver Foundation. Recent publications emphasize non-invasive diagnostics, proteomic biomarkers, and MASLD's systemic implications. Awards include the 2013 STINT Scholarship for teaching excellence and Educator of the Year 2015. Ekstedt actively develops medical education through MEQ exams, OSCE, and digital teaching frameworks.

• Digitalization
• eGovernment
• Cultural Policy
• +5 more

Katarina L Gidlund is a Professor at the Department of Communication, Quality Technology and Information Systems (KKI) at Mid Sweden University. She leads the Forum for Digitalization (FODI) and has extensive research in digitalization, eGovernment, and cultural policy. Department of Communication, Quality Technology and Information Systems (KKI) Forum for Digitalization (FODI) Her research focuses on digitalization challenges in public sector, including value realization, policy enactment, and critical analysis of digital practices. She examines how digitalization reshapes institutions, professions, and citizen-state relationships. Recent publications analyze government technology narratives (2025), digital participation frameworks (2023), and critical perspectives on cultural policy in Sweden (2023). Her work spans digital governance, epistemic tensions in policy implementation, and reflexive design methodologies. She collaborates with researchers like Sundberg, Nyhlén, and Lindell on topics including journalistic autonomy (2024), digital maturity in manufacturing (2019), and theoretical frameworks for eGovernment research (2008-2022). As an editor, she contributed to "Det akademiska arbetets villkor - villkorat akademiskt arbete (AVA)" (2025) and other anthologies focusing on university collaboration and governance.

Jeroen van der LaakView profile

Visiting Professor

• Computational Pathology
• Deep Learning
• Medical Image Analysis
• +5 more

Jeroen van der Laak is a Visiting Professor at Linköping University's Faculty of Medicine, affiliated with the Department of Health, Medicine and Care (HMV) and the Department of Diagnostics and Specialist Medicine (DISP). He is a key member of the Computational Pathology Group and contributes to the Wallenberg Centre for Molecular Medicine (WCMM), focusing on advancing digital pathology through artificial intelligence and deep learning methodologies. Dr. van der Laak's research centers on computational pathology, with specific expertise in developing deep learning algorithms to improve cancer diagnostics and prognosis. His work spans multiple domains including histopathological image analysis, tumor detection, biomarker identification, and computer-aided diagnosis systems. He investigates how machine learning techniques can enhance pathologist efficiency while reducing observer bias and identifying novel prognostic indicators for personalized cancer treatment. His research addresses critical challenges in computational pathology, including the need for high-quality, large-scale histopathological datasets and clinical validation of AI models. Analysis of Dr. van der Laak's recent publications reveals a strong focus on applying deep learning to diverse pathology challenges across multiple organ systems. His work demonstrates expertise in whole-slide image analysis, tumor segmentation, cancer grading, and biomarker discovery. Notably, his research spans breast cancer, prostate cancer, colorectal cancer, kidney transplant pathology, and gynecological pathology, showing both depth in specific applications and breadth across medical specialties. Key themes include attention-based image compression, human-in-the-loop refinement of AI models, and automated lesion scoring systems. Dr. van der Laak actively collaborates with international pathologists and participates in major European initiatives like the BIGPICTURE project, which aims to build an EU-scale digital pathology repository. His research emphasizes clinical validation of AI models to ensure safety and utility in routine practice, with contributions to consensus studies including recommendations for diagnosing serous tubal intraepithelial carcinoma (STIC) and standardization of molecular pathology education. As part of the Computational Pathology Group, Dr. van der Laak contributes to developing, validating, and deploying novel medical image analysis methods based on deep learning technology, with a focus on computer-aided diagnosis systems that directly support pathologists in their daily work while identifying potential new biomarkers for individualized treatment approaches.

Cormac McGrathView profile

Senior Lecturer

• Higher Education
• Educational Change
• Academic Development
• +7 more

Cormac McGrath is a Senior Lecturer in the Department of Education at Stockholm University, where he is affiliated with the Higher Education Learning Practices (HELP) research group. His academic journey began with training as a secondary school teacher in English and Philosophy, followed by work with teacher training at Harvard School of Education's Project Zero. He later served as an Educational Developer at Karolinska Institutet (KI) while completing his doctoral thesis on change practice and agency in higher education. McGrath's research spans multiple interconnected domains within higher education. His early work focused on educational change, collegial leadership, and academic development, as evidenced by publications like 'The Ebb and Flow of Educational Change' and 'Change in a Culture of Collegiality and Consensus-Seeking.' More recently, his research has evolved to address cutting-edge issues in educational technology, particularly the integration of artificial intelligence in teaching and learning environments. His work on MOOCs, virtual patients in medical education, and learning analytics demonstrates his commitment to innovative educational practices. An analysis of McGrath's recent publications reveals a clear trajectory toward examining the ethical and practical implications of AI in education. His 2024-2025 work focuses extensively on AI literacy in teacher education, responsible AI implementation, assessment practices in the age of generative AI, and privacy concerns in educational technologies. This research agenda reflects his position at the forefront of addressing how emerging technologies reshape educational landscapes while maintaining ethical standards. McGrath has been actively involved in several significant research projects, including 'Demystifying AI literacy in teacher training programmes,' 'AI literacy for Swedish Teacher Education,' and 'Ethical and Legal Challenges in Relationship to AI-driven practices in higher education.' His work often takes an interdisciplinary approach, connecting educational theory with practical applications across medical education, law, public health, and general higher education contexts. As an academic developer and researcher, McGrath has made substantial contributions to understanding how educational change occurs within university settings, with particular attention to the role of academic developers as brokers of change. His work bridges theoretical frameworks with practical implementation strategies, making his research valuable to both scholars and practitioners in the field of higher education.

• Climate Change
• Atmosphere-Climate System Interactions
• Arctic Warming
• +4 more

Hans Chen is an Assistant Professor in Geoscience and Remote Sensing at Chalmers University of Technology, Sweden. His research focuses on the interactions between the atmosphere and other components of the climate system, with particular emphasis on climate change and variability, Arctic warming and mid-latitude weather patterns, terrestrial carbon cycle dynamics, and observation-based estimation of greenhouse gas emissions. Dr. Chen's research interests span multiple critical areas of climate science. His work on Arctic warming investigates the connections between declining sea ice and changing weather patterns in mid-latitudes. He also studies terrestrial carbon cycle dynamics, examining how vegetation responds to climate variability and how these responses feed back into the climate system. A significant portion of his research involves developing methods for monitoring human emissions of carbon dioxide using satellite observations, which has important implications for climate policy and emissions verification. Dr. Chen leads several significant research projects including 'Unveiling the impacts of vapor pressure deficit on forest productivity (VAPOR)' (2024-2025), 'Arctic carbon cycle dynamics' (2024-2026), and 'Monitoring anthropogenic carbon dioxide emissions from space' (2023-2025). He is also a key participant in the long-running 'ModElling the Regional and Global Earth system (MERGE)' project that began in 2010. His scientific contributions span interdisciplinary research connecting atmospheric science, climate modeling, remote sensing, and environmental policy. Analysis of his recent publications reveals a strong focus on Arctic climate processes, carbon cycle dynamics, and the development of satellite-based monitoring techniques for greenhouse gases. His work frequently employs advanced statistical methods, machine learning approaches, and data assimilation techniques to extract meaningful insights from complex climate datasets. Dr. Chen collaborates with researchers across Europe and internationally, working with funding from organizations including the European Commission, Hasselblad Foundation, and the Swedish National Space Board. His research has practical applications for climate monitoring, emissions verification, and understanding the complex feedbacks within the Earth's climate system.

Carl-Johan StenbergView profile

Researcher

• Artificial Intelligence Literacy
• Digital Education
• Teacher Training
• +2 more

Carl-Johan Stenberg is a doctoral student at Linköping University, affiliated with the Department of Behavioral Sciences and Learning (IBL) and Department of Learning, Aesthetics and Natural Sciences (LEN). His work focuses on AI literacy and didactics in teacher education, examining how artificial intelligence can reshape pedagogical practices while addressing associated challenges. His research explores critical questions about: AI literacy requirements for educators Algorithmic teaching methods Digital transformation in education Ethical implications of AI in classrooms Technology-mediated learning environments Key publications include studies on: AI integration in teacher education (2025) Digital competence frameworks (2024) Educational philosophy in AI contexts (2025) He contributes to the WASP-HS research network and participates in practical educational research activities in Norrköping, Sweden.

Line HenriksenView profile

Lecturer

• Monster Theory
• Hauntology
• Creative Writing
• +4 more

Line Henriksen is a Lecturer in Literature and Creative Writing at Malmö University's Faculty of Culture and Society, Department of Art, Culture and Communication. She holds a PhD in Gender Research from Linköping University and is affiliated with the MEDEA Lab and The Monster Lab research groups. Her research explores: Monster theory and cultural representations of horror Hauntology and temporal studies Creative writing as methodological practice Digital ethics and bot communication Feminist posthumanism and speculative fiction Through artistic research approaches, she examines intersections of gender, technology, and cultural narratives. Recent publications demonstrate interdisciplinary engagement across gender studies, digital humanities, and literary theory, with consistent focus on ethical dimensions of human/non-human relationships. Her 2024 co-authored book examines feminist reconceptualizations of alien encounters. At MEDEA Lab, she contributes to multidisciplinary projects addressing societal challenges through experimental media approaches. Her work with The Monster Lab investigates cultural manifestations of monstrosity in contemporary media landscapes.

• Cardiology
• Myocardial Infarction
• Cardiac Biomarkers
• +5 more

Bertil Lindahl is a Professor in the Department of Medical Sciences, specializing in Cardiology at Uppsala University, with additional affiliation at the UCR-Uppsala Clinical Research Center. His research focuses on myocardial infarction, cardiac biomarkers, non-obstructive coronary artery disease, and cardiovascular outcomes research. He maintains active clinical and research responsibilities with contact information listed for both institutional locations. His research interests span several critical areas of modern cardiology including the diagnosis and classification of myocardial infarction, cardiac biomarker applications (particularly troponin), non-obstructive coronary artery disease (MINOCA), secondary prevention strategies, and cardiovascular outcomes research. His work heavily utilizes the SWEDEHEART registry, a Swedish national quality registry for coronary artery disease that enables large-scale epidemiological and clinical studies. Analysis of his recent publications reveals a strong focus on refining diagnostic criteria for myocardial infarction, understanding prognostic implications of various cardiac conditions, evaluating treatment effectiveness in real-world settings, and investigating the relationship between biomarkers and clinical outcomes. His research has significant implications for clinical practice guidelines and patient management strategies in cardiology. Lindahl has received recognition through numerous publications in high-impact journals including the New England Journal of Medicine, European Heart Journal, Journal of the American College of Cardiology, and Circulation. His work demonstrates strong national and international collaborations with researchers across multiple disciplines within cardiovascular medicine. His research portfolio includes clinical trials, registry-based studies, diagnostic evaluations, and methodological research. Current projects appear to focus on refining myocardial infarction classification systems, evaluating secondary prevention strategies, investigating biomarker applications, and studying special populations such as women with cardiovascular disease and patients with non-obstructive coronary artery disease.

• Computer Science Education
• Educational Technology
• Artificial Intelligence in Education
• +3 more

Calkin Suero Montero serves as Senior Lecturer at Uppsala University's Department of Information Technology, affiliated with the Vi3 and Computing Education Research groups. His position bridges theoretical computer science and practical educational innovation within Sweden's higher education landscape. Research focuses critically on technology-mediated learning environments, particularly generative AI applications in K-12 informatics education, mixed reality remote instruction, and programming pedagogy. His work examines cognitive, social, and technical dimensions of student engagement through empirical studies involving teachers and learners across diverse educational contexts. Methodologically, he employs qualitative frameworks to investigate how emerging technologies reshape classroom dynamics and knowledge construction. Current publication trends reveal concentrated exploration of AI's disruptive impact on traditional CS education paradigms, with significant attention to ethical implementation challenges and contextual adaptation requirements. His blended learning models specifically address mathematics instruction while cross-disciplinary collaborations extend into special education domains like autism-inclusive storytelling. As core faculty within Uppsala's computing education ecosystem, he contributes to the Vi3 research group's mission of developing human-centered technological solutions while advancing the university's strategic focus on digital transformation in pedagogy.

• Vascular Surgery
• Abdominal Aortic Aneurysm Screening
• Trauma Surgery
• +2 more

Knut Thorbjörnsen serves as an Affiliated Researcher at the Center for Clinical Research, Gävleborg and as a Physician specializing in Vascular Surgery within the Department of Surgical Sciences at Uppsala University. His dual clinical-research roles bridge academic medicine and regional healthcare delivery across Gävle and Uppsala facilities. His research focuses on vascular disease management with particular expertise in abdominal aortic aneurysm (AAA) screening programs, subaneurysmal aortic conditions, and trauma triage systems. Key interests include: Natural history of screen-detected aortic pathologies Cost-effectiveness of AAA screening in elderly populations Innovative endovascular repair techniques for vascular infections Validation of national trauma activation criteria Long-term outcomes of vascular interventions Analysis of his publication record reveals consistent contributions to vascular surgery literature, particularly through longitudinal studies of Swedish national screening programs. His work demonstrates methodological rigor in population-based cohort studies and clinical evaluations of emerging surgical techniques, with strong emphasis on practical clinical applications and public health implications. While no formal advising roles or student listings appear in available records, his collaborative publication patterns suggest active mentorship within vascular surgery research teams. His institutional affiliations with Uppsala University's surgical department and Gävleborg's clinical research center provide robust infrastructure for translational vascular research.