جستجوی استاد راهنمای دانشگاهی

• Probability Theory
• Futurology
• Existential Risk
• +۴ مورد دیگر

Olle Häggström is a Professor of Mathematical Statistics at Chalmers University of Technology, specifically in the Department of Applied Mathematics and Statistics. His academic career spans several decades with a significant shift in research focus over time. Häggström's research interests have evolved from traditional probability theory to encompass broader future-oriented topics. Initially focused on mathematical statistics and probability theory, including percolation theory and stochastic processes, he has increasingly turned his attention to futurology, existential risk, and AI safety in recent years. His work demonstrates a unique interdisciplinary approach, bridging rigorous mathematical analysis with philosophical considerations about humanity's technological trajectory. The trends in Häggström's publications reveal a clear evolution from purely mathematical research toward interdisciplinary studies examining the societal implications of emerging technologies. His recent work focuses heavily on AI safety, existential risk assessment, and long-term futures thinking, while still maintaining connections to his mathematical foundations. This shift is evident in publications ranging from technical mathematical papers to broader philosophical discussions about technology's impact on civilization. Häggström has received research funding from notable sources including the FTX Foundation Future Fund for his project "Topics in the theory of xrisk and longtermism" (2022-2025), indicating recognition of the importance of his work in the existential risk community. His book "Here Be Dragons: Science, Technology and the Future of Humanity" (2016) represents a significant synthesis of his thinking on these topics. While specific details about his advising activities are not provided in the source material, his research projects suggest engagement with interdisciplinary teams working at the intersection of mathematics, computer science, and future studies. His work appears to influence both academic and policy discussions regarding technological risk and long-term planning.

• Legal Evidence
• Cognitive Bias in Legal Decision Making
• Bayesian Evidence Models
• +۳ مورد دیگر

Christian Dahlman is a Professor in the Department of Law at Lund University, serving as Research Coordinator for the Law, Evidence and Cognition (LEVIC) research group. His work focuses on legal evidence, cognitive biases in legal decision-making, and Bayesian models of evidence evaluation. He contributes to UN Sustainable Development Goals related to justice and governance. Dahlman is actively involved in interdisciplinary research at the intersection of law, psychology, and artificial intelligence. Research interests include probabilistic reasoning in legal contexts, cognitive biases affecting judicial fact-finding, and the application of Bayesian networks to forensic evidence analysis. His work critiques common legal fallacies and proposes methods to debias legal decision-making processes. Recent activities include organizing the NORTH SEA GROUP legal evidence seminars and delivering invited lectures on topics like 'Against Plausibility' (2024). He supervises doctoral research in areas such as decisional privacy and legal cognition. Dahlman's projects address preventing miscarriages of justice and improving evidence evaluation frameworks. He leads the long-running Law, Evidence and Cognition research initiative (2010–present) and has coordinated international collaborations across Europe. Dahlman's contributions span legal education, historical legal case analyses, and policy recommendations for judicial reform.

• Epidemiology
• Biostatistics
• Cancer Survival Analysis
• +۳ مورد دیگر

Paul Lambert is a Visiting Professor at the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, specializing in population-based cancer survival analysis and biostatistical modeling. His work focuses on flexible parametric models , competing risks , and multistate survival frameworks to address challenges in cancer prognosis and treatment effects. Key research areas: Epidemiology , Biostatistics , Cancer Survival Affiliation: Karolinska Institutet, Sweden His recent publications analyze Nordic cancer trends (2002-2021), cardio-oncology risks , and survival extrapolation in clinical trials. He supervises advanced statistical training and leads grants from the Swedish Research Council and Swedish Cancer Society. Scientific Awards : No explicit honors listed. Grants include projects on statistical methods for cancer registry data (Swedish Research Council, Swedish Cancer Society).

• Chronic Pain Management
• Epidemiology
• Biostatistics
• +۳ مورد دیگر

Anna Grimby Ekman is a Professor in Health Science Statistics at the School of Public Health and Community Medicine, University of Gothenburg. Her research focuses on chronic pain epidemiology, biostatistical methods, and predictive modeling in healthcare. She leads the GothPain research group and the Biostatistics research group, advancing interdisciplinary approaches to chronic pain management and statistical analysis. Education: She holds a PhD in Pain Epidemiology from the Sahlgrenska Academy (2010) and a licentiate thesis in statistical methodology (1997). Teaching includes biostatistics, epidemiology, and pain epidemiology courses at the University of Gothenburg since 1996. She actively supervises master's theses in Mathematical Statistics and medical degree projects. Research interests span chronic pain mechanisms, statistical techniques (e.g., causal inference, Bayesian methods), and translational studies linking biostatistics to clinical outcomes. Her work emphasizes predictive modeling for treatment efficacy and pain rehabilitation strategies. Advising involves leading postgraduate education and supervising projects in pain and biostatistics. Key collaborations include the GothPain network and national/international studies on musculoskeletal disorders, breast reconstruction outcomes, and stress-related health issues. Labs/Teams: Leads the GothPain Chronic Pain Research Group and the Biostatistics Group, fostering multidisciplinary collaboration in healthcare analytics and pain science.

Per Johanssonمشاهده پروفایل

استاد

• Causal Inference
• Econometrics
• Labor Economics
• +۷ مورد دیگر

Per Johansson is a Professor in the Department of Statistics at Uppsala University, Sweden, with a distinguished career spanning several decades in causal inference methodology and its applications to labor economics, health economics, and social policy evaluation. His research primarily utilizes Swedish administrative data to examine critical issues in social insurance systems, labor market behavior, and health outcomes. Professor Johansson's research interests center on causal inference methods broadly defined, with particular focus on applications in labor economics, health economics, and social policy. His work demonstrates methodological rigor while addressing socially relevant questions about sickness absence, disability insurance, retirement decisions, gender differences in labor markets, and the effectiveness of social interventions. He has developed innovative approaches to causal identification in observational settings and has contributed significantly to the methodological literature on experimental design and inference. His publication record reveals a clear trajectory from foundational methodological work in econometrics and statistics toward increasingly policy-relevant applications. While maintaining strong methodological contributions, particularly in causal inference and experimental design, his recent work shows greater emphasis on healthcare applications, comparative effectiveness research, and interdisciplinary collaborations with medical researchers. This evolution demonstrates his ability to apply sophisticated statistical methods to pressing real-world problems across multiple domains. Co-opted member of the Prize Committee for the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel Professor Johansson has secured numerous research grants supporting his work on causal methods and policy evaluation, with particular emphasis on Swedish social insurance systems. His research has been instrumental in evaluating interventions related to sickness absence, disability insurance, and retirement policies. He has collaborated extensively with researchers across disciplines and institutions, including economists, statisticians, epidemiologists, and medical researchers, reflecting the interdisciplinary nature of his work. His methodological innovations in causal inference, experimental design, and analysis of administrative data have established him as a leading researcher in applying sophisticated statistical methods to evaluate social policies and healthcare interventions using both experimental and observational data sources.

Michael Dunnمشاهده پروفایل

استاد

• Linguistic Typology
• Language Evolution
• Phylogenetics
• +۳ مورد دیگر

Michael Dunn is a Professor in General Linguistics at Uppsala University, where he has held his position since 2014. Affiliated with the Department of Linguistics and Philology, his work bridges theoretical linguistics with empirical research on language evolution and diversity, making significant contributions to multiple subfields within linguistic science. Professor Dunn's research focuses on the evolutionary dynamics of language change, with expertise spanning language description, linguistic typology, and phylogenetics. His scholarly work encompasses multiple language families including Indo-European, Dravidian, Uralic, and Chukotko-Kamchatkan languages. He employs interdisciplinary methodologies combining computational approaches, historical analysis, and fieldwork to investigate how languages evolve and diversify across time and space. His research has particularly emphasized the application of phylogenetic methods to linguistic data, examining grammatical structures, lexical borrowing patterns, and typological features across diverse language families. Analysis of his recent publications reveals a consistent scholarly trajectory centered on language evolution through phylogenetic frameworks. His work demonstrates sophisticated integration of computational methods with traditional linguistic analysis, particularly evident in studies of grammatical gender systems, politeness evolution in Indo-European languages, and borrowing profiles in basic vocabulary. The interdisciplinary nature of his research is reflected in publication venues spanning linguistics, evolutionary science, and digital humanities journals, indicating broad scholarly impact across multiple academic domains. Professor Dunn maintains an active research agenda with numerous collaborations across international institutions, as evidenced by his extensive co-authorship network. His work has been referenced across various academic platforms including Wikipedia pages, news outlets, and social media, demonstrating significant scholarly influence. While specific grant information isn't detailed in the available materials, his extensive publication record across high-impact journals suggests sustained research funding and institutional support for his linguistic investigations.

• Legal Evidence
• Cognitive Bias in Legal Decision Making
• Bayesian Evidence Models
• +۳ مورد دیگر

Christian Dahlman is a Professor at the Department of Law, Lund University. He also serves as a Research coordinator for Law, Evidence and Cognition (LEVIC) and a Researcher in Criminal Law. His primary affiliations include the Department of Law and L.E.V.I.C., with a focus on interdisciplinary legal research. His research interests center on Legal Evidence, Cognitive Bias in Legal Decision Making, and Bayesian Evidence Models. He explores how probabilistic reasoning impacts judicial processes, cognitive distortions in legal judgments, and quantitative approaches to evidence evaluation. His work aligns with UN Sustainable Development Goals related to justice systems. Recent research trends include analyses of probabilistic fallacies in legal reasoning, historical legal trials (e.g., Galileo's case), and miscarriages of justice prevention. He actively organizes workshops and seminars on legal evidence through the NORTH SEA GROUP series. Scientific Awards: None explicitly listed. He supervises projects like 'Privacy and Autonomy' (student M Bergström) and 'Karaktärsbevisning' (student M Bergius). Key grants include the 'Preventing Miscarriages of Justice' initiative (2023-2026) and L.E.V.I.C., an ongoing research hub since 2010. He collaborates internationally, evidenced by activities in the Netherlands and Germany. L.E.V.I.C. focuses on cognitive and empirical approaches to legal evidence, bridging law, psychology, and statistics. Current activities include mock trials and interdisciplinary legal training programs.

Antoine Honoréمشاهده پروفایل

پژوهشگر

• Predictive Modeling
• Clinical Informatics
• Machine Learning
• +۴ مورد دیگر

Antoine Honoré is a Researcher (Postdoc) at KTH Royal Institute of Technology, working in the Division of Information Science and Engineering. He collaborates with Prof. Ming Xiao at KTH and Prof. Volker Lauschke at Karolinska Institutet's Department of Physiology and Pharmacology. His research focuses on developing predictive models for clinical contexts, emphasizing generalizability, calibration, and implementation of deep learning architectures. Key projects include graph-based models for genetic variant analysis in drug transporter proteins, advancing personalized medicine. Education: He holds a PhD from KTH Royal Institute of Technology under Assoc. Prof. Saikat Chatterjee and Prof. Eric Herlenius at Karolinska Institutet, with a thesis on deep learning for neonatal sepsis detection. His work bridges signal processing, machine learning, and clinical informatics. Research Interests: Predictive modeling in healthcare, machine learning applications in neonatal sepsis detection, pharmacogenomics, and integration of clinical data sources. He has pioneered LSTM and HMM-based models for vital sign analysis, contributing to early sepsis identification in preterm infants. Publications: Over 15 peer-reviewed articles, including work on DANSE algorithms (IEEE Transactions on Signal Processing), neonatal sepsis detection (Acta Paediatrica), and pharmacogenomic variant prediction (2025). His research spans signal processing, generative models, and clinical decision support systems. Labs/Teams: Active in Prof. Ming Xiao's research group at KTH and collaborates with Karolinska Institutet's Physiology and Pharmacology department. His work integrates AI with healthcare systems to improve clinical outcomes through data-driven approaches.

Oskar Kvimanمشاهده پروفایل

پژوهشگر

• Bayesian phylogenetics
• Probabilistic machine learning
• Variational inference
• +۱۵ مورد دیگر

Oskar Kviman is a doctoral student at KTH Royal Institute of Technology working in the Lagergren Lab within the Division of Computational Science and Technology. His research bridges machine learning, statistics, and computational biology with a focus on developing and applying advanced probabilistic methods. His primary research interests include: Bayesian phylogenetics and probabilistic machine learning Variational inference, variational auto-encoders, and sequential Monte Carlo methods Generative AI techniques including flow matching, Schrödinger bridges, and diffusion models Computational cancer research focusing on differential expression testing and spatial transcriptomics Kviman's publication record demonstrates significant contributions to variational inference methodology, particularly in phylogenetics and generative modeling. His work spans top machine learning conferences including ICML, NeurIPS, and AISTATS, showing consistent development of techniques that improve efficiency and accuracy in probabilistic modeling. Recent publications focus on multi-marginal flow matching, variational resampling, and mixture learning in black-box variational inference. He has been recognized for his peer review contributions as a Top reviewer (10%) for AISTATS 2023. Kviman has supervised master's theses for Xindi Liu and Ricky Molén at KTH and serves as a lecturer for 'Statistical Methods in Applied Computer Science' since 2021, while previously working as a teaching assistant for 'Machine Learning, Advanced Course' and 'Deep Learning, Advanced Course'.

Lilianne Eningerمشاهده پروفایل

دانشیار

• Developmental Psychology
• Child Development
• Social Emotional Competence
• +۳ مورد دیگر

Lilianne Eninger serves as Associate Professor and Deputy Head of Department at Stockholm University's Department of Psychology within the Faculty of Social Sciences. She is an active researcher specializing in developmental psychology with a particular focus on child development and social emotional competence in educational contexts. Her work spans cross-cultural comparisons, intervention development, and assessment methodologies. Dr. Eninger's research primarily centers on social emotional competence in children, early childhood education interventions, and the cultural adaptation of developmental programs. Her work demonstrates particular expertise in the Promoting Alternative Thinking Strategies (PATHS) program and its implementation in Swedish preschool contexts. She investigates how socioeconomic factors, neighborhood conditions, and cultural contexts influence child development outcomes and intervention effectiveness, with significant contributions to understanding cross-cultural measurement invariance. Analysis of Dr. Eninger's recent publications reveals a strong focus on social emotional learning in preschool settings, with particular attention to cultural adaptation of interventions across different contexts. Her work spans methodological advancements in assessment tools, neighborhood effects on development, and the implementation of evidence-based programs in educational settings. The research demonstrates consistent application of rigorous quantitative methods including structural equation modeling and cluster randomized trials. Dr. Eninger leads and participates in multiple research projects including Parent Web - support for families with adolescents, Internet based parent training in Arab, Farsi and Dari, and Supporting positive youth development. As Deputy Head of Department, she contributes to academic leadership while maintaining an active research agenda focused on practical applications of developmental science.

Ullrika Sahlinمشاهده پروفایل

مدرس ارشد

• Uncertainty Quantification
• Risk Assessment
• Environmental Decision Making
• +۴ مورد دیگر

Ullrika Sahlin is a Senior Lecturer at Lund University, affiliated with the Centre for Environmental and Climate Science (CEC), BECC (Biodiversity and Ecosystem services in a Changing Climate), and MERGE (ModElling the Regional and Global Earth system), with additional roles in Computational Science for Health and Environment. Her research focuses on characterizing and communicating uncertainty in scientific models and assessments to inform decision-making processes under uncertainty. Her expertise spans uncertainty quantification, risk assessment, Bayesian analysis, and environmental decision-making, applied to critical areas including invasive species management, food safety, ecosystem services valuation, and climate change impacts. She actively contributes to UN Sustainable Development Goals through interdisciplinary work integrating probability theory, computational science, and evidence-based environmental modeling. Recent publications (2024-2025) reveal strong thematic consistency in advancing adverse outcome pathway methodologies, hybrid uncertainty elicitation techniques, and ecological assessment frameworks. These works demonstrate systematic integration of statistical rigor with environmental applications, particularly in toxicology risk assessment and climate-driven ecosystem modeling. Scientific recognition includes: Richard J. Burk Outstanding Service Award (2016) Dr. Sahlin leads substantial research funding including QBSF (Quantitative Biodiversity Science for Finance, 2024-2029), IPPM (Pollinator Pesticide Mitigation, 2024-2026), and BeeSYNC (Climate-Driven Pollination Synchrony, 2024-2028), with supervision of 5 graduate students. Her 43 recorded activities demonstrate extensive engagement in conference organization (e.g., The Risk and Uncertainty Conference 2024) and expert consultations. As a core member of CEC and BECC networks, she drives collaborative research on climate-biodiversity interactions through computational modeling approaches, with ongoing projects addressing pollinator declines, chemical risk assessment, and financial applications of biodiversity science.

Richard Dawidمشاهده پروفایل

استاد

• Philosophy of Science
• Philosophy of Physics
• High Energy Physics
• +۵ مورد دیگر

Richard Dawid is Professor of Philosophy of Science at Stockholm University's Department of Philosophy. He holds a PhD in theoretical physics from the University of Vienna and transitioned from physics to philosophy in 2000. Before joining Stockholm University in 2016, he worked as a philosopher of science at the University of Vienna and the MCMP Munich after previously working as a physicist at TU Munich and the Lawrence Berkeley Laboratory. Dawid earned his PhD in theoretical physics from the University of Vienna, which established the foundation for his unique interdisciplinary approach. His educational background bridges the physical sciences and philosophy, creating a distinctive perspective on fundamental physics questions. Dawid's research focuses on philosophical aspects of contemporary theories in high energy physics and cosmology. He is renowned for developing the concept of non-empirical theory confirmation, detailed in his book "String Theory and the Scientific Method" (Cambridge University Press, 2013). His work spans Everettian quantum mechanics, data analysis in high energy physics, string dualities, cosmological multiverse, anthropic reasoning, Bayesian confirmation theory, and scientific realism debates. He approaches these topics with a methodology that challenges traditional boundaries between empirical and non-empirical reasoning in science. Analysis of Dawid's recent publications reveals a consistent focus on meta-empirical theory assessment across diverse domains of fundamental physics. His work increasingly explores the philosophical implications of quantum mechanics interpretations, particularly the Everettian (many-worlds) approach, and examines the boundaries of scientific methodology where empirical testing faces significant constraints. There's a clear trajectory toward integrating historical perspectives with contemporary philosophical analysis of physics, demonstrating how past scientific developments inform current theoretical challenges. Dawid currently leads a VR-funded (Swedish Research Council) research project on the philosophy of cosmology. His ongoing projects "Non-empirical Theory Confirmation in Fundamental Physics" and "Theory succession and finality claims in fundamental physics" investigate the significance of non-empirical reasoning in fundamental physics and explore claims about final theories in contemporary physics. These projects examine how theoretical virtues and meta-empirical considerations can provide significant support for theories even in the absence of direct empirical evidence, particularly in contexts like string theory and cosmology where experimental verification remains challenging.

• Healthcare Logistics
• Operations Research
• Healthcare System Optimization
• +۶ مورد دیگر

Sebastiaan Meijer is a Professor of Health Care Logistics at KTH Royal Institute of Technology. His research focuses on applying logistics principles to healthcare systems, particularly in optimizing resource allocation, patient flow, and integrating technology like sensor data and simulations. He leads a team developing gaming simulations and interactive methods to improve healthcare efficiency, with a focus on smart cities and elderly care. Key areas include home health monitoring platforms, emergency department logistics, and medical waste management. His work addresses challenges in coordinating complex healthcare networks across institutions. Research Interests: Healthcare Logistics Simulation Modeling Patient Flow Optimization Telemedicine Reablement Programs for Older Adults Medical Waste Transportation Recent Articles: Focus on real-world evidence gaps in clinical trials, hospital overcrowding diagnostics, and hybrid modeling for complex systems. These studies highlight interdisciplinary approaches combining data science, simulation, and healthcare policy. Awards: Not explicitly mentioned in provided texts. Advising & Grants: Supervises 16+ students (listed in 'students'). Research projects include the ASSIST reablement program feasibility study and telemedicine evaluation in surgical settings. Labs/Teams: Leads a multidisciplinary team at KTH addressing healthcare logistics challenges through simulation games and data-driven methods.