جست‌وجوی استاد و پژوهشگر

Julia Höglundمشاهده پروفایل

پژوهشگر

• Genetic Variation
• Evolutionary Biology
• Genomic Sequence Annotation
• +۵ مورد دیگر

Julia Höglund is a Postdoctoral Researcher based at the Centre for Palaeogenetics, affiliated with the Department of Zoology at Stockholm University and collaborating with Wageningen University and Research. Her primary research focuses on genomic sequence annotation, mutational load quantification, and the role of genetic variation in evolution and disease. She works on endangered species like the arctic fox and extinct species such as the woolly mammoth. BSc in Biology, Lund University (2012-2015) MSc in Biology, Lund University (2015-2017) MSc in Bioinformatics, Lund University (2015-2017) PhD in Medical Sciences (Statistical Genetics), Uppsala University (2018-2022) Her research spans genetic epidemiology , inflammatory disease mechanisms , and conservation genomics , with expertise in whole-genome sequencing, polygenic risk scores, and evolutionary adaptation studies. Key projects include developing the FlyCADD model for variant scoring, analyzing estradiol's genetic impact on cancer, and exploring owl vision genetics. Recent publications reveal trends in inflammatory disease genetics (2019-2022), variant annotation (2025), and conservation genomics (2017-2019). Her work bridges computational biology, statistical genetics, and evolutionary applications. No scientific awards are explicitly mentioned in the available text. Julia works jointly with Dr. Mirte Bosse at Wageningen University and Research, focusing on genomic models for endangered and extinct species. Her lab affiliations include the Centre for Palaeogenetics and Stockholm University's Department of Zoology.

Erik Lindstromمشاهده پروفایل

استاد

• Financial Mathematics
• Statistical Inference
• Stochastic Processes
• +۲ مورد دیگر

Erik Lindstrom is a Professor of Mathematical Statistics and Head of Division at Lund University's Centre for Mathematical Sciences within the Faculty of Science. He additionally serves as assistant Director for the Industrial Engineering and Management program and directs the statistical consulting service for the Science faculty. His educational background includes: M.Sc. in Engineering Physics (2000) from Lund University B.Sc. in Economics and Business (2000) from Lund University M.Sc. in Economics and Business (2001) from Lund University Ph.D. in Mathematical Statistics (2004) from Lund University Lindstrom's research bridges theoretical statistics with real-world applications in finance and energy systems. His work focuses on parameter estimation algorithms for discretely observed diffusion processes, financial mathematics including option valuation under uncertainty, energy finance, power system stability, and statistical testing methodologies. The 2015 book "Statistics for Finance" synthesizes key aspects of his financial statistics research. Recent publications (2023-2025) reveal a concentrated research trajectory applying statistical jump models to cryptocurrency markets and financial options, alongside advanced time series techniques for building energy load forecasting. This demonstrates his consistent interdisciplinary approach connecting stochastic processes with practical financial and energy sector challenges. His scientific recognition includes: Excellent Teaching Practitioner (ETP) award (2013) Lindstrom actively mentors doctoral researchers including current PhD students Carl Åkerlindh and Peter Nystrup, and postdoctoral fellows Josef Höök and Sidi Mohamed Aly. His teaching portfolio spans Financial Statistics (MSc), Non-linear Time Series (MSc/PhD), and Statistical Inference for Partially Observed Stochastic Processes (PhD), supported by research grants in financial mathematics and energy applications. As head of division and director of the statistical consulting service, he leads initiatives providing statistical methodology support across the Science faculty, fostering cross-disciplinary research collaboration through structured consultation frameworks.

• Cognitive Psychology
• Judgment and Decision Making
• Probability Judgment
• +۵ مورد دیگر

Peter Juslin is a Professor at Uppsala University, affiliated with the Department of Psychology and the Division of Perception and Cognitive Psychology. His research focuses on cognitive psychology, judgment, and decision-making, particularly on phenomena like overconfidence, the naivety of intuitive statistics, and additive probability integration. He collaborates with interdisciplinary teams across psychology, law, and energy systems. PhD in Psychology (1993), Uppsala University Bachelor of Arts (1989) in Psychology and Philosophy, Uppsala University His research explores how humans make probability judgments, the role of similarity-based processes, and applications to real-world domains like legal decision-making and energy consumption. He critiques traditional heuristics-and-biases approaches, proposing instead that naive sampling models explain judgment errors more effectively. Recent work examines cognitive processes in demand response, environmental psychology, and associative models in probability estimation. Key themes include cognitive constraints, sequential decision-making, and the interplay between intuitive and analytic reasoning. Scientific awards include the Torgny Segerstedt Medal (2008), Oscar Award (1998), and New Scientist Award (1994). He was elected to the Royal Swedish Academy of Sciences in 2013. He teaches advanced courses in cognitive psychology, supervises students at all levels, and engages in public science through articles and lectures to governmental agencies.

Ronnie Pingelمشاهده پروفایل

مدرس ارشد

• Causal Inference
• Biostatistics
• Public Health
• +۳ مورد دیگر

Ronnie Pingel serves as a Senior Lecturer at Uppsala University's Department of Statistics within the Faculty of Social Sciences, while also maintaining an associated researcher position at the Department of Public Health and Caring Sciences (General Practice division) in the Faculty of Medicine. With dual appointments spanning statistical methodology and public health applications, Pingel bridges quantitative theory with population health research. Ronnie Pingel's research spans causal inference methodology, biostatistics, and public health applications. Primary interests include propensity score-based estimators for causal effects, mental health epidemiology (particularly adolescent male psychosocial health), cardiovascular outcomes research, and diabetes/cardiovascular disease epidemiology. Recent work demonstrates expertise in longitudinal study designs, registry-based analyses, and methodological validation of statistical approaches in real-world health data. Analysis of Pingel's 15 most recent publications reveals consistent focus on causal inference methods applied to public health questions, with particular emphasis on mental health trajectories, cardiovascular outcomes, and adolescent health behaviors. The work frequently employs Swedish registry data and demonstrates methodological rigor in handling observational data through propensity scoring, decomposition analysis, and structural equation modeling. Pingel maintains active collaborations across Uppsala University's medical and statistical departments, with frequent co-authorship on interdisciplinary projects involving the SWEDEHEART registry, pregnancy cohort studies, and adolescent health surveys. Current research involves ongoing work with the SUPRIM trial (psychological interventions in coronary disease) and PhysCan trial (exercise during cancer treatment).

David Seimمشاهده پروفایل

استاد

• Labor Economics
• Public Economics
• Wealth Taxation
• +۵ مورد دیگر

David Seim is a Professor in the Department of Economics at Stockholm University, with his workplace located in Room A660 at Universitetsvägen 10 A. His contact information includes email david.seim@su.se and phone number 08-16 35 39. Professor Seim's research focuses on labor economics and public economics, with particular expertise in Swedish economic policy. His work examines wealth taxation systems, employment protection legislation, income mobility patterns, and intergenerational transmission of economic beliefs and outcomes. He has conducted extensive research on how notice periods affect job transitions, the impacts of eliminating employment protection for older workers, and the relationship between inheritances and wealth inequality in Sweden. His recent publications demonstrate a consistent focus on empirical economic analysis of Swedish policy, with a blend of theoretical modeling and data-driven research. The articles reveal a strong emphasis on labor market dynamics, taxation policy, and the psychological factors influencing economic behavior and policy preferences. His work often bridges microeconomic theory with practical policy applications in the Swedish context. While specific scientific awards are not documented in the available information, Professor Seim's substantial publication record in high-impact economic research demonstrates significant scholarly contribution to the field. His work appears frequently in economic journals and policy reports, suggesting recognition within the academic community. As a professor at Stockholm University, Professor Seim likely supervises graduate students and contributes to the academic development of economics students, though specific details about his advisees are not available in the current documentation. His research agenda appears well-funded through standard academic channels that support economic research in Sweden.

Erik Schaffernichtمشاهده پروفایل

مدرس ارشد

• Robotics
• Sensor Systems
• Machine Learning
• +۶ مورد دیگر

Erik Schaffernicht serves as a Senior Lecturer in the Department of Natural Sciences and Technology at Örebro University's School of Science and Technology. His research is primarily conducted through the Center for Applied Autonomous Sensor Systems (AASS) where he leads work in the Adaptive and Interpretable Learning Systems and Robot Navigation and Perception research groups. Dr. Schaffernicht's research spans multiple areas in robotics and artificial intelligence, with particular expertise in sensor systems, behavior trees, and gas distribution mapping. His work bridges theoretical computer science with practical applications in autonomous systems, environmental monitoring, and human-robot interaction. His research often involves developing novel algorithms for robot perception, control, and decision-making in complex environments. His recent publications demonstrate a strong focus on behavior trees for robot control, gas distribution mapping techniques, and applications of machine learning in robotics. The research shows increasing sophistication in using deep learning approaches for environmental sensing and robot navigation, with applications ranging from industrial safety to healthcare monitoring. Dr. Schaffernicht maintains an active research agenda with numerous publications in top robotics and AI venues, including IEEE Robotics and Automation Letters, Robotics and Autonomous Systems, and various IEEE conference proceedings. His work shows consistent collaboration with researchers across Europe, particularly with the AASS research center at Örebro University. His research projects include both ongoing work on automatic cognitive screening tests using eye-tracking technology and completed projects such as AIR (Action and Intention Recognition), RAISE (Robotic System for Air Quality Assessment), and SmokeBot (Mobile Robots for Disaster Site Inspection).

Håkan Nilssonمشاهده پروفایل

دانشیار

• Cognitive Psychology
• Decision Making
• Probability Judgment
• +۴ مورد دیگر

Håkan Nilsson is a Senior Lecturer/Associate Professor at the Department of Psychology, Uppsala University, specializing in Perception and Cognition. His research focuses on cognitive psychology, decision making, and probability judgment with significant contributions to understanding human reasoning under uncertainty. His primary research interests include: Cognitive biases in probability judgment, particularly the conjunction fallacy How people interpret odds in sports betting contexts Mathematical modeling of decision processes (configural weighted average model) The relationship between numerical ability and decision quality Development of debiasing techniques for probabilistic reasoning Analysis of his recent publications reveals consistent focus on understanding probability judgment mechanisms. His work demonstrates that even numerically skilled individuals remain susceptible to decision paradoxes, suggesting deep-rooted cognitive processes. Notable research areas include how betting odds are converted to probability estimates and why combo bets appear more attractive despite lower probabilities. His scientific contributions encompass: Development of the configural weighted average model for probability judgment Studies on the relationship between numerical ability and susceptibility to decision paradoxes Research on the cognitive substrate of subjective probability Exploration of how monetary incentives affect probability assessment Nilsson has maintained extensive collaborations with Peter Juslin, Anders Winman, and Patric Andersson. His work appears in leading journals including Psychological Review, Journal of Experimental Psychology, and Cognition, demonstrating significant impact in cognitive and decision sciences.