جستجوی استاد راهنمای دانشگاهی

• Breast cancer screening
• Cervical cancer screening
• HPV vaccination
• +۵ مورد دیگر

George Napolitano is an Academic employee at the University of Copenhagen's Department of Public Health within the Section of Environmental Health. His work focuses on providing statistical support for various research projects in public health, with particular expertise in cancer screening programs and environmental health research. Dr. Napolitano holds a PhD in Mathematics from the Department of Mathematical Sciences and an MSc in Physics from the University of Naples Federico II. Prior to his current position, he worked as a Postdoc/Researcher at the Centre for Mathematical Sciences from 2013 to 2017, where he conducted research in Theoretical and Mathematical Physics and Applied Probability. His primary research interests include breast cancer screening, cervical cancer screening, HPV vaccination, and allostatic load. His expertise in statistical analysis bridges advanced mathematical methodologies with practical public health applications. Dr. Napolitano has published extensively, with 51 research outputs documented in his profile. His recent publications (2024-2025) demonstrate a strong focus on cervical cancer screening outcomes among HPV-vaccinated women through the Trial23 cohort study, breast cancer screening methodologies including tomosynthesis and deep learning approaches, and environmental health research examining air pollution's impact on lung cancer, respiratory infections, and COVID-19 mortality. His work consistently applies sophisticated statistical methods to address critical questions in epidemiology. Dr. Napolitano maintains an active research profile with multiple publications receiving significant attention from news outlets and academic platforms. His interdisciplinary background in theoretical physics and mathematics provides unique expertise in developing and applying complex statistical models to health data, making substantial contributions to cancer epidemiology and environmental health research.

• Actuarial Science
• Statistics
• Machine Learning
• +۲ مورد دیگر

Frederik Hytting Jørgensen serves as a Research Fellow at the Department of Mathematical Sciences, University of Copenhagen. His research spans critical domains in quantitative analysis: Actuarial Science with emphasis on fairness frameworks Statistical causal inference methodologies Machine learning ethics in insurance applications Risk modeling for insurability assessment Algorithmic bias mitigation techniques His 2024 publication in the European Actuarial Journal pioneers connections between plurality of perspectives, causal mechanisms, and insurability constraints, establishing foundational work for ethically robust actuarial models that balance technical precision with social responsibility in algorithmic decision-making systems.

• Computational Chemistry
• Cheminformatics
• Quantum Chemistry
• +۵ مورد دیگر

Maria Harris Rasmussen is a Postdoctoral Researcher in the Department of Chemistry at the University of Copenhagen, where she conducts cutting-edge research at the intersection of computational chemistry, cheminformatics, and artificial intelligence. Her work focuses on developing and applying computational methodologies to solve complex chemical problems, with particular emphasis on reaction discovery, molecular representation, and catalyst design. Her research interests span multiple domains of computational chemistry, with primary focus on Cheminformatics where she develops algorithms for molecular representation including SMILES notation for transition metal complexes. In Quantum Chemistry , she investigates photoinduced electron transfer processes and reaction mechanisms using advanced simulation techniques. Her work in Machine Learning for Chemistry includes developing explainable AI methods for molecular property prediction and uncertainty quantification in chemical data sets. She also contributes significantly to Catalysis Research through computational approaches for de novo catalyst discovery and reaction screening. Analysis of her publication record reveals strong trends in developing computational tools that bridge theoretical chemistry with practical applications. Her recent work shows increasing integration of machine learning with traditional quantum chemical methods, particularly in the areas of reaction space exploration and catalyst discovery. The interdisciplinary nature of her research connects chemistry with computer science, physics, and data science, reflecting the evolving landscape of modern computational chemistry. Maria maintains active research collaborations with prominent scientists including Jensen J.H., Mikkelsen K.V., and several international researchers as evidenced by her publication record. Her computational methodologies have gained attention across academic and research communities, with multiple publications receiving significant readership on platforms like Mendeley and social media engagement.

Karen-Inge Karstoftمشاهده پروفایل

دانشیار

• Clinical Psychology
• Health Psychology
• Trauma Psychology
• +۹ مورد دیگر

Karen-Inge Karstoft is an Associate Professor in the Department of Psychology at the University of Copenhagen's Faculty of Social Sciences. She joined the department in November 2020 after serving as a Senior Researcher at the Danish Veteran Centre's Research and Knowledge Centre. Her academic journey includes positions as an Affiliated Researcher and Part-time Lecturer at the University of Copenhagen, and Researcher and Part-time Lecturer at the University of Southern Denmark. Dr. Karstoft earned her PhD in Psychology from the University of Southern Denmark in 2014, with a dissertation on traumatic stress reactions following military deployment. She completed her MSc in Psychology with a focus on neuropsychology and clinical psychology from the University of Copenhagen in 2010, and her BSc in Psychology from the same institution in 2007. Her research program centers on clinical and health psychology with a specialization in trauma responses and PTSD development. She investigates how individuals react differently to trauma exposure and applies machine learning methods to predict mental health problems following trauma. Her work spans complexity science of psychopathology, comorbidity networks, veteran mental health, and refugee mental health. Dr. Karstoft's approach integrates advanced statistical methods with clinical applications to address mental health challenges in diverse populations. Her research has been published in high-impact journals including Nature Genetics, Nature Communications, and European Journal of Psychotraumatology. Recent work focuses on Ukrainian refugees, genetic architecture of PTSD, and therapeutic interventions. She has received significant recognition including the Young Investigator Award from The Danish Psychological Association in 2019. Young Investigator Award from The Danish Psychological Association (2019) Dr. Karstoft serves as Principal Investigator on multiple major grants including the DARECO cohort study, comorbidity networks research, and studies on adverse childhood experiences. She has secured funding from Carlsbergfondet and the Independent Research Fund Denmark totaling millions of Danish kroner. Her collaborative network includes partnerships with the Danish Veteran Centre and international research consortia. She teaches courses on trauma, PTSD, comorbidity diagnostics, research methods, and complexity science in clinical psychology.