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Post-Doctoral Associates

People

  • Visiting Fellow

    Dr. Esen is a postdoctoral researcher from the Department of Clinical Epidemiology (DCE) at Aarhus University in Denmark. She is currently undertaking a two-year research stay at the Yale School of Public Health (YSPH). Dr. Esen holds a Master's degree in statistics and a PhD in health sciences from Aarhus University. Her research focuses on data management, data analysis, and statistical and epidemiological methods, with a particular emphasis on causal inference methods and pharmacoepidemiology. Her current research involves developing algorithms for target trial emulation. She has been involved in numerous national and international research projects, demonstrating a strong track record of collaboration. This includes working with researchers at Stanford University and the Karolinska Institute, as well as contributing to large-scale international initiatives such as the Nordic Pregnancy Drug Safety Study (NorPreSS). Her work has been recognized through publications in high-impact journals. She was awarded the Best Flash Talk Prize in 2020 and the prestigious Tove Nilsson Research Prize in 2024 for significant contributions to the field of epidemiology.
  • Environmental Health Sciences

    Associate Research Scientist in Epidemiology (Environmental Health)

    Exposomics covers the interaction between environmental exposures, including from contaminants, diet, and drugs, with biological consequences. My specific interests within exposomics are to develop mass spectral and informatics approaches to more comprehensively characterize both the exposome (exogenous compounds) and endogenous (biological) molecules. I am also interested in the interaction between exogenous compounds and endogenous compounds which can lead to novel compounds, for example DNA adducts, small molecule adducts, and oxidation products. As oxidation products are a nearly universal indication of biological stress, developing tools to improve the coverage of oxidized molecules will aid in numerous applications. Through my future research, I aim to develop techniques that more comprehensively covering molecules which are indicative of our exposures and biological response, allowing researchers to determine mechanisms and markers linking health and the environment. Ideally, the research and mentoring during my career will result in changes in policy and education, and development of new treatments, which will reduce harmful exposures and their consequences. Current focuses include PFAS software development, exposome monitoring using passive sampling and non-targeted mass spectrometry software solutions, and lipidomics.
  • Postdoctoral Associate

    Yuanhang Yang is a Postdoctoral Associate at Yale School of Public Health. His research focuses on the safety of medication use during pregnancy and its potential effects on infant health, with a particular interest in women with autoimmune diseases. He uses large healthcare databases, including MarketScan, Cosmos, and the Danish National Birth Cohort, to generate real-world evidence on medication safety and inform clinical decision-making. Before joining Yale, Yuanhang earned his PhD in Epidemiology from Karolinska Institute in Stockholm, Sweden. His doctoral research focused on autoimmune diseases, particularly inflammatory bowel disease (IBD), and their associations with adverse kidney outcomes.
  • Postdoctoral Associate

    Haoran is a postdoctoral associate in the Department of Environmental Health Sciences. Her research interests center around the understanding of how environmental and social factors during critical periods of early life development may affect the risk of health conditions in pregnancy complications, neonatal outcomes, and childhood neurodevelopment. She has particular interest in the application of novels study designs in the epidemiological research. With backgrounds of environmental science and engineering in her undergraduate study, Haoran is also interested in exposure related research like chemical mixtures and geospatial analysis.