Dr. Chen Chen is a postdoctoral scholar at Scripps Institution of Oceanography at the University of California San Diego. Her research lies under three main areas: 1) applying causal inference and advanced methods in air pollution epidemiology, 2) incorporating considerations of social determinants of health into studies of environmental exposures, and 3) quantifying the health risks of emerging climate-related hazards and informing effective adaptation strategies. She is also interested in…
Yongsoo Choi is a Postdoctoral Associate at Yale University, working under the mentorship of Dr. Michelle Bell. His primary research interest is in exploring the varying patterns of health effects caused by air pollution across different times, regions, and populations. Furthermore, he is focused on identifying the causes behind these variations. His goal is to generate valid evidence that can help reduce the overall disease burden attributable to air pollution…
Dr. Choma is a Research Fellow in the Department of Environmental Health at the Harvard T.H. Chan School of Public Health. His research focuses on health risk assessment, with a primary interest in the use of risk assessment to inform policy decisions. Dr. Choma’s research has focused on fine particulate matter air pollution and on the health co-benefits of climate change mitigation, especially on the transportation sector, where he has…
George is the 2022 Wojcicki and Troper Postdoctoral Research Fellow of Harvard Data Science Initiative. He received a Ph.D. in Computer Science from the DaSciM group of LIX, École Polytechnique in Paris, France. He is working on machine learning for structured data with a special focus on graphs and generally non-Euclidean structures. His research is concentrated mainly on building powerful graph learning models, that are able to extract knowledge in…
Younsoo Jung is a research associate in the Department of Environmental Health at Harvard T.H Chan School of Public Health, mentored by Kari Neadu. Her research interests are quantifying the impact of climate change and understanding the vulnerable groups to improve health disparity and help better shape health policy. She completed her Ph.D. in Economics at the University of Iowa.Her dissertation focused on the impact of Medicaid expansion on vulnerable…
Heejun Shin is a fifth-year Ph.D. candidate in statistics at the University of Florida, under the mentorship of Joseph Antonelli. His research focuses on causal inference, Bayesian modeling, and treatment effect heterogeneity, particularly in the context of analyzing the health impacts of environmental exposures.
Mauricio Tec is a Ph.D. student in Statistics at the University of Texas at Austin. His main research interest is developing new AI and statistical methods for public policy, healthcare, and scientific applications. He considers major challenges like causality, sequential decisions, uncertainty quantification, and modeling complex structured data. Thus, he focuses mainly on deep and reinforcement learning, Bayesian statistics, and causal inference techniques. He believes that AI can revolutionize scientific…
Veronica Wang is a Post-doctoral Fellow who is interested in how environmental exposures influence health. She completed her Masters and Doctoral education in Environmental Health at Harvard T.H. Chan School of Public Health, where her work was primarily on the adverse effects of air pollution and solar activity in pregnant and elderly populations. Her current work focuses on respiratory outcomes in early childhood and Parkinson’s disease in the elderly.
Arpita Biswas is a CRCS Postdoctoral Fellow at the John A. Paulson School of Engineering and Applied Sciences, Harvard University. Her research focuses on Algorithmic Decision Making and Societal Impact, tackling fairness concerns, resource limitations, and robustness issues. Her broad areas of interest include Algorithmic Game Theory, Optimization, and Machine Learning. Her algorithmic contributions span across a wide range of problems, including fair resource allocation, fairness in machine learning, sequential…
Marissa Childs is a postdoctoral fellow through the Harvard University Center for the Environment mentored by Christopher Golden and Francesca Dominici. Her research broadly seeks to understand how environmental change affects human health by combing data from remote sensing and ground measurements with methods from disease ecology and causal inference. Her current postdoc research is part of the Madagascar Climate-Smart Public Health project. Marissa received her PhD from the Emmett…