Dr. Francesca Dominici is the Clarence James Gamble Professor of Biostatistics, Population and Data Science at the Harvard T.H. Chan School of Public Health and Director of the Harvard Data Science Initiative at Harvard University.  She is a member of the National Academy of Medicine and of the International Society of Mathematical Statistics. In 2024, she was named by TIME100 Health as one of the most influential scientists in global health in the world. Before being appointed founding Director of the Harvard Data Science Initiative, she was Senior Associate Dean for Research at the Harvard TH Chan School of Public Health. Dr. Dominici is also the founder and lead Principal Investigator (PI) for the National Studies on Air Pollution and Health Group (NSAPH), as well as a co-founding PI and leader for the BUSPH-HSPH Climate Change and Health Research Coordinating Center, CAFÉ.
 
Dr. Dominici’s research has focused on machine learning, Artificial Intelligence, causal inference, and data science to impact climate and environmental policy.   Her air pollution studies have directly and routinely impacted air quality policy, leading to more stringent ambient air quality standards in the U.S. Her work has been covered by the New York Times, the Los Angeles Times, the BBC, the Guardian, CNN, and NPR.  
 
Among her most recent awards, Dr. Dominici has been recognized as the Mosteller Statistician of the Year by the Boston Chapter of the American Stati…

Danielle Braun is a Principal Research scientist in the Biostatistics Department at the Harvard T.H. Chan School of Public Health and at the Department of Data Science at Dana-Farber Cancer Institute. Her areas of research include risk prediction, genetic epidemiology, measurement error, survival analysis, frailty models, clinical tool development, causal inference, and environmental health. As a Principal Research Scientist Danielle co-leads the BayesMendel lab and is Director of Data Science for Environmental and Climate Health in the NSAPH group.

Catherine Adcock is the Program Coordinator at the National Studies on Air Pollution and Health lab as well as the Harvard Data Science Initiative. She provides administrative support to NSAPH, the HDSI, Harvard Data Science Review, and to Dr. Francesca Dominici in her roles of faculty director of the HDSI and Professor of Biostatistics. Catherine graduated from Capital University with a BA in History.

Prof. Michelle Bell is an environmental epidemiologist at Yale University in the School of the Environment.

Falco is an Assistant Professor in the Department of Biostatistics at the University of California, Los Angeles (UCLA) and a visiting scientist at Harvard University.

His research interests are primarily in methodological and applied (bio)statistics with a focus on applications of causal inference and artificial intelligence in public health and medicine.

Up-to-date news on his work can be found at: https://www.falcobargaglistoffi.com/
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Salvador is a PhD Student affiliated with NSAPH and advised by Nima Hejazi. He works on nonparametric causal inference under network interference.

Heather McBrien is a 2nd year PhD student in the Environmental Health Sciences department at the Columbia Mailman School of Public Health. Her research uses large datasets and novel methods to evaluate the impacts of population-level climate-related exposures, including climate-related disasters. Her current projects evaluate the impacts of wildfire smoke and wildfire disaster exposure on perinatal health outcomes, and the impacts of power outage and co-occurring disaster exposure on vulnerable groups. Her interests include environmental and research justice, reproducibility, and research that informs climate policy.

Sophie is a PhD student in Biostatistics working with Dr. Francesca Dominici. Her dissertation work focuses on unifying and extending methods to address unmeasured spatial confounding in causal inference.

Michael Cork is a PhD candidate in Biostatistics, where he conducts research at the intersection of causal inference, environmental health, and air pollution policy. His work focuses on developing data science methods to estimate the health impacts of environmental exposures and support cleaner, healthier communities. Prior to his doctoral studies, Michael worked in a global health setting, where he developed geospatial models to improve HIV prevalence prediction in low- and middle-income countries.

Giacomo De Nicola is a postdoctoral fellow at the Harvard T.H. Chan School of Public Health, under the joint mentorship of Christopher Golden and Francesca Dominici. His research broadly seeks to design, implement and leverage modern statistical tools to address real-world problems, with a focus on applications in public and planetary health. His current postdoc research is part of the Climate-Smart Public Health project, where he aims at understanding and measuring the impact of climate and climate change on health outcomes. Giacomo holds a PhD in Statistics from LMU Munich, an MSc in Economic and Social Sciences from Bocconi University, and a BSc in Statistics from the University of Florence, where he received the best student award for graduating top of his class. His research on assessing excess mortality during crises earned him a special award from the Federal Statistical Office of Germany.

Shuxin is a PhD student in Population Health Sciences program with a focus on environmental epidemiology at Harvard.

Tinashe is a Programmer on the NSAPH Data Science team and Research Software Engineer for the Golden Lab Planetary Health Research Group. He started in February, 2025.

From 2018 to 2022, Tinashe was a neuroimaging data analyst at the Penn Lifespan Informatics and Neuroimaging Center, where he developed various software and programming tools to process, curate, and analyze neuroimaging data. In the role, Tinashe gained his expertise in developing robust, reproducible, and scalable data preprocessing pipelines, using technologies like Python, R, bash, and docker. Tinashe earned his Accelerated BSMS in Psychology from Drexel University. Mentored by Fengqing Zhang of the Quantitative Psychology & Statisics Lab, Tinashe defended his Master’s thesis, “Advanced Data Mining Models for Psychological and Behavioral Research,” in 2018. In addition to his work in psychology, Tinashe has experience as a data scientist in People Analytics, where he worked on NLP and text mining solutions geared to improve employee success, and as a data scientist in Real World Oncology Data (RWD) at ConcertAI, where he developed dashboards for pharmacovigilence of Adverse Events related to cancer treatment exposure.

Tinashe is an advocate for the growing importance of the Research Software Engineer role in the scientific arena. He holds a mentorship position in the official Data Science Learning Community, and is staff writer on the US chapter of the Research Software Engineers Asso…

Lauren Mock is a biostatistician with the NSAPH group. She researches the effects of heat and air pollution exposures on a variety of health outcomes, including neurodegenerative diseases, heat-related illness, and mortality, with a particular focus on treatment effect heterogeneity. Lauren holds a BA in Earth & Environmental Science and an SM in Biostatistics.

Sophie-An is a junior at Harvard College studying Environmental Engineering and Economics. She joined NSAPH in 2023 and studies how air pollution affects intergenerational economic mobility among low income American children.

Kevin is a Postdoctoral Research Fellow in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. His research areas include causal inference, observational studies, treatment interference, policy evaluation, environmental health, and time series analysis.

Trang Bui is a postdoctoral associate at University of Rochester. She started working with NSAPH since July, 2024. Her research interests are experimental design, network analysis, causal inference and AI validation and monitoring.

Dr. Choma is a Research Scientist at 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 benefits of emission controls, especially on the transportation sector, where he has assessed health benefits achieved by past regulation and new technologies, such as vehicle electrification and automation. He is also currently working to quantify the health benefits that can be achieved by reducing urban heat islands in the United States, and on new epidemiologic studies assessing the health effects of environmental radiation, including ambient particulate matter radioactivity. He has participated in several international efforts to improve the quantification of the health effects of fine particulate matter in life cycle assessment and other emission reduction and policy analyses. Dr. Choma’s research has been covered by The Associated Press, The New York Times, ABC News, The Washington Post, Popular Science, USA TODAY, The Hill, Newsweek, and other national and international news outlets.

Dr. Choma received his Ph.D. in Population Health Sciences from Harvard University, where he specialized in Risk and Decision Sciences, within the Environmental Health field of study. He is from Brazil and previously received an …

Veronica is a Research Associate at the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. Her research focuses on modeling missing data mechanisms across a range of applications, from survey statistics to causal inference. She is particularly interested in the use of Bayesian inference to address complex problems in biostatistics. Currently, she works on the formalization and implementation of models for causal analysis in clinical and environmental studies.

Mahima Kaur is a Programmer in the NSAPH Data Science team. She joined in July 2024 and contributes to developing reproducible and scalable data preprocessing pipelines using open science tools such as Python, R, and SQL. Her work supports large-scale public health research, particularly in analyzing Medicare data and environmental exposures. Mahima holds a Master’s degree in Health Informatics from Yale University and brings a strong foundation in programming, data analytics, and health data science to her role.

Heejun is a Postdoctoral Research Fellow at NSAPH, having started in June 2024. He completed his Ph.D. in Statistics at the University of Florida under the supervision of Dr. Joseph Antonelli.

James is a PhD student in Biostatistics working with Dr. Francesca Dominici. His research focuses on integrating biostatistical principles—such as causal inference and uncertainty quantification—with artificial intelligence (AI) techniques. Before beginning his doctoral studies, James earned an AB in Statistics from Harvard College, where he conducted research in evolutionary genetics and competed on the Varsity Nordic Skiing team.

Veronica is a second-year postdoctoral fellow as part of NSAPH who studies the association between environmental exposures and hospitalizations with neurological diseases in the Medicare population.

Claudio Battiloro is a Postdoctoral fellow at the Harvard T.H. Chan School of Public Health and a former Visiting Associate at the SEAS of the University of Pennsylvania. He received a M.Sc. cum laude in Data Science and a Ph.D. cum laude in Information and Communication Technologies from Sapienza University of Rome. Claudio’s research interests include theory and methods for topological signal processing and deep learning-fields in which he has several pioneering contributions-, distributed stochastic optimization, and (broadly) AI for Healthy Climate Adaptation. He has over 35 publications, including papers published in top-tier journals (e.g., Journal of Machine Learning Research, IEEE Transactions on Signal Processing, IEEE Transactions on IoT and IEEE Transaction on Green Communications and Networking) and conferences (e.g. ICLR, ICML,ICASSP, and IJCNN). Claudio received different awards, such as the IEEE SPS Italian Chapter Best M.Sc. Thesis Award (2020), the GTTI Best Ph.D. Thesis Award (2024), and the “Elio Di Claudio” award for the best Ph.D. Thesis in ICT in 2024.

Federica is a Postdoctoral Research Fellow at NSAPH, having started in June 2024. Her research focuses on evaluating the effects of pollutant exposure on various health outcomes.

Raphael is a 4th year Biostatistics PhD Candidate working on policy learning and causal inference problems.

Jonathan Gilmour is a Data Scientist at the Harvard T.H. Chan School of Public Health. His work focuses on human health impacts of climate change and the environmental impacts of AI and data centers. He is also leading federal data and informational resource preservation work with the Public Environmental Data Partners and tracking the impacts of federal policy changes at The Impact Project. He previously was a Science and Technology Policy Fellow at the Aspen Policy Academy, an advisor to the Rockefeller Foundation’s Pandemic Prevention Initiative, and a Data Infrastructure Engineer at The COVID Tracking Project at The Atlantic. He graduated from Grinnell College in 2019 with a B.A. in Computer Science.

Scott Delaney, ScD JD MPH, is an epidemiologist at the Harvard T.H. Chan School of Public Health. His research seeks to identify ways that environmental, social, and legal factors interact to affect health outcomes with the aim of creating better, more equitable healthcare systems. Currently, Dr. Delaney is exploring how these factors exacerbate effects of climate change on brain health, including Alzheimer’s Disease and Parkinson’s Disease.

Dr. Delaney is also an attorney. He holds degrees from Harvard (ScD), Johns Hopkins (MPH), and the University of Illinois (JD, BS in corporate finance and valuation).

Ahmet is pursuing his Master’s degree in Computer Science at ETH Zurich, where he focuses on causal inference, generative models, and theoretical computer science. He has previously worked on the analysis of various k-means algorithm variants. For his master’s thesis, he is visiting the Harvard Data Science Initiative (HDSI), working on leveraging generative models to scale causal inference methods to high-dimensional settings.

Grace Yang is a rising junior at Harvard College, double concentrating in Statistics and Economics. She is originally from Carmel, Indiana, and she enjoys applying data science and quantitative methods to problems at the intersection of economics, health, and social justice. Her research experience spans many fields, including bioinformatics, economic policy, and criminal justice reform.

Eric is a sophomore at Harvard College planning on studying Statistics. He loves probability, and in his free time, he enjoys playing all types of games and solving puzzles.

Ricky is a junior at Harvard College studying Statistics and Mathematics. He joined NSAPH in 2025 and is interested in applying data science and causal inference to air pollution.