Marie O’Neill

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My research interests include health effects of air pollution, temperature extremes and climate change (mortality, asthma, hospital admissions, birth outcomes and cardiovascular endpoints); environmental exposure assessment; and socio-economic influences on health.
Data science tools and methodologies include geographic information systems and spatio-temporal analysis, epidemiologic study design and data management.

Carina Gronlund

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As an environmental epidemiologist and in collaboration with government and community partners, I study how social, economic, health, and built environment characteristics and/or air quality affect vulnerability to extreme heat and extreme precipitation. This research will help cities understand how to adapt to heat, heat waves, higher pollen levels, and heavy rainfall in a changing climate.

Kevin Bakker

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Kevin’s research is focused on to identifying and interpreting the mechanisms responsible for the complex dynamics we observe in ecological and epidemiological systems using data science and modeling approaches. He is primarily interested in emerging and endemic pathogens, such as SARS-CoV-2, influenza, vampire bat rabies, and a host of childhood infectious diseases such as chickenpox. He uses statistical and mechanistic models to fit, forecast, and occasionally back-cast expected disease dynamics under a host of conditions, such as vaccination or other control mechanisms.

Andrew Brouwer

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Andrew uses mathematical and statistical modeling to address public health problems. As a mathematical epidemiologist, he works on a wide range of topics (mostly related to infectious diseases and cancer prevention and survival) using an array of computational and statistical tools, including mechanistic differential equations and multistate stochastic processes. Rigorous consideration of parameter identifiability, parameter estimation, and uncertainty quantification are underlying themes in Andrew’s work.

Rajiv Saran

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Dr. Saran is an internationally recognized expert in kidney disease research – specifically, in the area of kidney disease surveillance and epidemiology. From 2014 – 2019, he served as Director of the United States Renal Data System (USRDS; www.usrds.org), a ‘gold standard’ for kidney disease data systems, worldwide. Since 2006 he has been Co-Principal Investigator for the Centers for the Disease Control and Prevention’s (CDC’s) National CKD Surveillance System for the US, a one of a kind project that complements the USRDS, while focusing on upstream surveillance of CKD and its risk factors (www.cdc.org/ckd/surveillance). Both projects have influenced policy related to kidney disease in the US and were cited extensively in the July 2019 Advancing American Kidney Health Federal policy document. Dr. Saran led the development of the first National Kidney Disease Information System (VA-REINS), for the Department of Veterans Affairs (VA), funded by the VA’s Center for Innovation, and one that led to the VA recognizing the importance of kidney disease as a health priority for US veterans. Dr. Saran has recently (2018-2021) been funded on a spin off project from VA REINS for investigation of ‘hot-spot’ of kidney disease among US Veterans involving both risk-prediction and geospatial analyses – a modern approach to health system big data being used for prevention and population health improvement, using kidney disease as an example. This approach has broad application for prevention and optimizing management of major chronic diseases.

Bogdan I. Epureanu

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• Computational dynamics focused on nonlinear dynamics and finite elements (e.g., a new approach for forecasting bifurcations/tipping points in aeroelastic and ecological systems, new finite element methods for thin walled beams that leads to novel reduced order models).
• Modeling nonlinear phenomena and mechano-chemical processes in molecular motor dynamics, such as motor proteins, toward early detection of neurodegenerative diseases.
• Computational methods for robotics, manufacturing, modeling multi-body dynamics, developed methods for identifying limit cycle oscillations in large-dimensional (fluid) systems.
• Turbomachinery and aeroelasticity providing a better understanding of fundamental complex fluid dynamics and cutting-edge models for predicting, identifying and characterizing the response of blisks and flade systems through integrated experimental & computational approaches.
• Structural health monitoring & sensing providing increased sensibility / capabilities by the discovery, characterization and exploitation of sensitivity vector fields, smart system interrogation through nonlinear feedback excitation, nonlinear minimal rank perturbation and system augmentation, pattern recognition for attractors, damage detection using bifurcation morphing.

Lana Garmire

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My research interest lies in applying data science for actionable transformation of human health from the bench to bedside. Current research focus areas include cutting edge single-cell sequencing informatics and genomics; precision medicine through integration of multi-omics data types; novel modeling and computational methods for biomarker research; public health genomics. I apply my biomedical informatics and analytical expertise to study diseases such as cancers, as well the impact of pregnancy/early life complications on later life diseases.

Xu Shi

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My methodological research focus on developing statistical methods for routinely collected healthcare databases such as electronic health records (EHR) and claims data. I aim to tackle the unique challenges that arise from the secondary use of real-world data for research purposes. Specifically, I develop novel causal inference methods and semiparametric efficiency theory that harness the full potential of EHR data to address comparative effectiveness and safety questions. I develop scalable and automated pipelines for curation and harmonization of EHR data across healthcare systems and coding systems.

Evan Keller

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Our laboratory focuses on (1) the biology of cancer metastasis, especially bone metastasis, including the role of the host microenvironment; and (2) mechanisms of chemoresistance. We explore for genes that regulate metastasis and the interaction between the host microenvironment and cancer cells. We are performing single cell multiomics and spatial analysis to enable us to identify rare cell populations and promote precision medicine. Our research methodology uses a combination of molecular, cellular, and animal studies. The majority of our work is highly translational to provide clinical relevance to our work. In terms of data science, we collaborate on applications of both established and novel methodologies to analyze high dimensional; deconvolution of high dimensional data into a cellular and tissue context; spatial mapping of multiomic data; and heterogenous data integration.

Laura Power

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I am an infectious disease and preventive medicine physician and my interests include studying the epidemiology of communicable diseases and and the practice of public health. I’m a clinical assistant professor in the Department of Epidemiology at the School of Public Health and in the Division of Infectious Diseases at the Medical School. My work also focuses on connecting physicians to public health practice; I serve as the Program Director for the Preventive Medicine Residency and I lead a certificate program in population health and health equity for physicians in training. I’m also an associate editor for the American Journal of Preventive Medicine. My research focuses on the epidemiology and prevention of infectious disease, including communicable diseases in the broader public health setting.