Lana Garmire

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.


Accomplishments and Awards

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.

Joshua Welch

Joshua Welch

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Our research aims to address fundamental problems in both biomedical research and computer science by developing new tools tailored to rapidly emerging single-cell omic technologies. Broadly, we seek to understand what genes define the complement of cell types and cell states within healthy tissue, how cells differentiate to their final fates, and how dysregulation of genes within specific cell types contributes to human disease. As computational method developers, we seek to both employ and advance the methods of machine learning, particularly for unsupervised analysis of high-dimensional data. We have particular expertise in manifold learning, matrix factorization, and deep learning approaches.


Accomplishments and Awards

Nancy Fleischer

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Dr. Fleischer’s research focuses on how the broader socioeconomic and policy environments impact health disparities and the health of vulnerable populations, in the U.S. and around the world. Through this research, her group employs various analytic techniques to examine data at multiple levels (country-level, state-level, and neighborhood-level), emphasizing the role of structural influences on individual health. Her group applies advanced epidemiologic, statistical, and econometric methods to this research, including survey methodology, longitudinal data analysis, hierarchical modeling, causal inference, systems science, and difference-in-difference analysis. Dr. Fleischer leads two NCI-funded projects focused on the impact of tobacco control policies on health equity in the U.S.

Robert Hampshire

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He develops and applies operations research, data science, and systems approaches to public and private service industries. His research focuses on the management and policy analysis of emerging networked industries and innovative mobility services such as smart parking, connected vehicles, autonomous vehicles, ride-hailing, bike sharing, and car sharing. He has worked extensively with both public and private sector partners worldwide. He is a queueing theorist that uses statistics, stochastic modeling, simulation and dynamic optimization.

Niccolò Meneghetti

Niccolò Meneghetti

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Dr. Niccolò Meneghetti is an Assistant Professor of Computer and Information Science at the University of Michigan-Dearborn.
His major research interests are in the broad area of database systems, with primary focus on probabilistic databases, statistical relational learning and uncertain data management.

Yajuan Si

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My research lies in cutting-edge methodology development in streams of Bayesian statistics, complex survey inference, missing data imputation, causal inference, and data confidentiality protection. I have extensive collaboration experiences with health services researchers and epidemiologists to improve healthcare and public health practice, and have been providing statistical support to solve sampling and analysis issues on health and social science surveys.

Karen Alofs

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My research focuses on how environmental change, including climate, invasion and habitat destruction influences freshwater ecological communities across space and time. I am involved in a collaborative interdisciplinary project funded by a MIDAS Propelling Original Data Science (PODS) Grant: CHANGES: Collections, Heterogeneous data, And Next Generation Ecological Studies.We are developing protocols for integrating heterogeneous natural science datasets to investigate the impacts of environmental changes on species. Our project focuses on climate change impacts on inland lake fish communities across Michigan, drawing on more than a century’s worth of data and specimens archived at the University of Michigan Museum of Zoology (UMMZ) and the Institute for Fisheries Research (IFR), which is a cooperative unit of the Michigan Department of Natural Resources (DNR) Fisheries Division and the University of Michigan.

Hernán López-Fernández

Hernán López-Fernández

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I am interested in the evolutionary processes that originate “mega-diverse” biotic assemblages and the role of ecology in shaping the evolution of diversity. My program studies the evolution of Neotropical freshwater fishes, the most diverse freshwater fish fauna on earth, with an estimate exceeding 7,000 species. My lab combines molecular phylogenetics and phylogeny-based comparative methods to integrate ecology, functional morphology, life histories and geography into analyses of macroevolutionary patterns of freshwater fish diversification. We are also comparing patterns of diversification across major Neotropical fish clades. Relying on fieldwork and natural history collections, we use methods that span