Faculty Profile
Emily Hector, PhD
- Associate Professor, Biostatistics
Emily Hector is an associate professor in the Department of Biostatistics at the University
of Michigan. Emily’s work focuses on distributed estimation and inference and data
integration. She is particularly interested in applications to climate, neuroimaging
and electronic health records data. She received the NSF CAREER award in 2023, and
serves as an Associate Editor for Reproducibility at JASA.
- PhD, Biostatistics, University of Michigan, 2020
- MS, Biostatistics, University of Michigan, 2016
- BS, Honors Probability and Statistics, McGill University, 2014
Research Interests:
Correlated data, Divide-and-conquer, Distributed estimation and inference, Estimating equations, Generalized method of moments, Heterogeneous data integration, Parallel computing. Brain imaging analysis, Electronic Health Records data, Metabolomics, Spatial data, Wearable devices.
Research Projects:
Correlated data, Divide-and-conquer, Distributed estimation and inference, Estimating equations, Generalized method of moments, Heterogeneous data integration, Parallel computing. Brain imaging analysis, Electronic Health Records data, Metabolomics, Spatial data, Wearable devices.
Research Projects:
- NSF DMS 2337943 (2024-2029). CAREER: New data integration approaches for efficient
and robust meta-estimation, model fusion and transfer learning (PI Hector).
- NSF DMS 2152887 (2022-2025). Projecting flood frequency curves under a changing climate
using spatial extreme value analysis (PI Reich).
- NIH R01GM087964 (2022-2026). Development and Application of New Ionization Methods for Biological Mass Spectrometry (PI Muddiman).
G.A. Castiblanco-Rubio, E.C. Hector, J. Urena-Cirett, A. Cantoral, H. Hu, K.E. Peterson,
M.M. Tellez-Rojo, E.A. Martinez-Mier (2025). Dietary fluoride exposure during early
childhood and its association with dental fluorosis in a sample of Mexican adolescents.
International Journal of Environmental Research and Public Health. 22(5):689.
E.C. Hector and R. Martin (2024). Turning the information-sharing dial: efficient inference from different data sources. Electronic Journal of Statistics. 18(2):2974-3020.
E.R. Bruce*, R.R.Kibbe*, E.C. Hector, D.C. Muddiman (2024). Absolute Quantification of Glutathione using Top-Hat Optics for IR-MALDESI Mass Spectrometry Imaging. Journal of Mass Spectrometry. 59(10):e5091.
E.C. Hector and B.J. Reich (2024). Distributed inference for spatial extremes modeling in high dimensions. Journal of the American Statistical Association. 119(546):1297-1308.
E.C. Hector, L. Tang, L. Zhou, P.X.-K. Song (2024). Data integration and model fusion in the Bayesian and Frequentist frameworks. Handbook on Bayesian, Fiducial and Frequentist Inference. Chapter 11 (pp. 238-263). Chapman and Hall/CRC Press.
E.C. Hector and R. Martin (2024). Turning the information-sharing dial: efficient inference from different data sources. Electronic Journal of Statistics. 18(2):2974-3020.
E.R. Bruce*, R.R.Kibbe*, E.C. Hector, D.C. Muddiman (2024). Absolute Quantification of Glutathione using Top-Hat Optics for IR-MALDESI Mass Spectrometry Imaging. Journal of Mass Spectrometry. 59(10):e5091.
E.C. Hector and B.J. Reich (2024). Distributed inference for spatial extremes modeling in high dimensions. Journal of the American Statistical Association. 119(546):1297-1308.
E.C. Hector, L. Tang, L. Zhou, P.X.-K. Song (2024). Data integration and model fusion in the Bayesian and Frequentist frameworks. Handbook on Bayesian, Fiducial and Frequentist Inference. Chapter 11 (pp. 238-263). Chapman and Hall/CRC Press.
Room M4172 SPH II
1415 Washington Heights
Ann Arbor, MI 48109
Email: [email protected]
For media inquiries: [email protected]
1415 Washington Heights
Ann Arbor, MI 48109
Email: [email protected]
For media inquiries: [email protected]
Areas of Expertise: Biostatistics, Brain Disorders, Child Health, Environmental Health, Maternal Health, Nutrition, Precision Health, Sleep, Toxicology, Women’s Health