Hi, I'm Margaret!
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I am a PhD Candidate in Biostatistics at the University of Michigan. My research focuses on Accelerometry Data, particularly developing new methods to analyze Physical Activity and Sleep Data in free-living populations.
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An East Coast transplant, I have lived in Ann Arbor now since 2015 - and love it (Go Blue!) Outside of working, I enjoy hiking, bookstores, coffee shops, and visiting my family.
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Education
PhD Candidate
University of Michigan
After beginning the PhD program in Fall of 2017, I achieved candidacy in May 2018
MS in Biostatistics
University of Michigan
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I completed my Masters Degree in Biostatistics in May 2017
BS/BA in Math and Economics
Villanova University
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I completed my undergraduate education in May 2011
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Research and Experience
Graduate Method Research
University of Michigan, 2016- present
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My dissertation research focuses on method development for analyzing Accelerometer Data, both in terms of Physical Activity and Sleep. I joined the Peter Song Lab as well as the ELEMENT (Early Life Exposures in Mexico to ENvironmental Toxicants) group for this dissertation research. I have shared my work at ENAR and JSM poster presentations in 2019 and 2018.
Graduate Applied Research
University of Michigan, 2016 - present
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From 2016 to present I have worked with the Early Life Exposures in Mexico to ENvironmental Toxicants (ELEMENT) group, which is a cohort birth study in Mexico City spanning two decades and three generations. With this group I work on wide-range of data, including:
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Metabolomics Data
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Accelerometer Data
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Toxicant Exposure Data
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Cognitive Neuro Data
Graduate Teaching Experience
University of Michigan, 2015
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In 2016 I was a Graduate Student Instructor (GSI) for the undergraduate Statistics course (Stat 250) taught within the University of Michigan.
Financial Analyst
GE Healthcare, 2012-2015
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Prior to returning to graduate school, I worked as a Financial Analyst with GE Healthcare.
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I began as part of the Financial Management Program (FMP), which is a two-year rotational leadership program with concentrations in Controllership, Financial Planning & Analysis, Corporate Strategy and Operational Efficiency; the program combines 4 intensive job assignments with demanding coursework in finance and accounting.
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Upon completing the FMP program, I accepted a position as a Global Supply Chain FP&A Analyst
Publications
Journal Publications
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​Baek, J., Banker, M., Jansen, E. C., She, X., Peterson, K. E., Pitchford, E. A., and Song, P. X. K.,“An Efficient Segmentation Algorithm to Estimate Sleep Duration from Actigraphy Data,”en, Statistics in Biosciences, vol. 13, no. 3, pp. 563–583, Dec. 2021, ISSN: 1867-1772.
Recognized as a 2022 Statistics in Biosciences Best Paper Award
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He, X., Banker, M., Puttabyatappa, M., Padmanabhan, V., and Auchus, R. J., “Maternal 11-
Ketoandrostenedione Rises Through Normal Pregnancy and Is the Dominant 11-Oxygenated
Androgen in Cord Blood,” The Journal of Clinical Endocrinology & Metabolism, vol. 107, no. 3,
pp. 660–667, Oct. 2021, ISSN: 0021-972X.
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*Banker, M., *Puttabyatappa, M., O’Day, P., Goodrich, J. M., Kelley, A. S., Domino, S. E.,
Smith, Y. R., Dolinoy, D. C., Song, P. X. K., Auchus, R. J., and Padmanabhan, V., “Associa-
tion of maternal-neonatal steroids with early pregnancy endocrine disrupting chemicals and
pregnancy outcomes,” Journal of Clinical Endocrinology & Metabolism, 2020, ISSN: 0021-972x.
DOI: 10.1210/clinem/dgaa909.​
*Authors contributed equally (co-first authors)
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Kelley, A. S.*, Banker, M.*, Goodrich, J. M., Dolinoy, D. C., Burant, C., Domino, S. E., Smith, Y.R., Song, P.X-K., Padmanabhan, V. (2019). Early pregnancy exposure to endocrine disrupting chemical mixtures are associated with inflammatory changes in maternal and neonatal circulation. Scientific reports, 9(1), 5422. *Authors contributed equally (co-first authors)
Awarded NIEHS Extramural Paper of the Month
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Puttabyatappa, M.*, Banker, M.*, Zeng, L., Goodrich, J. M., Domino, S.E., Dolinoy, D.C., Meeker, J., Pennathur, S., Song, P.X-K., Padmanabhan, V. (2019 Submitted for Publication, The Journal of Clinical Endocrinology & Metabolism). Maternal First Trimester EDC Mixtures are Associated with Sexually-Dimorphic Changes in Pregnancy Oxidative Milieu
*Authors contributed equally (co-first authors)​
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Jansen, E. C., Dolinoy, D. C., O'Brien, L, Peterson, K.E., Chervin, R., Banker, M., Téllez-Rojo, M.M., Cantoral, A., Mercado-Garcia, A., Sanchez, B., Goodrich, J.M. (2019 Accepted for Publication, Sleep). Sleep duration and fragmentation in relation to leukocyte DNA methylation in adolescents.
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Wu, Y., Jaclyn M. Goodrich, J. M., Dolinoy, D. C., Sánchez, B.N, Ruiz-Narváez, E.A., Banker, M., Cantoral, A., Mercado-Garcia, A., Téllez-Rojo, M.M., Peterson, K.E. (2019 Submitted for Publication, Medicine & Science in Sports & Exercise). Accelerometer-Measured Physical Activity, Reproductive Hormones and DNA Methylation
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Jansen, E. C., Dunietz, G. L., Chervin, R. D., Baylin, A., Baek, J., Banker, M., Song, P.X-K., Cantoral, A., Rojo, M.M.T. and Peterson, K.E. (2018). Adiposity in Adolescents: The Interplay of Sleep Duration and Sleep Variability. The Journal of Pediatrics, 203, 309-316.
Presentations
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Supervised Learning of Physical Activity Features from Functional Accelerometer Data, Oral Presentation, ICSA (International Chinese Statistical Association) Applied Statistics Symposium, Best Student Paper Session, Gainesville, FL. June 2022
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An Efficient Segmentation Algorithm to Estimate Sleep Duration from Actigraphy Data, Oral Presentation (Joint with Peter X.K. Song), ICSA Applied Statistics Symposium, Best SIBS paper 2022 Session, Gainesville, FL. June 2022
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Supervised Learning of Physical Activity Features from Functional Accelerometer Data, Oral Presentation, ENAR, Houston, TX., Mar. 2022
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Association of Maternal-Neonatal Steroids With Early Pregnancy Endocrine Disrupting Chemicals
and Pregnancy Outcomes, Poster, ENDO, Virtual, Mar. 2021.
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Functional Data Analysis of Physical Activity Probability Curves from Personal Accelerometer Devices. Poster, Joint Statistical Meeting. Denver, CO. August, 2019.
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Novel Statistical Methods to Determine Sleep Duration from Personal Wearable Accelerometer Devices. Poster, ENAR. Philadelphia, PA. March 2019.
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Novel Statistical Methods to Determine Sleep Duration from Personal Wearable Accelerometer Devices. Poster, Michigan Institute for Data Science (MIDAS). Ann Arbor, MI. October, 2018.