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Hi, I'm Margaret!

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.

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. 

to 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

I completed my Masters Degree in Biostatistics in May 2017

BS/BA in Math and Economics

Villanova University

I completed my undergraduate education in May 2011

to Work

Research and Experience

Graduate Method Research
University of Michigan, 2016- present

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

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:

  • Metabolomics Data

  • Accelerometer Data

  • Toxicant Exposure Data

  • Cognitive Neuro Data 

Graduate Teaching Experience
University of Michigan, 2015

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

Prior to returning to graduate school, I worked as a Financial Analyst with GE Healthcare. 

  • 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.

  • Upon completing the FMP program, I accepted a position as a Global Supply Chain FP&A Analyst




Journal Publications
  • ​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

  • 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.

  • *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)

  • 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

  • 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)

  • 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.

  • 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

  • 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.

  • 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

  • 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

  • Supervised Learning of Physical Activity Features from Functional Accelerometer Data, Oral Presentation,  ENAR, Houston, TX., Mar. 2022

  • Association of Maternal-Neonatal Steroids With Early Pregnancy Endocrine Disrupting Chemicals
    and Pregnancy Outcomes, Poster, ENDO, Virtual, Mar. 2021.

  • Functional Data Analysis of Physical Activity Probability Curves from Personal Accelerometer Devices. Poster, Joint Statistical Meeting. Denver, CO. August, 2019.

  • Novel Statistical Methods to Determine Sleep Duration from Personal Wearable Accelerometer Devices. Poster, ENAR. Philadelphia, PA. March 2019. 

  • Novel Statistical Methods to Determine Sleep Duration from Personal Wearable Accelerometer Devices. Poster, Michigan Institute for Data Science (MIDAS). Ann Arbor, MI. October, 2018. 




University of Michigan

Ann Arbor, MI

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