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. 

 

Education

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PhD Candidate

University of Michigan

 

After beginning the PhD program in Fall of 2017, I achieved candidacy in May 2018

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MS in Biostatistics

University of Michigan

I completed my Masters Degree in Biostatistics in May 2017

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BS/BA in Math and Economics

Villanova University

I completed my undergraduate education in May 2011

 

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

     

 

Publications

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.

Presentations
  • 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. 


     

    Contact    

 

University of Michigan

Ann Arbor, MI

 

mbanker@umich.edu

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