Silvia P. Canelón

Silvia P. Canelón

Postdoctoral Research Scientist

University of Pennsylvania

About me

Hello, and welcome! I’m a postdoctoral research scientist in the Department of Biostatistics, Epidemiology, and Informatics at the University of Pennsylvania Perelman School of Medicine. My research interests include applications of biomedical informatics in the public and population health fields. I work in the Boland Lab on projects that develop novel data mining methods to extract pregnancy-related information from Electronic Health Records (EHR) and study the relationship between environment and disease. Learn more about my research interests in publications.

I enjoy using R to optimize my research workflow and have noticed it making guest appearances elsewhere in my life. I’m certified as an RStudio Tidyverse Instructor and am passionate about R education for the public good. Keep up with my R tinkering in posts and teaching in talks. Thanks for stopping by!


  • Reproductive & sexual health
  • Prenatal & perinatal health
  • Social determinants of health
  • Environmental exposures
  • Data science for good
  • R education


  • Tidyverse Instructor Certification, 2020


  • Certificate in Biomedical Informatics, 2019

    University of Pennsylvania

  • Ph.D. in Biomedical Engineering, 2018

    Purdue University

  • B.S. in Biomedical Engineering, 2012

    University of Minnesota



Postdoctoral Research Scientist

University of Pennsylvania

Oct 2018 – Present Philadelphia, PA

Developing tools to mine Electronic Health Record (EHR) data for population-level analyses with the purpose of understanding female fertility and infertility related conditions.

Designing machine learning methods and algorithms with the goal of contributing software to the biomedical informatics field and making it accessible in open platforms


Graduate Research Assistant

Purdue University

May 2012 – May 2018 Indianapolis, IN

Characterized the type I collagen matrix produced by osteoblasts in vitro to assess structural, biochemical, mechanical, and biological properties. Assays used include atomic force microscopy, nanoindentation, Fourier transform infrared spectroscopy, and quantitative gene expression analysis.

Investigated the effect of (1) an induced reduction in molecular crosslinking on type I collagen matrix properties and (2) mechanical loading via equibiaxial substrate strain to determine the impact of environmental factors.


Recent & Upcoming Talks

Introducción al Paquete xaringan

Taller del paquete xaringan para presentaciones,
creado para R-Ladies Xalapa

Sharing Your Work with xaringan: The Basics and Beyond

An introduction to xaringan for presentations, created for the NHS-R Community 2020 Virtual Conference

An Antarctic Tour of the Tidyverse

An introductory tidyverse tutorial created and presented for R-Ladies Chicago

Posts & Publications

Recent Posts

Becoming certified as an RStudio Tidyverse Instructor

An overview of the RStudio Instructor certification process and collection of resources to support anyone on their certification journey.

Customizing Hugo Academic's Dark Mode with Help from Atom

Tutorial on how to customize the dark mode in Hugo’s Academic theme with help from the Atom text editor package Pigments.

Recent Publications

Not All C-sections Are the Same: Investigating Emergency vs. Elective C-section Deliveries as an Adverse Pregnancy Outcome

Publication and poster accepted for the 2021 Pacific Biocomputing Symposium. This study utilizes Electronic Health Record (EHR) data to assess the impact of pregnancy-specific maternal morbidity and patient-specific characteristics on experiencing an emergency admission at the time of delivery and its relationship to Cesarean section (C-section) deliveries

Development and Evaluation of MADDIE: Method to Acquire Delivery Date Information from Electronic Health Records

An R algorithm designed to extract delivery episode details from structured Electronic Health Record data.

Is Hydroxychloroquine Safe During Pregnancy? Observations from Penn Medicine

Preprint as a contribution from a rapid response exploration of hydroxychloroquine effects on pregnancy-related outcomes.


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