Sarah Leavitt
Adjunct Lecturer at Boston University School of Public Health
Boston, Massachusetts, United States
Summary
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Senior🎓
Top SchoolSarah Leavitt is an adjunct lecturer and biostatistician with eight years of experience applying statistical computing to infectious disease research, particularly tuberculosis transmission dynamics. With a PhD in Biostatistics from Boston University, she has developed Bayesian survival meta-analysis methods that integrate diverse data streams and account for interval censoring and disease severity. She teaches courses like Introduction to Statistical Computing and Biostatistics, mentors students in R and SAS, and blends hands-on coding instruction with methodological research. As a former postdoc and graduate researcher focused on TB in South Africa, she brings field-informed perspectives to model development and data cleaning. Outside academia she balances a dynamic career with parenting, channeling practical organizational and mentorship skills from childcare and camp leadership into collaborative research and teaching.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science (BS), Biology, General, Bachelor of Science (BS), Biology, General at Messiah CollegeDoctor of Philosophy (Ph.D.), Biostatistics, Doctor of Philosophy (Ph.D.), Biostatistics at Boston University
Github Skills (13)
r-package5
r65
network-graph4
mathematics4
r4
network-analysis3
igraph2
graph-theory2
open-science2
graph-algorithms2
time-series1
complex-networks1
data-science1
Programming languages (1)
Github contributions (5)
sarahleavitt/nbTransmission
Jun 2019 - Jan 2021
R package for the naive Bayes (NB) transmission method: estimating relative transmission probabilities, reproductive number, and serial interval.
Contributions:8 releases, 172 commits, 2 PRs in 1 year 6 months
HopkinsIDD/hitRcovid
Sep 2020 - Dec 2020
Contributions:81 commits, 67 pushes, 3 issues in 2 months
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