Home » A Statistician's Life, Celebrating Women in Statistics

Stephanie C. Hicks

1 March 2019 No Comment

Affiliation:
Assistant Professor, Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
Faculty Member, Johns Hopkins Data Science Lab
Co-Founder, R-Ladies Baltimore

Educational Background:
BS, Mathematics, Louisiana State University
MA and PhD, Statistics, Rice University

About Stephanie
I am from a small town in north Louisiana. I had several highly influential math teachers in middle and high school. At the time, I was primarily interested in chemistry, so I began my college career majoring in chemical engineering. However, I quickly discovered what I loved most about chemistry was mathematics. Within one semester, I switched to majoring in mathematics and went on to tutor local high-school students and college students.

I was supported by two scholarship programs (LSU-HHMI Undergraduate Research Program and LA-STEM Research Scholars Program), which provided resources, preparation, and support to pursue terminal degrees in a STEM field. As part of the scholarship programs, I completed two summer research experience for undergraduates (REUs) in biostatistics, one at Rice University in 2005 and another at the University of Wisconsin in 2006. These rewarding research experiences led me to seek out additional probability and statistics coursework at Louisiana State University (LSU) and ultimately to pursue a PhD in statistics at Rice University. My doctoral thesis focused on developing statistical methods for investigating the consequences of mutations in the genomes of pediatric cancer patients. The diverse training I received at Rice taught me the importance of communication and open collaboration to successfully solve real-world problems.

As a postdoctoral research fellow at the Dana-Farber Cancer Institute (DFCI) and Harvard T.H. Chan School of Public Health, I continued to develop statistical methods and software using the R programming language for the analysis of genomics data under the supervision of Rafael Irizarry. In addition, I accumulated substantial teaching experience in statistics, data analysis, and genomics. I served as the lead teaching fellow for data science at Harvard University, assisted in teaching the statistical methods for functional genomics course at Cold Spring Harbor Laboratories, developed course material and videos for a series of data analysis for genomics courses at Harvard edX, and co-taught data science at Harvard T.H. Chan School of Public Health. The most rewarding part of these experiences was to hear how students were successfully obtaining jobs by discussing their data science final projects in job interviews. These experiences affirmed for me the value of motivating statistical concepts with data and challenging students to think critically and apply their knowledge in practice.

Currently, I am an assistant professor in the department of biostatistics at Johns Hopkins Bloomberg School of Public Health. I am also a faculty member of the Johns Hopkins Data Science Lab and co-founder of R-Ladies Baltimore, a local chapter of a global organization to promote gender diversity in the R programming community. My research interests focus on developing statistical methods, tools, and software for the analysis of genomics data. Specifically, my research addresses statistical challenges in epigenomics, functional genomics, and single-cell genomics such as the pre-processing, normalization, and analysis of noisy high-throughput data leading to an improved quantification and understanding of biological variability. This work led to a K99/R00 award from the National Human Genome Research Institute.

I actively contribute software packages to the R/Bioconductor software project and continue to teach courses in data science and the analysis of genomics data. Most recently, I became involved in one of the 85 one-year projects to develop collaborative computational tools partnering between the Chan Zuckerberg Initiative and the Human Cell Atlas (HCA). With other Bioconductor developers, I will create the infrastructure and tools needed to analyze potentially billions of single cells in the HCA within Bioconductor, which has been highlighted at Rice University and Johns Hopkins.

I am actively working on creating a children’s book featuring trailblazing women in statistics and data science. Stay tuned for updates!

I consider my family—my incredibly supportive husband, Chris, and our two beautiful boys, Alex (2016) and Theo (2017)—a great achievement. In many talks I give, I like to talk about non-work–related things, such as my own hobbies or my family, as a way to normalize the stigma of work-life balance in academia. I strive hard every day to find that work-life balance and want students to know you can absolutely have a great family life and be successful in academia.

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