Stephanie C. Hicks

Stephanie C. Hicks is an Associate Professor in the Department of Biomedical Engineering at the Whiting School of Engineering and in the Department of Biostatistics at Johns Hopkins University. She is also affiliated with multiple research centers, including the Malone Center for Engineering in Healthcare, the Center for Imaging Science, the Center for Computational Biology, the Johns Hopkins Data Science Lab, and serves as a preceptor in the Department of Genetic Medicine and the Department of Biochemistry and Molecular Biology.

• B.S. in Mathematics from Louisiana State University (LSU)
• M.A. and Ph.D. in Statistics from Rice University, advised by Marek Kimmel and Sharon Plon
• Postdoctoral training with Rafael Irizarry at the Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health

Dr. Hicks is an applied statistician whose research lies at the intersection of genomics and biomedical data science. Her work focuses on developing computational methods using statistics and machine learning to address challenges in single-cell genomics, epigenomics, and spatial transcriptomics. She implements these methods as open-source software, guided by a 'problem-forward' philosophy that emphasizes real-world applicability. Her research has led to contributions in spatially aware quality control (e.g., SpotSweeper), self-supervised learning for spatial domain detection, and benchmarking of feature selection methods. Her recent publications reflect a strong trend in integrating machine learning—especially deep learning and transformers—into genomic data analysis.

She has received numerous honors, including the COPSS Emerging Leader Award, the Teaching in the Health Sciences Young Investigator Award, the Myrto Lefkopoulou Distinguished Lectureship (2023), and election as a Fellow of the American Statistical Association. These awards recognize her leadership, contributions to statistical science, and commitment to education and reproducibility.

Dr. Hicks is actively involved in mentoring and advising, with students such as Kinnary Shah, Jianing Yao, Michael Totty, and Boyue Guo contributing to her research. She also contributes to the academic community through editorial roles, including Associate Editor for Reproducibility at the Journal of the American Statistical Association and membership on the editorial board of Genome Biology. She co-hosts the popular podcast The Corresponding Author and is a co-founder of R-Ladies Baltimore, promoting diversity and inclusion in data science.

Her work is supported by her affiliations with interdisciplinary research hubs at Johns Hopkins, where she collaborates across engineering, medicine, and data science. She is also deeply engaged in science communication, education, and advocacy, notably through her public commentary on the importance of federal research funding and participation in events like Stand Up for Science.