About me

I am a Postdoctoral Research Fellow at the Dana-Farber Cancer Institute and an affiliate of the Department of Biostatistics at the Harvard T.H. Chan School of Public Health in Boston.

My research focuses on Bayesian statistics, probabilistic machine learning, and cancer genomics. I am particularly interested in Bayesian discrete matrix factorization and other interpretable models for complex biomedical data, especially in cancer genomics. While cancer genomics provides the main motivation for this work, the methods are useful more broadly for uncovering structure in high-dimensional and heterogeneous data.

I earned my Ph.D. in Probability and Statistics from CIMAT, A.C., where my research focused on statistical genomics, particularly classification and network integration. As part of my doctoral training, I joined the Department of Bioinformatics at the Walter and Eliza Hall Institute of Medical Research (WEHI) in Melbourne, Australia, as a visiting scientist and Ph.D. candidate. There, I worked on an interdisciplinary project on acute rheumatic fever and rheumatic heart disease using multiplex assay, RNA-sequencing, and proteomics data. Before moving to the United States, I taught statistics at the university level in Kenya and worked on problems in biostatistics, statistical learning, and applied statistics.

I enjoy developing statistical methods that are mathematically sound, computationally useful, and interpretable in real scientific applications.