I am a postdoctoral fellow in Prof. Stephanie Hicks’s group in the Department of Biostatistics at the Bloomberg School of Public Health, Johns Hopkins University.

My research work is on statistical methodology, software development, and benchmarking for the analysis of high-throughput genomics data. Currently, I am mainly working with spatially resolved transcriptomics and single-cell RNA sequencing data. My work is motivated by collaborative projects with researchers in various fields of biology. These collaborations show us where the interesting statistical problems lie, and let us contribute to fascinating scientific advances.

I support open science principles, including free availability of code, software, and data resources, and publication of preprints. In my methodological work, I am a proponent of rigorous benchmarking against existing methods. I mainly work with the R programming language, and most of my software packages have been developed as part of the open-source Bioconductor project. I am also interested in teaching, especially R programming skills, and have been an instructor for several short workshops for Data Carpentry and Software Carpentry. In January 2021, I received a Research Symbiont award for open code and data sharing.

My training includes a PhD in Biostatistics with Prof. Mark Robinson at the University of Zurich, Switzerland, and a MSc in Statistics at ETH Zurich, Switzerland. Previously, I studied physics, mathematics, and economics at the University of Western Australia and Australian National University, and worked for several years as a policy analyst for the Australian federal public service.