Xingyi (Daniel) Chen
Undergraduate at Johns Hopkins University
I am Xingyi (Daniel) Chen, a rising senior at Johns Hopkins University studying Applied Mathematics & Statistics with minors in Computational Medicine and Mathematics.
My interests lie in biostatistics, computational genomics, and biomedical data science, especially in developing statistical and machine learning methods for high-dimensional biomedical data. I am particularly interested in single-cell and spatial genomics, transcriptomics, and translational problems in medicine and healthcare.
For Summer 2026, I will be a full-time QSURE intern at Memorial Sloan Kettering Cancer Center (MSKCC) in Manhattan, New York. I will work under Dr. Andrew McPherson.
I am currently a research assistant in the Hicks Lab, where I develop computational methods and reproducible pipelines for spatial transcriptomics and RNA-seq analysis. My recent work includes building Visium HD analysis workflows, porting SpotSweeper from R to Python and releasing a Python implementation (GitHub, PyPI), developing isoform-level models for biological age prediction, and maintaining the Python package visiumhd-utils.
Previously, I worked in the Beer Lab at Johns Hopkins on exploratory analysis and visualization of gene expression data, and I completed a bioinformatics internship in the Wei Lab, where I supported spatial-omics projects and presented literature reviews on machine learning applications in genomics.
I am broadly interested in pursuing PhD training at the intersection of biostatistics, statistical genomics, and computational biology.
Outside of research, I enjoy traveling, exploring new cafes/restaurants/cities, and having fun with my friends :)
You can find my CV, GitHub, LinkedIn, and other links below.