Xingyi (Daniel) Chen

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, statistical genomics, computational biology, and biomedical data science. I am especially interested in developing statistical and machine learning methods for high-dimensional biomedical data, with applications in single-cell genomics, spatial transcriptomics, RNA-seq, and translational problems in medicine and healthcare.

In Summer 2026, I will be a full-time QSURE intern at Memorial Sloan Kettering Cancer Center in New York, working in the Shah Lab under the mentorship of Dr. Andrew McPherson. My project focuses on developing computational methods to detect homozygous deletions from single-cell DNA sequencing data.

I am currently a research assistant in the Hicks Lab at Johns Hopkins University, Department of Biostatistics, where I develop computational methods, software, and reproducible workflows for spatial transcriptomics and RNA-seq analysis. My recent work includes isoform-level models of human brain aging, Python software for spatially aware quality control, Visium HD preprocessing and visualization pipelines, and benchmarking gene panel selection methods for spatial transcriptomics.

Previously, I worked in the Beer Lab at Johns Hopkins Department of Biomedical Engineering on exploratory analysis and visualization of gene expression data, and I completed a bioinformatics internship in the Wei Lab in Shanghai, where I supported spatial-omics projects and presented literature reviews on machine learning applications in genomics.

I also serve as an Undergraduate Lead Teaching Assistant in the Johns Hopkins Department of Mathematics, where I lead discussion sections, mentor undergraduate TAs, and support courses including Differential Equations and Calculus III.

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, and cities, and spending time with friends.

You can find my CV, Email, GitHub, Google Scholar, LinkedIn, and other links below.