Our primary research interest is to develop computational methods for analyzing modern “omics” data, especially for single-cell and spatial transcriptomics. Our research combines statistical modeling, bioinformatics, and machine learning to provide a more rigorous interpretation of biological signals. Some specific topics include:

1. Generation of realistic in silico single-cell and spatial multi-omics data;
2. Computational modeling of gene co-expression in single-cell and spatial transcriptomics;
3. Detection of differential expression in single-cell and spatial transcriptomics;
4. Gene selection, dimensionality reduction, and cell subsampling for large-scale datasets.

We are looking for students and postdocs that are interested in developing novel computational methods for single-cell/spatial omics.

Students in Ph.D. in Biomedical Science at UConn Health are very welcome to rotate in our lab. If you are interested in computational genomics, please email me (dosong@uchc.edu) or stop by my office (R1151).

Our lab is seeking one postdoctoral researcher in the field of bioinformatics, computational biology, and statistical genomics. Please email me (dosong@uchc.edu) with “Postdoc application: + YOUR NAME” as the subject line and include your CV (including a list of references) and a research statement (1-2 pages). Review of applications will begin immediately and continue until the position is filled.

Accepting Lab Rotation Students: Spring 2 Block 2025

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