I joined Genentech in August 2021 as a Senior Scientist and then as a Principal Scientist in 2022. My research focuses on large-scale single-cell multi-omics and spatial omics data analysis and tool development. Before joining Genentech, I was an Assistant Professor of Medicine (tenure-track) at Harvard Medical School, an Assistant Investigator & Director of Bioinformatics and Computational Biology at the Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, and an Associate Member of the Broad Institute of MIT and Harvard. My representative works include a) RSEM, a popular RNA-Seq transcript quantification tool that is cited over 15,000 times (Google Scholar) and adopted by big consortia such as TCGA and ENCODE; b) Cumulus, the first comprehensive cloud-based single-cell RNA-Seq data analysis framework. I completed two postdoctoral trainings with Dr. Lior Pachter at UC Berkeley and Dr. Aviv Regev at the Broad Institute.
It takes me over 10 years to transit from a hardcore computer scientist, whose main focus is novel tool development to a computational biologist, who appreciate both data-driven science discovery and innovative tool development. The two postdoc trainings I received from Drs. Lior Pachter and Aviv Regev are essential for making this transition happen. As a Postdoc mentor, I hope to help my trainees to advance their scientific career, just like how my postdoc advisers helped me before. Collaborating with colleagues from Cellular and Tissue Genomics, AI/ML and the Translational Genomics program, my trainees will have opportunities to work on exciting translational research by applying cutting edge single-cell multiomics & spatial omics technologies and the state-of-the-art deep learning algorithms.
Nat. Methods 2020; 17:793-798
Nature 2021; 595(7865):107-113
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My lab focuses on single-cell multiomics and spatial omics big data analysis and tool development. My lab utilizes the state-of-the-art machine learning and cloud computing technologies. In particular, my lab has three directions: a) novel sequencing and spatial technology evaluation, b) scalable tool and infrastructure development (e.g. Cumulus, Pegasus), and c) science-driven data analysis utilizing the technology and tools evaluated/developed in a) and b).