CV
Curriculum vitae for Qian Qin.
Contact Information
| Name | Qian Qin |
| Professional Title | Principal Investigator / Professor, School of AI, Wuhan University |
| qinqian [at] whu [dot] edu [dot] cn |
Professional Summary
Computational biologist developing AI and multi-omics methods with a professional focus on spatial transcriptomics analysis and long-read RNA-seq/DNA-seq structural variant analysis. Current work includes cancer genomics, scalable cell segmentation pipelines, immune-mediated disease research, and long-read sequencing approaches for resolving complex transcriptomic and genomic variation.
Experience
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2024 - 2026 Boston, MA, USA
Research Scientist; Staff Scientist / Collaborator
Brigham and Women's Hospital; Dana-Farber Cancer Institute, Harvard Medical School
Conducted computational biology research across Harvard Medical School-affiliated research institutes, with emphasis on cancer genomics, long-read sequencing, multi-omics analysis, autoimmune disease research, and spatial transcriptomics methods.
- Developed computational workflows for long-read RNA-seq/DNA-seq analysis, structural variant interpretation, spatial transcriptomics data processing, tissue organization analysis, cell-state mapping, and cell-cell interaction analysis.
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2022 - 2024 Cambridge, MA, USA
Genomics Team Lead
Broad Institute of MIT and Harvard
Led multi-omics data pipeline development for DepMap at the Broad Institute.
- Developed and supported scalable pipelines for WGS, ATAC-seq, single-cell ATAC-seq, RNA-seq, and long-read RNA-seq/DNA-seq analysis.
- Built workflows for structural variant analysis and integration across large-scale DepMap multi-omics datasets.
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2019 - 2022 Boston, MA, USA
Postdoctoral Research Fellow
Massachusetts General Hospital, Harvard Medical School
Conducted postdoctoral research in rhabdomyosarcoma single-cell genomics, lineage tracing, cancer epigenomics, and probabilistic modeling of cell-state dynamics.
- Analyzed rhabdomyosarcoma single-cell RNA-seq and single-cell ATAC-seq datasets.
- Analyzed rhabdomyosarcoma single-cell lineage tracing data and CRISPR clonality recorder datasets, including GESTALT-based lineage recording systems.
- Performed ChIP-seq data analysis for rhabdomyosarcoma regulatory genomics studies.
- Developed single-cell dynamics models using Pyro and PyTorch.
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2017 - 2019 Shanghai, China
Assistant Research Scientist
Children's Hospital of Fudan University, Pediatric Research Institute
Studied clinical genomic diagnosis for pediatric diseases.
- Advanced the first real-world clinical deployment of in-house genomic analysis tools.
Education
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2012 - 2017 Shanghai, China
PhD Student
Tongji University
School of Life Sciences and Technology
- Advised by Dr. Xiaole Shirley Liu
- Contributed to the ENCODE project and developed computational methods, databases, and infrastructure for large-scale epigenomic data analysis.
Skills
Computational Biology (Expert): AI for biomedicine, Bioinformatics, Cancer genomics, Cell segmentation, Clinical genomics, DNA-seq, Epigenomics, Gene fusions, Long-read sequencing, Machine learning, RNA-seq, Single-cell multi-omics, Spatial transcriptomics, Structural variation, Xenium
Programming Languages (Expert): Python, R, Rust
Machine Learning (Expert): PyTorch, Pyro