Research Areas

Area 1: High-throughput Single-cell Multiomics & AI Foundation Model

We harness genetic demultiplexing (SNP) and hashing strategies (Antibody/Lipid tagging) to maximize throughput for understanding human genetic variation at population-scale. We developed SCITO-seq, leveraging combinatorial indexing to enable ultra-high throughput (>1M cells) profiling of RNA+protein in the same cell. These large-scale data productions are essential for building AI foundation models.

Area 2: Spatial Multiomics Platforms

We deploy various combinatorial indexing strategies (sci-RNA-seq, XYZeq, Seq-Scope) to perform single-cell multiomics and develop novel experimental and computational methods for spatial sequencing at unprecedented scale. Beyond spatial transcriptomics, we are developing platforms for spatial genomics and epigenomics analysis through collaborations with clinical scientists.

Area 3: CRISPR-based Functional Genomics

We use CRISPR a/i/KO systems to edit primary cells (e.g., human T cells) and cancer cells with state-of-the-art editing technology, focusing on immunology and immuno-oncology. Combined with SCITO-seq, we develop genome-scale single-cell CRISPR editing platforms to evaluate functional variants identified through single-cell and spatial multiomics analyses.