I am a Senior Bioinformatics Scientist at Johns Hopkins Medicine with over 9 years of experience in Genomic Data Science.

I specialize in Multi-Omics Integration, Spatial Transcriptomics, and Single-Cell/Nucleus Genomics (sc/snRNA-seq), leveraging machine learning, deep learning, and robust statistical frameworks to uncover the genetic and molecular architectures of complex neuropsychiatric disorders (Bipolar Disorder, Schizophrenia, MDD).

• MDD vs. BP Transcriptomic Pipeline: A high-resolution computational workflow examining mechanistic and splicing differences in BP vs. MDD across the human Amygdala and sgACC.
  • Features: qSV-adjusted Differential Expression, WGCNA, Fusion-TWAS, IsoTWAS, and Leafcutter Splicing Analysis.
• Lithium Mechanism Study: Investigating longitudinal gene expression dynamics, structural alterations, and neuroprotective treatment response in Bipolar Disorder cohorts using large-scale Bulk and snRNA-seq.
• Genome-Wide Association Studies (GWAS) Pipeline: A publication-grade, end-to-end framework for running massive variant-phenotype association mappings across multi-diagnostic cohorts (Controls, MDD, and BP).
  • Features: Sample/Variant Quality Control (PLINK/GCTA), HRC Genotype Imputation (Michigan Imputation Server/Eagle), Covariate-Regressed Linear/Logistic and LMM Association Testing (RVTESTS), Inverse-Variance Meta-Analysis (METAL), and Post-GWAS Inflation Diagnostics (Manhattan, Q-Q, and Normalized Lambda Testing).
• Genomic Pipelines: Developing cloud-scalable, reproducible Nextflow and SLURM pipelines for high-throughput variant calling and transcriptome-wide association mapping.