My research interests focus on advancing precision medicine by leveraging bioinformatics, data science and interdisciplinary collaboration. My work aims to bridge computational approaches with clinical insights to address the complexities of tumor heterogeneity, particularly through multi-omics integration and predictive modeling. 

Specifically, I focus on:

1. Biomarker Discovery and Validation: Developing and validating molecular biomarkers that can reliably predict cancer onset, progression, and response to therapies.

2. Understanding Cancer Heterogeneity: Utilizing single-cell and bulk omics data to elucidate the genetic and molecular diversity within tumors and across patient populations. 

3. Integrative Data Approaches for Treatment Prediction: Employing machine learning and AI to integrate multi-omics and clinical data, building models that predict treatment efficacy and resistance mechanisms. 

We collaborate with researchers and clinicians to design studies, analyze data, and develop data-driven products. We work on a variety of projects, including:

• Collaborate with researchers to perform in-depth genomics and clinical data analysis, offer support in preparing manuscripts and grant applications.
• Partner with clinicians to design studies and analyze data, develop data-driven products, and validate hypotheses using real-world evidence gathered from diverse consortium organizations, such as labs, hospitals, and literature mining.
• Provide insightful data science consultation to pharmaceutical and biotech companies on new drug development, leveraging both short-reads and long-reads sequencing data analysis, and utilizing structured and unstructured patient's data for clinical research.