I am a Ph.D. student in Biomedical Sciences at the University of Macau, focusing on the intersection of artificial intelligence and computational cardiotoxicity modeling.

My current research centers on ion channel electrophysiology and action potential modeling — building computational models to explore how different drugs may affect cardiac safety and toxicity.

Beyond predictive modeling, I aim to develop interpretable and clinically relevant AI tools that can support real-world drug safety assessment and personalized treatment strategies. By collaborating closely with clinicians, my goal is to bridge computational biology and precision medicine.

Investigated how common cardiometabolic conditions, such as hypertension, modulate immune responses to vaccination and influence real-world vaccine effectiveness. Led a retrospective cohort study that identified hypertension as a significant factor attenuating COVID-19 vaccine protection in elderly patients (published in Frontiers in Immunology). Continued to expand this research line to explore interactions between broader cardiovascular comorbidities and vaccine performance across different infectious diseases.

Conducted analysis of single-cell and immunomics datasets, built and optimized analysis pipelines, developed bioinformatics tools, and facilitated collaborative projects across multidisciplinary teams.

We applied sea-ATI to seven plant tissues to survey their active cistrome and generated 41 motif models, including 15 new models representing previously unidentified cis-regulatory vocabularies. ATAC-seq and RNA-seq analyses confirmed the functionality of these elements. Comparing WRKY CREs between sea-ATI and DAP-seq libraries revealed thermodynamic and genetic drift effects on evolution. Sea-ATI can identify both positive and negative regulatory cis-elements, providing insights into the functional non-coding genome of plants (published in Nucleic Acids Research).

ATAC-seq, DNase-seq, Sea-ATI and other technologies were used to find non-coding functional sites and develop high-quality germplasm resources for forage (published in iMeta).

Leveraged E. coli CL high-expression system to produce influenza HA antigen and implemented a streamlined one-step purification, enhancing yield and workflow efficiency.