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.

Developing AI and machine learning models to better understand and predict human diseases through biomedical data analysis.

Applying statistical modeling and data analysis techniques to identify patterns and determinants in large-scale health datasets.

Exploring single-cell sequencing data to uncover cellular heterogeneity and mechanisms of disease progression.

Studying the epigenetic regulation of cell identity and tissue regeneration through integrative computational methods.

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.

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.

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