NIH T90 fellowProject 1: Identifying the functions of Tie2 receptor complexes to rescue diabetic vasculopathyProject 2: Developing a novel synthetic serum-free media for optimal pluripotent stem cell culture.Project 3: Characterizing the biochemical activity of AI-designed de novo protein binders using high-throughput cell-based assays for basic science research and therapeutic application.

NIH T90 & TL1 fellowMagnuson ScholarProject 1: Investigated the molecular basis of Tie2 signaling using AI-based design protein scaffolds to mitigate vascular diseases.Project 2: Utilized de novo designed high-affinity mini binder proteins to neutralize SARS-COV2 virus infection in kidney organoids and cardiomyocytes.Project 3: Performed single-cell RNA sequencing and analysis to study tooth development and devise differentiation protocols from induced pluripotent stem cells to make ameloblasts and odontoblasts.Project 4: Characterized the differentiation capacity and cellular senescence metabolism of dental pulp stem cells.

Ronald E. McNair scholarProjects:1. Yeast Replicative lifespan project - Used yeast cells with different genotypes to perform large-scale screens to understand how different genetic, environmental, and metabolic factors affect yeast aging. 2. Yeast Chronological Lifespan Project - Aimed to understand how various drugs impacted on yeasts’ lifespan over time. 3. A drugs screen project to find natural compounds that mimic the functions of rapamycin for mTor inhibition to understand the validity of the health benefits of common supplement drugs. 4. Investigation of exceptionally long-lived single mutant yeasts - Utilized R programming to search for yeast strains that lived for more than 75 divisions to identify genes and metabolic pathways that interplayed in yeast longevity.

Patient blood sample documentation, blood processing for cryopreservation, cell culture BLS3 hood sterilization, and liquid nitrogen storage management.

SNI Summer Research Intern Extension to part-time intern Project: Evaluated the correlation between MRI data and cognitive test scores of Multiple Sclerosis patients and aimed to develop a standardized model to diagnose Multiple Sclerosis at an early stage.