I am a PhD candidate in the Graduate Group in Biostatistics at University of California, Berkeley, advised by Prof. Yun S. Song. Committed to advancing our understanding of biology through rigorous computational and statistical frameworks, I specialize in distilling insights from high-dimensional and noisy biomedical data. My methodological focus encompasses statistical machine learning and deep learning techniques, which I apply to a wide array of biological questions spanning cell biology, cancer immunology, and neuroscience. I am particularly captivated by the untapped potential of emerging technologies such as spatial transcriptomics and CRISPR-screening, which I believe are key to unraveling the complex molecular landscapes underlying tumor microenvironments and cellular interactions.
As a first-generation college student, I am deeply devoted to promoting diversity, equity, inclusion, and belonging (DEIB) in academia. Through various roles, including serving as the Inaugural DEIB Fellow at UC Berkeley’s Biostatistics Division, I have spearheaded numerous initiatives to increase accessibility and representation. My efforts span from community outreach programs exposing underrepresented minorities to STEM, to lectures exploring algorithmic bias in healthcare, to bolstering inclusive admissions processes. Having directly experienced educational barriers, my personal journey fuels my passion for dismantling systemic inequities. I strive to continue driving positive change, furthering DEIB through mentorship, collaboration, and outreach.
Pronouns: she/her/hers
Ph.D. in Biostatistics (designated emphasis in Computational and Genomic Biology), 2020 - present
University of California, Berkeley
M.A. in Biostatistics, 2018 - 2020
University of California, Berkeley
B.S. in Mathematics and Applied Mathematics, 2014 - 2018
Tianjin University, China
Graduate student intructor
Graduate student intructor
Graduate student instructor
Graduate student intructor