About me

I am a postdoctoral scholar in the Division of Biostatistics at University of California, Berkeley, mentored by Dr. Mark van der Laan and Dr. Maya Petersen. In 2020, I received PhD in Biostatistics from Johns Hopkins University under the supervision of Dr. Brian Caffo.

My research focuses on novel causal inference and reproducibility analysis methods driven by real-world challenges in clinical trials, electronic health records, and neuroimaging data. My methodological work includes targeted maximum likelihood estimation (TMLE) for longitudinal causal mediation, higher order TMLE and computerized analysis of causal roadmaps, meta-learning with the Highly Adaptive Lasso, and analysis of reproducibility measures for imaging data. My applied research involves random interventions and trial emulation with health registry data, clinical trials with brain functional connectivity, and causal mediation of longitudinal and neuroimaging data.

Keywords

Targeted machine learning; Causal inference; Longitudinal mediation; Stochastic intervention; Survival analysis; Reproducibility.

Neuroimaging data; Functional connectivity; Primary Progressive Aphasia (PPA); Neurodegenerative diseases; Clinical trials; Electronic health records; Health registry data; Trial emulation.