Biography
In 2022, I earned my Master of Public Health (MPH) in Epidemiology and Biostatistics from UC Berkeley, where I developed a strong interest in Bayesian statistics and causal inference. I am currently a Biostatistician in the Department of Anesthesiology, Perioperative, and Pain Medicine, where I leverage electronic health record (EHR) data to investigate a wide range of observational research questions using advanced causal inference techniques. My work primarily focuses on evaluating treatment effectiveness, identifying risk factors for perioperative outcomes, and optimizing clinical decision-making through methods such as mixed-effects modeling and survival analysis. Previously, I worked as a data engineering intern at Bayer Pharmaceuticals and as a research assistant in the Marshall Lab at UC Berkeley, where I developed predictive models for malaria incidence in São Tomé and Príncipe.

Interests
Moving forward, I am particularly interested in advancing causal inference methodologies for healthcare data and integrating machine learning approaches to enhance clinical decision-making in perioperative and pain medicine.

Play

In my free time, I enjoy exploring new activities, from surfing and boxing to pottery and rock climbing. I’m also passionate about EDM concerts and love learning about the music production process