About Me

Greetings!

I am a research scientist at Fred Hutch with hands-on experience in designing and implementing statistical and machine learning methods to solve real-world problems. My background includes rigorous training in data analysis, statistical modeling, and causal inference, with a strong emphasis on generating actionable insights from complex, high-dimensional data.

I completed my PhD in Biostatistics at Emory University. where I worked on developing robust and efficient statistical procedures using machine learning techniques. My work has involved high-dimensional feature selection, targeted learning algorithms, and theory for two-stage sampling designs - techniques that I have applied to large-scale datasets to support data-driven decision-making.

I enjoy working at the intersection of statistics and data science, and I am passionate about developing reliable, interpretable, and scalable solutions that drive real-world impact.