About
I'm a professional teacher, data scientist, and researcher.
Currently, I'm pursuing a PhD in Statistics at UCLA, building on a foundation that includes a Bachelor’s in Pure Mathematics and a Master’s in Applied Statistics. Before my doctoral studies, I spent five years in the classroom teaching high school math and physics—an experience that taught me how to translate complex quantitative ideas into clear, actionable results.
As a teacher, I’m passionate about mentoring students and helping them develop both conceptual understanding and practical problem‐solving skills. Whether I’m guiding students through proof techniques or demonstrating real‑world quantitative applications, my goal is always to foster curiosity, persistence, and confidence in the team I lead.
As a data scientist, I'm eager to analyze data to expose patterns and unearth trends that are novel, rigorous, and helpful.
Working as the Lead AI Architect at a startup, I lead the development of scalable AI infrastructure that bridges statistical rigor with real-world operational needs.
As a researcher, my primary interest lies in time‑series analysis and point processes. I’m currently developing statistical frameworks that can be applied to infectious disease dynamics, with the aim of informing policy and improving real‑world decision‑making.
If you have a project idea or challenge you’d like me to tackle,
I’d love to hear from you—please feel welcome and encouraged to reach out using the contact information below.