Rita Neupane

A little about me

I'm a researcher drawn to the place where biology meets computation, held there by one persistent question: how much more can we understand about life once we're willing to look at it through data? I like taking complicated problems apart until they become smaller, answerable ones, then chasing those answers through science, mathematics, and code. To me, research isn't the search for a tidy conclusion. It's an interrogation of the data itself: where it came from, how far it can be trusted, and what it's actually entitled to tell us. Most of what I've learned has been self-taught, shaped less by instruction than by deciding to do the thing and learning what I needed along the way. I've studied caffeine consumption and dengue transmission in Nepal, investigated antimicrobial resistance in E. coli through computational methods, and helped build a platform that makes dengue surveillance data easier to read and act on. When the dengue data proved difficult to access, I went directly to government offices, sitting with officials to understand how health data are collected, evaluated, and released. Tutoring taught me something similar from another direction: how to see a familiar idea through someone else's eyes and find the explanation that actually lands. Computational biology, genomics, and public health are where I keep returning, but I don't want to be fenced into a single discipline. I want to move between biology, mathematics, computing, research, and teaching, using each as a different lens on the same problems. I hope to become a scientist who not only studies difficult biological questions, but translates them: building tools people can use and making science legible to those who need it. For me, learning is a cycle of curiosity, experimentation, teaching, and the next question.