College Freshman, Inducted 2019
Harvard University, Computer Science
Hematological diseases affect millions of people worldwide. Early diagnosis is key to treating/mitigating these diseases, but diagnosis is costly, time-intensive, and requires trained medical professionals. Automated or in-home screening can greatly improve the prognosis and treatment of these diseases. My research focused on developing a low-cost, smartphone-based, solution that instantly screens for hematological diseases. I successfully designed a clip-on smartphone microscope attachment that captures blood cell images from a blood-smear. I applied computer vision techniques to segment the individual cells and trained deep-learning models to automatically classify blood cell morphology, detect abnormalities, and screen for diseases.