About Me

I am a researcher with 12 years of experience coding in Python, 6 years experience in computer vision and 7 years experience in machine learning/AI. I have experience in both FinTech and biological applications, and am passionate about buildings models that have real-world net positive impact.

Current Work Experience

Currently, I am a Staff Machine Learning Scientist at Visa in Value-Added Services, building fraud detection models for real-time payment networks. Visa is a payment network organization (now corporation) which handles safe and secure payments for every cardholder across the world in the Visa payment network.

Past Work Experience

During graduate studies, I pursued an internship at Genentech, a research division of Roche. I was in an Computer Vision/AI team and utilized neural nets to visualize gene expression in histopathology tissue as my project.

Academic Experience

I graduated with an MS and PhD from the University of Michigan School of Medicine in the Department of Computational Medicine and Bioinformatics (DCMB). Most of my research centered on developing machine learning methods in precision medicine to ameliorate the negative effect of small sample size. I also have a Master in Public Health in Hospital & Molecular Epidemiology, which gave me expertise in experiment/project design, as well as scientifically-sound statistical strategies for interpreting data while ameliorating bias.