Summary
Jungang Zou is a PhD candidate in Biostatistics at Columbia University with eight years of experience bridging software engineering and statistical research, currently serving as a graduate research assistant and teaching assistant. His work centers on Bayesian methods for handling missing data, informed by strong practical skills in data mining, deep learning, and large-scale data tools like Spark. Comfortable across C, C++, Java, Python, R, and SQL, he has applied these languages in both academic research and quantitative development at WorldQuant. Known for translating complex statistical ideas into reproducible code and coursework, he brings a rare combination of rigorous biostatistics training and hands-on software engineering from a software engineering bachelor’s background. Based in New York, he focuses on reproducible, computation-efficient solutions for real-world biomedical data problems.
8 years of coding experience
Doctor of Philosophy - PhD, Biostatistics, Doctor of Philosophy - PhD, Biostatistics at Columbia University in the City of New York
Bachelor of Engineering - BE, Software Engineering, Bachelor of Engineering - BE, Software Engineering at 厦门大学
English, Chinese