Summary
Yifeng Tao is a Quantitative Researcher at Citadel Securities with a Ph.D. in Computer Science from Carnegie Mellon and a decade of experience applying machine learning to real-world problems. He blends rigorous academic research—five years as a Carnegie Mellon graduate research assistant—with hands-on quantitative work in a high-frequency trading environment. His background spans machine learning, automation, and economics, giving him a rare cross-disciplinary view of modeling, systems, and market behavior. At Citadel Securities he focuses on translating advanced ML methods into production-ready strategies and tools. Based in New York, he brings both deep theoretical knowledge and practical engineering discipline to fast-paced, data-driven decision making. Colleagues can expect a researcher who values reproducibility and robust, scalable solutions informed by top-tier academic training.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at Carnegie Mellon University School of Computer Science
Bachelor’s Degree Economics (Second degree), Bachelor’s Degree Economics (Second degree) at Tsinghua University
English, Chinese