Xiao Fang is a quantitative researcher based in New York with 10 years of experience translating advanced statistical and computational methods from cosmology into finance. After a prolific academic career—60+ publications and 3000+ citations—she led data-analysis pipelines and core software in C/C++ and Python for large international astrophysics collaborations before moving into quantitative finance at A.R.T. Advisors. Xiao combines rigorous experimental-design thinking with practical production coding, building robust analysis tools under real-world constraints. Her background in leading independent research projects and collaborating across global teams gives her a rare blend of deep domain expertise and cross-disciplinary communication skills. Notably, she brings the precision of a stargazer to market modeling, applying techniques honed on the night sky to noisy financial signals.
10 years of coding experience
Bachelor’s Degree, Physics, Bachelor’s Degree, Physics at Nankai University
Exchange, Physics, Exchange, Physics at Heidelberg University
Doctor of Philosophy (PhD), Physics, Doctor of Philosophy (PhD), Physics at The Ohio State University
An FFTLog code for efficiently computing integrals containing 1 spherical Bessel function or Bessel function or its 1st/2nd derivative.
Contributions:1 release, 51 commits, 3 PRs in 3 years 4 months
besselintegralsbessel-functionderivativecomputing
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