Xingjian Di

Ph.D. in Mathematics

di@xingjian.me (+86) 18621717131 xingjian.me

Education

New York University

Ph.D. in Mathematics

Advisors: Wei Wu (NYU Shanghai) and Nina Holden

Dissertation: Scaling limits of pole-free almost acyclic orientations

Core research areas: random geometry, statistical physics, mathematical physics

University of Illinois at Urbana–Champaign

B.S. in Physics and B.S. in Mathematics

Graduated Magna Cum Laude

Projects

InsiderSpot

Options-Based Insider Trading Detection

  • Built a data pipeline to process large-scale US equity options data (current quotes + historical chains) sourced from Massive
  • Developed volatility surface analysis framework using Python to model implied volatility skew and curvature, term structure, and Greeks

Anime Image Super-Resolution via Deep Learning

  • Implemented a ResNet-based CNN for image denoising and super-resolution using TensorFlow
  • Developed custom video processing filters in C++ using the VapourSynth API for video enhancement
  • Awarded National First Prize in the China Adolescents Science & Technology Innovation Contest

Research Experience

Ph.D. Research

Random Geometry & Statistical Physics

Research on Liouville quantum gravity, imaginary geometry, string theory, and random oriented maps on Riemann surfaces. Also studied loop O(n) models and Manhattan pinball through random walk representations.

Invited Talks

  • University of Warwick — Probability at Warwick Summer School, Jul 2025
  • University of Chicago — Probability and Statistical Physics Seminar, Jan 2025
  • University of Chicago — Two-Dimensional Random Geometry Workshop, Jul 2024
  • Oberwolfach — Arbeitsgemeinschaft in QFT and Stochastic PDEs, Dec 2023

Undergraduate Research

Magnetism & Differential Geometry

Applied Cartan's theory of differential forms to derive conserved momenta of the Belavin–Polyakov skyrmion. Published in SciPost Phys. 11, 108 (2021). DOI: 10.21468/SciPostPhys.11.6.108

Technical Skills

Programming

Python, C++, SageMath

Data Science

pandas, numpy, scipy, matplotlib

Machine Learning

TensorFlow, CNN

Quantitative Finance

Options pricing, volatility surfaces, Greeks

Mathematics

Probability theory, stochastic processes, statistical physics

Tools

Git, LaTeX, typst, Jupyter, Linux, VapourSynth

Teaching

Teaching assistant for Ph.D.-level courses at NYU. Teaching assistant and guest lecturer for undergraduate courses at NYU Shanghai (2022–2025).