Candi Zheng

About Me

I am currently pursuing my Ph.D. in a joint program between the Department of Mathematics at Hong Kong University of Science and Technology (HKUST) and the Department of Mechanics and Aerospace Engineering at the Southern University of Science and Technology (SUSTech), superivsed by Professor Yang Wang and Professor Shiyi Chen. My academic background includes a B.S. in Physics from SUSTech and a pure math Ph.D. qualification from HKUST.

Research Interests

I’m interested in bridging artificial intelligence (AI) with non-equilibrium physics, especially focusing on generative modeling and kinetic theory, emphasizing both the insights from physics and mathematical solidity. My current research includes:

• Physics in Generative Modeling: how physics knowledge helps diffusion model and image generation
• Non-Equilibrium Physics: how data-driven approach helps models for kinetic theory, rarefied gas dynamics, shock waves, and light scattering

News

Characteristic Guidance Web UI

We are excited to share our publicly available extension, the Characteristic Guidance Web UI, which provides large CFG (Cassifier-Free Guidance) scale correction for the Stable Diffusion web UI (AUTOMATIC1111).

Moment Gauge

Try our python & JAX library Moment Gauge, designed to facilitate the implementation of numerical solvers using the maximal entropy moment method. Built on the JAX framework, Moment Gauge aims to provide reusable code for researchers and developers working with rarefied gas dynamics and other applications of the maximal entropy moment method.

Publications

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