Physics · Generative Modeling · Scientific ML

Chen Mu

Physics undergraduate at Sun Yat-sen University working on generative modeling, probability transport, scientific machine learning, and AI-assisted research engineering.

CV (PDF) Email GitHub

Institution: Sun Yat-sen University
Program: Physics undergraduate
Location: Shenzhen, China
Period: Sept. 2024–Present
Expected June 2028

Research interests

Generative modeling and scientific research systems

My current interests include diffusion and flow matching, controllable generation, sampling dynamics, ODE/SDE probability transport, scientific machine learning, and AI-assisted scientific workflows. I am particularly enthusiastic about algorithms and operator-based methods, while continuing to build deeper theoretical and practical foundations in these areas.

Selected research

Independent coursework project · 2026

Diffusion, Flow Matching, and CRH-CFG

I independently completed the publicly available coursework and assignments from CMU 10-799, Diffusion and Flow Matching.

Poster (PDF) Paper (PDF) Code / repository

Implemented: DDPM, straight-path Flow Matching, DDIM, Euler and Heun samplers, and conditional classifier-free guidance.
Experiment setting: CelebA 64×64; Modal L40S; independent ResNet-18 evaluator.
Conditional adherence: Joint-target accuracy increased from 3.1% at w = 0 to 94.5% at w = 2. This result indicates stronger adherence, not general image quality.
Sampler comparison: At matched NFE, Heun showed no Pareto improvement.
CRH-CFG probe: Across 1,000 paired seeds per target, the descriptive result was 98.40% → 98.80% (+0.4 pp). It does not demonstrate improved preservation or conditional quality.

Engineering disclosure: Codex assisted engineering; I retained research design, interpretation, and validation.

Scientific modeling

Physics and research engineering projects

Darcy-coupled tumor drug transport

A Mathematica finite-element framework coupling Darcy flow with convection–diffusion–reaction transport for intratumoral drug simulation.

Read project paper (PDF)

Bird-vocalization acoustic features

An automated acoustic feature-extraction workflow developed around bird-vocalization data from the Shenzhen–Hong Kong border.

Read project paper (PDF)

Mathematica-based agent harness

Research engineering for AI-assisted scientific workflows, connecting symbolic computation, experiment execution, and auditable outputs.

Private repository

Profile

Education and skills

Education

Major in Physics
Sun Yat-sen University
Sept. 2024–Present
Expected June 2028 · Shenzhen

Technical skills

Python, C++, C, Wolfram Language
PyTorch and scientific ML
Server administration and Unix-like systems
Docker, LaTeX, and BibTeX
TOEFL iBT 104; CET-6 596

Selected recognition

First Prize, 2nd “Illuminating the Future” Optics Science Communication Writing Competition

UCAS Education Foundation / Wiley · “Chirped Pulse Amplification: Born from Playing with Fire”

USACO Gold

Spring 2026

Contact

Research assistant opportunities

I am seeking research assistant opportunities in computer science and AI, especially projects where a physics background can inform modeling, dynamics, control, or scientific reasoning.

chenm369@mail2.sysu.edu.cn · GitHub · CV (PDF)