Projects

Research code, open-source tools, and academic resources.

Research Code

GradTDDFT

A JAX-based differentiable implementation of time-dependent density functional theory (TDDFT). Provides end-to-end differentiable SCF calculations, Casida equations, and neural network exchange-correlation functional training. Supports GPU acceleration via CUDA J/K integral experiments.

GradTDDFT overview
Python MIT license ★ 1 Updated Jun 2026
deep-learningdifferentiable-programmingquantum-chemistry-programs

QHformer

A SO(3)-equivariant neural network for predicting quantum Hamiltonian matrices from molecular geometries. Combines hybrid attention mechanisms with equivariant architectures for accurate Hamiltonian prediction in quantum chemistry applications.

QHformer overview
Python MIT license ★ 0 Updated May 2026
attention-mechanismequivariant-networkgraph-neural-networksquantum-chemistry
🧠 3D Model Architecture Graph

OPTXC

A machine learning toolkit for optimizing exchange-correlation functionals in linear-response TDDFT calculations. Supports multiple functionals (LC-wPBE, wB97XD) and optimization models (XGBoost, Random Forest, Gradient Boosting, CatBoost). Transforms SMILES strings into molecular descriptors for functional optimization.

Jupyter Notebook ★ 0 Updated May 2026
density-functional-theorymachine-learningquantum-chemistrytime-dependent