Software

I’m committed to providing open-source software and tools for the scientific community. My GitHub page can be found here. Below are software tools from my publications and tools I contributed to during my time in industry.


Research Themes: (select to filter) molecular representationdesign and optimizationpredictive chemistryautomationdata


MolGEN

GitHub: https://github.com/tuoping/MolGEN


MolGEN is an open source conditional generative modeling package that couples the state-of-the-art flow matching frameworks with equivariant transformers. The framework can be easily adapted to evaluate the free energy surfaces, metastability, and generate kinetic pathways.

predictive chemistry

alchemicalFES

GitHub: https://github.com/tuoping/alchemicalFES


alchemicalFES implements free energy sampling of the alchemical space based on flow matching of the Dirichlet distribution and achieves multi-temperature generation with a light-weight CNN model by reformulating the guidance technique.

predictive chemistry


Open software that I contribute to

OpenScience

Website: https://openscienceteam.github.io/OpenScience/
GitHub: https://github.com/OpenScienceTeam/OpenScience


OpenScience is an open-source course knowledge base spanning multiple disciplines including physics, chemistry, and computer science.

data

deepmd-kit

GitHub: https://github.com/deepmodeling/deepmd-kit


DeePMD-kit is a package written in Python/C++, designed to minimize the effort required to build deep learning-based model of interatomic potential energy and force field and to perform molecular dynamics (MD). This brings new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Applications of DeePMD-kit span from finite molecules to extended systems and from metallic systems to chemically bonded systems.

molecular representationpredictive chemistry

dpgen

GitHub: https://github.com/deepmodeling/dpgen


DP-GEN (Deep Potential GENerator) is a software written in Python, delicately designed to generate a deep learning based model of interatomic potential energy and force field. DP-GEN is dependent on DeePMD-kit. With highly scalable interface with common softwares for molecular simulation, DP-GEN is capable to automatically prepare scripts and maintain job queues on HPC machines (High Performance Cluster) and analyze results.

dataautomation

dpdata

GitHub: https://github.com/deepmodeling/dpdata


dpdata is a python package for manipulating DeePMD-kit, VASP, LAMMPS data formats. dpdata only works with python 3.x.

dataautomation

dpdispatcher

GitHub: https://github.com/deepmodeling/dpdispatcher


DPDispatcher is a Python package used to generate HPC (High-Performance Computing) scheduler systems (Slurm/PBS/LSF/Bohrium) jobs input scripts, submit them to HPC systems, and poke until they finish.

dataautomation