It gives a perspective on the progress of AI tools in computational chemistry through the lens of his decade-long contributions put in the wider context of the trends in this rapidly expanding field.

Recently, the Chung group at Southern University of Science and Technology (SUSTech) has combined efficient machine learning potentials (MLPs) with multi-scale quantum refinement methods to enhance computational efficiency and reliability.

MLatom 3 is a program package designed to leverage the power of ML to enhance typical computational chemistry simulations and to create complex workflows.

GICnet models are analytical representation of molecules and chemical reactions in four-dimensional spacetime!

XACS team in collaboration with Mario Barbatti and groups in Warsaw University and Zhejiang lab has recently published a paper in JCTC about the versatile Python implementation of surface-hopping dynamics.