Hongjin Wang is a PhD candidate in the Applied Physics & Applied Mathematics Department (APAM) at Columbia University, where he specializes in computational mineral physics. Since joining Columbia in Spring 2021, his work has focused on understanding the behavior of hydrous minerals in subduction zones, particularly serpentines and related phases that influence water transport into Earth’s deep interior. His research integrates density functional theory, molecular dynamics, and advanced machine-learning potentials to model the structure, stability, and thermoelastic properties of minerals under high-pressure, high-temperature conditions. He develops and applies computational frameworks to explore how hydration affects mineral behavior across geophysical environments. Hongjin’s broader interests span mineral physics, materials modeling, and machine-learning–accelerated simulations for Earth and planetary sciences. He is pursuing his PhD at Columbia Engineering’s Fu Foundation School of Engineering and Applied Science (SEAS).

Contact: hw2626@columbia.edu