As a graduate student in the lab of Prof Xiaosong Li at Chemistry department, Hang worked on developing novel relativistic multireference configuration interaction (MRCI) methods and the corresponding high-performance distributed softwares. The code he developed is able to handle MRCI problems with billions of determinants on a few workstations. He also applies those methods to solve problems such as resolving X-Ray absorption spectra of transition metal complexes and studying non-radiative decay pathways of highly energized matter. In addition, Hang was a trainee of the Clean Energy Institute DIRECT data science program during the 2018 ~ 2019 academic year and he completed the MolES Data Science Option. After graduating in 2023, Hang began his career as a software engineer at Google and works on developing performant networking solutions for high-performance computing and machine learning workloads.