photo of Chong Sun

 Professor Chong Sun will be joining CCB on September 1, 2025

Education

Ph.D. in Theoretical Chemistry, California Institute of Technology, 2021 (Garnet Chan)
B.A. in Chemistry, Peking University, 2015 (Hong Jiang, Wenjian Liu)

Biography

Chong’s research focuses on the interface between traditional quantum chemistry and emerging technologies such as artificial intelligence (AI) and quantum information. Her goal is to build a computational platform for understanding intricate chemical and physical phenomena and discovering novel functional materials to support the next wave of the industrial revolution. Chong received her B.A. from Peking University, under the supervision of Profs. Hong Jiang and Wenjian Liu, where she studied spin-crossover materials using density functional theory (DFT) and Monte Carlo simulations. She completed her Ph.D. at Caltech under Prof. Garnet Chan, where she developed classical and quantum algorithms for strongly correlated electrons, including finite-temperature density matrix embedding theory (FT-DMET) and the quantum imaginary time evolution (QITE) algorithm. After her Ph.D., Chong was a postdoctoral researcher with Prof. Alán Aspuru-Guzik at the University of Toronto, where she developed machine learning models for chemical systems, including the neural network quantum state (NNQS) Waveflow and the autoregressive molecular generation model Quetzal. She later worked with Prof. Gustavo Scuseria at Rice University on traditional quantum chemistry methods, where she developed a framework for selected non-orthogonal configuration interaction with single and double excitations (SNOCISD). Chong also has industrial research experience as a scientist at Zapata AI Inc. and Microsoft, where she worked on quantum computing solutions to chemical problems. She will join Rutgers CCB as a faculty member in fall 2025 and looks forward to tackling new scientific challenges with the Rutgers community.

Future Research

Research in the Sun Lab will focus on developing and applying cutting-edge computational tools to tackle challenging problems in chemistry and materials science. The group pursues three independent but highly connected directions: 1) quantum chemistry methodology development, 2) machine learning (ML) and artificial intelligence (AI) for chemistry, and 3) functional materials design. We are particularly interested in designing next-generation clean energy materials, such as organic photovoltaics, and exotic quantum materials for technologies like quantum computing and information storage. The Sun Lab seeks passionate students and researchers interested in solving chemical problems using numerical simulation, data science, AI, and scientific programming. Chong has extensive experience mentoring undergraduate and graduate students, as well as industrial interns. Students joining the group will receive rigorous training in scientific research, gaining skills that are transferable to a wide range of academic and industry roles. If you are interested in joining the Sun Lab, please contact Chong directly at This email address is being protected from spambots. You need JavaScript enabled to view it.

https://sites.rutgers.edu/chong-sun/