Kaili Cao is a PhD candidate in physics at The Ohio State University. He is broadly interested in theoretical and computational aspects of cosmology and astrophysics, focusing on developing novel algorithms and high-performance software pipelines to address key challenges at the intersection of theory and data.

His cosmological research, with Dr. Christopher M. Hirata and Dr. David H. Weinberg, is centered on preparing for NASA’s forthcoming Nancy Grace Roman Space Telescope. As a member of the Roman High Latitude Imaging Survey (HLIS) Cosmology Project Infrastructure Team (PIT), he is a key developer of the IMCOM (image combination) software. He has led a significant refactoring of the IMCOM codebase, implementing new linear algebra strategies that improved its computational performance by an order of magnitude. This work is critical for creating the high-resolution images that will be used for precision weak gravitational lensing measurements. His work in this area extends from these foundational algorithms to cosmological inference, where he uses Fisher forecasting techniques to predict how Roman’s data will constrain our understanding of the universe.

With Dr. Marc H. Pinsonneault, he uses the Modules for Experiments in Stellar Astrophysics (MESA) to model the structure and evolution of red giant stars, testing fundamental theories of stellar physics against observational data from the APOGEE survey and NASA’s Kepler mission. As a member of the Roman Asteroseismology Wide-Field Science (WFS) Team, his research also extends to asteroseismology, where he has developed new statistical methods to more accurately determine the masses and ages of evolved stars.

As an experienced Python programmer, Kaili specializes in writing object-oriented, high-efficiency programs based on libraries like NumPy and Numba. He is also the author of the ContEvol formalism, a novel family of numerical methods.

Links: NASA/ADS (recommended) / GitHub / ResearchGate / INSPIRE / Google Scholar

Last updated: 8/22/2025