Mandy Chen

Mandy Chen is an observational astronomer affiliated with the California Institute of Technology and the Carnegie Observatories. She earned her PhD in 2024 from the University of Chicago under Prof. Hsiao-Wen Chen. Her research focuses on the cosmic baryon cycle, particularly the dynamics and properties of the circumgalactic medium (CGM) around galaxies, utilizing integral-field spectroscopy from instruments like VLT/MUSE and JWST/NIRSpec. She is a core member of the Cosmic Ultraviolet Baryon Survey (CUBS) collaboration, contributing to studies of quasar nebulae, turbulence in CGM, and galaxy feedback processes.

Her work combines observational techniques with advanced data analysis, including gravitational lensing modeling and machine learning applications. Key projects include analyzing 3D IFU datacubes to study CGM emission, investigating turbulence drivers in obscured quasars, and exploring the interplay between AGN activity and galaxy evolution. She has presented her research at institutions such as the University of Cambridge, the Chinese University of Hong Kong, and Ohio State University.

Chen is also actively involved in software development for astronomical data analysis, with GitHub repositories focusing on emission line fitting, spectral visualization tools (fitviz), and deep learning applications in astrophysics (DeepNoise). Her research interests extend to diversity and inclusion in STEM, reflecting her background growing up in Guizhou, China, and her education at the University of Hong Kong and the University of Chicago.