About me

I am a PhD candidate in astrophysics at The National Astronomical Observatories, CAS (NAOC). I am recently working in radio astronomy and data analysis, with a primary focus on the detection and characterization of faint extragalactic HI signals. My research interests lie at the intersection of observational radio astronomy, signal processing, and machine learning, particularly in searching for dark galaxies from HI observation data.

I have extensive experience in processing and analyzing HI radio data, including FITS data cubes, moment map construction, spectral measurements, and source parameter extraction using tools such as SoFiA, and Python-based scientific libraries (e.g., Astropy, SpectralCube). A significant part of my recent work involves applying supervised machine learning methods—such as Random Forest classifiers—for source classification, feature selection, and performance evaluation in HI source catalogs.

My research also includes the study of low-mass and diffuse systems, such as dark galaxy candidates, and the use of multi-resolution or auxiliary observations to improve source validation. I am also interested in reproducible data analysis workflows, and scalable methods suitable for next-generation radio surveys.

This website documents my research projects, codes, notes, and academic activities.