Research & Projects
Research & Projects
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Astrophysics & Astronomy
Astrophysics & Astronomy
THE ASTROPHYSICAL JOURNAL: https://iopscience.iop.org/article/10.3847/1538-4357/adfb7d
Our research (https://www.arxiv.org/abs/2508.09370) delivers a practical advance for astrophysics: a ML approach that reliably classifies the coolest stars and brown dwarfs—objects that dominate our Galaxy and often host planets—without slow, expert-by-eye inspection. Using low-resolution near-infrared spectra, our models achieve ~95% accuracy within one spectral subtype and can also flag key physical traits (surface gravity and metallicity), a capability that scales to the millions of spectra expected from surveys like Gaia, SDSS, and SPHEREx. By automating and standardizing this step, the work accelerates cataloging nearby low-mass objects, improves the search for unusual targets, and strengthens population studies that inform planet formation and Galactic structure.
AcademicPoster_New.pdfAmerican Astronomical Society: https://ui.adsabs.harvard.edu/abs/2024AAS...24333006Z/abstract
We analyzed 219 million low-resolution Gaia DR3 spectra and, after rigorous quality cuts, distilled a high-purity set of 37,945 stellar spectra to build calibrated templates. Anchored to SDSS spectral standards, the library spans 3,360–10,200 Å and includes 201 main-sequence templates across OBAFGKM (subtypes 0–9), plus white dwarfs (DA0.5–DA7.0) and carbon stars (dCG, dCK, dCM). The result is a clean, standardized reference for fast, consistent spectral typing and downstream stellar population studies. Github Repo
American Astronomical Society: https://ui.adsabs.harvard.edu/abs/2025AAS...24546403Z/abstract
We build ML tools that read low-resolution infrared spectra to identify the coolest stars and brown dwarfs (M, L, T) with about 95% accuracy—no hand-typing required. Beyond labels, the models also flag metallicity and surface gravity clues, helping us quickly map and understand our smallest, coolest galactic neighbors.
The study of minor bodies in the Solar System is a fundamental area of research in astrophysics. In our lab, we aimed to apply astrometry to determine the proper motions of asteroids using CCD images obtained from the Direct Imaging Camera on the Nickel telescope at Lick Observatory. We first analyzed the properties of the imaging system and reduced our CCD images using dark and flat field frames to obtain high-quality measurements. We then compared our science images with those in the USNO-B star catalog and performed a fit to determine the plate constants of the imaging system, which enabled us to calculate the standard coordinates of the stars and asteroids. We finally determined the proper motions of asteroid Aline. Through this lab, we have demonstrated the successful application of astrometry in determining the proper motions of asteroids using CCD images.
Astronomical spectroscopy involves the usage of telescopes and spectrographs to investigate the light emitted by objects, which provides us insight into their constituent elements and molecules. In this lab, we used an Ocean Optics spectrometer to analyze the spectrum of particular elements, determining their spectral lines and comparing them with the spectra database from the CRC Handbook of Chemistry & Physics. We also investigated the HgCd and He lamp frames, star J0047+03, and star BD+284211 collected by the KAST spectrograph, processed bias subtraction, and flat field division. By comparing the resulting spectrums to those stored in the KAST database and using the linear fitting method, our results demonstrate a linear relationship between the pixel value and wavelength of the elements present.
This laboratory study aims to explore and characterize the Charged-Coupled Device (CCD), an essential tool in modern astronomy that uses the photoelectric effect to record visible light. Our goal is to operate a CCD detector on the Nickel 1-meter telescope at Lick Observatory, understand its limitations, and analyze the resulting data using Python. This includes investigating physical limitations on light detection, precision of brightness measurement, detector noise, and systematic errors. The hands-on experience will provide us with a comprehensive understanding of photon counting, CCD detector characteristics, and data analysis within a single, condensed exploration.
Talks
Talks
Group Led DI (CCDs and Detector Noise_ Implications for Observational Astrophysics).pdfHolographic Universe and Event Horizon of Blackholes.pdfAI Application
AI Application
Internship Report.pdfWorked on AI Thermal Imaging technology, the algorithm of computer simulation methodology, their application in the electric power industry, wildfire detection, and resource protection. Developed a deliberate proposal for customers needing efficient body temperature screening techniques during the COVID-19 pandemic.
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