PhD Student, University of Delaware
I'm Siddharth Chaini, or Sid for short.
I'm currently pursuing my PhD at the Department of Physics and Astronomy, University of Delaware. My work is at the intersection of computer programming, data science, physics, and astronomy. I'm particularly interested in:
When I'm not working on research, I enjoy watching and playing football (soccer), coding for fun (automating the boring stuff!), and bicycling.
Here are some highlights of the projects I have worked on:
My latest project, DistClassiPy, is a Python library that introduces a novel classifier capable of utilizing multiple distance metrics for classification tasks. This library was specifically applied to the analysis of light curves from variable stars observed by the Zwicky Transient Facility (ZTF). For a detailed exploration of this project, please refer to our published paper here or on (arXiv).
One of my recent projects involved a comprehensive comparison of a Milky Way kinematics model, initially developed using Sloan Digital Sky Survey (SDSS) data, with the more recent Gaia (DR3) data. The findings of this study are detailed in our published paper, accessible here or on (arXiv).
As part of my research, I contributed to the enhancement of feature extraction techniques for the RESSPECT project. Our approach involved the application of curve fitting methods and deep learning algorithms, specifically GP-VAE, to derive meaningful features from light curves. For a more detailed exploration of this project, please visit the project page.
My research involved the application of deep learning techniques for the photometric classification of compact images from the Sloan Digital Sky Survey, distinguishing between galaxies, stars, and quasars. For a detailed exploration of this project, please refer to our published paper hereor on (arXiv).
As part of a course project, I tackled the PLAsTiCC data challenge. In this, we employed a stacked ensemble of GRU and Dense networks to classify simulated light curves. For more details, please check it out on (arXiv).
If you have any questions about my research, wish to discuss potential collaborations, or have spotted a bug in my code, please feel free to contact me! You can reach me via email at chaini@udel.edu.