Sreevarsha sreejith

Astrophysicist & Machine Learning Researcher working on anomaly detection in large-scale sky surveys.

My research focuses on machine-learning and statistical methods for large astronomical imaging and time-domain surveys, with applications in extragalactic astrophysics, supernova cosmology, and time-domain astronomy. I develop methods for astronomical image analysis, including galaxy morphology studies and automated pipelines for large survey datasets such as LSST and Euclid.

A mosaic of galaxy images from the Euclid telescope.
Figure showing some typical results from the ×PSF-×iPSF-×iPSF1 network for image reconstruction after PSF deconvolution (Sreejith, Slosar & Wang, 2024).
 Illustration of the var_blend artefact label (Sreejith + 2026).
Comparison of RDN & SExtractor in deblending images (Wang, Sreejith + 2022).