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About

Avinash Singh is a rising star in time-domain astrophysics, whose work is shaping how we discover and classify cosmic transients. His primary research focuses on robotic telescope operations, supernova classification, and the development of machine-learning tools for real-time astronomical analysis. Singh’s most impactful contribution is his leadership in establishing the GROWTH-India Telescope (GIT)—India’s first robotic eye for time-domain astrophysics. This 70 cm facility, with its wide 0.7-degree field of view, represents a major infrastructural achievement, enabling rapid follow-up of transient events and strengthening India’s role in global survey networks. The foundational paper describing GIT has already garnered 31 citations, underscoring its importance to the community. More recently, Singh developed CCSNscore, a multi-input deep learning tool that uses SED-machine spectra to automatically classify core-collapse supernovae. This work, published in 2025, addresses a critical bottleneck in the Zwicky Transient Facility era, where the sheer volume of candidates outpaces human classification. By bridging robotic instrumentation with cutting-edge AI, Singh is not only advancing our understanding of stellar explosions but also building the automated infrastructure essential for the next generation of time-domain surveys.