ICTS

The astronomical community has entered an era of data-intensive discovery. Observational programs such as DES, DESI, Euclid, JWST, LSST, and ZTF, alongside upcoming facilities like the Roman Space Telescope and the SKAO, promise unprecedented volumes of complex, high-dimensional data, while cosmological simulations continue to grow in scale and complexity. Extracting meaningful physical insight from these datasets increasingly demands tools beyond traditional statistical methods. AI and ML techniques, including deep learning and generative AI, have shown striking success in pattern recognition, generative modelling, uncertainty quantification, and scientific workflow automation.

Yet adoption of AI in astrophysics and cosmology remains uneven, hindered by limited domain-specific training among astronomers, poor interpretability of ML models, and a silo between the astronomy and AI communities. This 12-day workshop brings together early-career researchers, PhD students, postdocs, and junior faculty, with leading international and national experts at the interface of AI/ML and astrophysics.

Structured in three phases (pedagogical foundations, thematic applications, and collaborative ideation), the program moves participants from core concepts to cutting-edge applications in galaxy formation, dark energy, time-domain astronomy, and cosmological simulations, culminating in hands-on collaboration and research planning. Evening talks by academic and industry experts will connect these tools to broader domains such as healthcare, education, and urban mobility.

By building practical bridges between the astronomy and AI communities, the workshop aims to train a generation of astrophysicists who are not just users of AI but informed contributors to its evolution in the sciences.

Eligibility Criteria: Open to early-career researchers – PhD students, postdocs, and junior faculty – in astrophysics, cosmology, data science, or AI/ML with an interest in astronomical applications. Exceptionally qualified Master's/Bachelor's students working in these areas will also be considered. No formal prerequisites; however, familiarity with Python, basic statistics, machine learning, or generative AI will be extremely helpful for the hands-on tutorials.

Accommodation will be provided for outstation participants at our on-campus guest house.

ICTS is committed to building an environment that is inclusive, non-discriminatory, and welcoming of diverse individuals. We especially encourage the participation of women and other under-represented groups.