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Suchetha Cooray
Postdoctoral Scholar, Physics
Suchetha Cooray is a KIPAC Postdoctoral Fellow at Stanford University. His research operates at the intersection of observational data, galaxy formation physics, cosmological theory, and artificial intelligence.
Suchetha is broadly interested in decoding the "cosmic ecosystems" that drive galaxy growth and evolution. His work seeks to reveal the complete lifecycle of galaxies—tracing their origins from density peaks of dark matter, through the complex interaction of their baryonic components, to their eventual cessation of star formation. Galaxy formation presents a profound computational challenge, as physical processes span at least 14 orders of magnitude, from the sub-parsec scales of black hole accretion disks to the vast web of cosmic large-scale structure.
To navigate this complexity, Suchetha employs numerical simulations and machine learning to build statistically robust models of the Universe, connecting the first galaxies revealed by JWST to the mature populations of the present day. As the field enters a transformative decade for precision cosmology, his research focuses on maximizing the scientific insights from upcoming major surveys—including PFS, Euclid, Rubin LSST, SPHEREx, and Roman.
Previously, Suchetha was a JSPS Postdoctoral Fellow at the National Astronomical Observatory of Japan and earned his doctorate at Nagoya University.
Suchetha is broadly interested in decoding the "cosmic ecosystems" that drive galaxy growth and evolution. His work seeks to reveal the complete lifecycle of galaxies—tracing their origins from density peaks of dark matter, through the complex interaction of their baryonic components, to their eventual cessation of star formation. Galaxy formation presents a profound computational challenge, as physical processes span at least 14 orders of magnitude, from the sub-parsec scales of black hole accretion disks to the vast web of cosmic large-scale structure.
To navigate this complexity, Suchetha employs numerical simulations and machine learning to build statistically robust models of the Universe, connecting the first galaxies revealed by JWST to the mature populations of the present day. As the field enters a transformative decade for precision cosmology, his research focuses on maximizing the scientific insights from upcoming major surveys—including PFS, Euclid, Rubin LSST, SPHEREx, and Roman.
Previously, Suchetha was a JSPS Postdoctoral Fellow at the National Astronomical Observatory of Japan and earned his doctorate at Nagoya University.
Research Projects
Artificial Intelligence and Machine Learning
At KIPAC, researchers are working to advance the frontiers of astronomy through the application of AI and machine learning, and simultaneously pushing the frontiers of AI/ML methods in pursuit of astrophysics discovery.
Computational Astrophysics
KIPAC researchers tackle a wide range of computational challenges as part of a mission to bridge the theoretical and experimental physics communities.
Nancy Grace Roman Space Telescope
The Nancy Grace Roman Space Telescope (formerly the Wide Field Infrared Survey Telescope, or WFIRST) is a mission designed to study dark energy, the evolution of galaxies, and the populations of extrasolar planets.Contact
Mail Code
4060