Shoubaneh Hemmati

Shoubaneh "Shooby" Hemmati is an early career Staff Scientist at the Infrared Processing and Analysis Center (IPAC) at the California Institute of Technology. She works for the Euclid NASA Science Center at IPAC (ENSCI) and the NASA/IPAC Infrared Science Archive (IRSA), supporting US-based investigations that use Euclid data and managing infrared astronomy data archives.

Dr. Hemmati completed her undergraduate studies in Physics in Iran before moving to the United States. She earned her Ph.D. under the supervision of Dr. Bahram Mobasher at UC Riverside, followed by postdoctoral positions at IPAC with Dr. Peter Capak and at NASA JPL with Dr. Eric Huff. She was encouraged to apply for her current position at IPAC and values working in an environment with "great" culture surrounded by leading researchers in the field.

Dr. Hemmati specializes in applying machine learning techniques to problems in cosmology and galaxy formation and evolution. Her research focuses on the intersection of artificial intelligence and cosmology, particularly exploring potential connections between AI, dark matter, and dark energy. She has investigated how training deep learning architectures with archival data can enhance galaxy images, representing the boundless possibilities of AI-driven exploration in astronomy. She is particularly interested in image enhancement with deep learning for astronomical applications, which has significant potential for advancing observational astronomy.

As a member of the IPAC scientific staff, Dr. Hemmati contributes to major space missions including the Euclid mission, a European Space Agency mission with NASA participation designed to study the geometry and nature of the dark Universe. She has conducted observing runs using Hawaii's Keck telescopes and received the NASA Postdoctoral Fellowship, which held special significance given her childhood admiration for NASA.