Machine Learning and Instrument Autonomy Group

     Mario Damiano obtained his BSc in physics and MSc degree in astrophysics at the University of Palermo in Italy (UNIPA). Since then, Mario has been studying the atmospheric characteristics of extrasolar planets.

     Mario received his Ph.D. at the University College London (UCL). During his Ph.D. he worked on the analysis of data taken from space satellites (e.g., Hubble Space Telescope) and ground facilities (e.g., Very Large Telescope). The Ph.D. was funded by the European Research Council (ERC) and the National Institute of Astrophysics (INAF).

     Since 2018, he is employed at the Jet Propulsion Laboratory (NASA/JPL). Mario performs data analysis (of HST and JWST observations) to study and to interpret the spectroscopic characteristics of exoplanetary atmospheres to unveil atmospheric composition and dynamics of these alien worlds. In particular, he focuses on the development of Bayesian retrieval frameworks that can extract information form exoplanetary reflected light spectra. Mario is also an enthusiast of deep learning and AI, and he is exploring the possibilities of implementing such powerful algorithms into his research.

Find my publications on Google Scholar


Office: 158-256A

Mail Stop: 158-242
4800 Oak Grove Drive
Pasadena, CA 91109


Astrophysics (PhD) - University of London
Astrophysics (MS) - Università degli Studi di Palermo
Physics (BS) - Università degli Studi di Palermo

Research Interests

Composition and dynamic of exoplanetary atmospheres
Data analysis of observations taken from space and ground facilities
Interpretation of atmospheric spectra through Bayesian retrieval process
Development of deep learning algorithms for data analysis

Mario Damiano