Dr. Mario Damiano
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.
Office: 158-256A
Mail Stop: 158-242
4800 Oak Grove Drive
Pasadena, CA 91109
Astrophysics (MS) - Università degli Studi di Palermo
Physics (BS) - Università degli Studi di Palermo
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 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
Contact
Email: mario.damiano@jpl.nasa.govOffice: 158-256A
Mail Stop: 158-242
4800 Oak Grove Drive
Pasadena, CA 91109
Education
Astrophysics (PhD) - University of LondonAstrophysics (MS) - Università degli Studi di Palermo
Physics (BS) - Università degli Studi di Palermo
Research Interests
Composition and dynamic of exoplanetary atmospheresData 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
