Mario Damiano

Ph.D. in Astrophysics

Contact

• Address: 4800 Oak Grove Dr, M/S 158-222D, 91109, Pasadena, CA, United States
• Mobile: +1 (818) 928-9338
• Mail: mario.damiano@jpl.nasa.gov

About Me

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.

Research interests

• Characterization of exoplanetary atmospheres.
• Spectroscopic data interpretation from observations gathered via space- and ground-based facilities.
• Implementation of inverse information extraction techniques via Bayesian statistics.
• Automation of data evaluation processes leveraging Machine Learning (ML) algorithms.
• Formulation of comprehensive pipelines for streamlined data analysis.
• echnical and scientific interpretation of data patterns and model predictions.

Professional experience

• Scientist & Data Scientist, NASA / Jet Propulsion Laboratory – California Institute of Technology. CA, United States. October 2022 - today.
• JPL Postdoctoral Fellow, NASA / Jet Propulsion Laboratory – California Institute of Technology. CA, United States. November 2018 - October 2022.
• Research Associate, National Institute of Astrophysics Palermo Observatory (INAF-OAPa). Palermo, Italy. December 2015 - December 2020.

Education

• PhD in Astronomy
  December 2015 – January 2019
  Department of Physics and Astronomy, University College London, United Kingdom.
  Thesis title: "From space to ground: planetary atmospheres revealed through a machine learning approach".
  Subjects: Transmission spectroscopy of exoplanets with the HST/WFC3 camera, data analysis, atmoshperic retrievals, high-resolution spectral data analysis, machine learning, spectroscopy.
  Supervisors: Prof. Giovanna Tinetti, Dr. Giuseppina Micela, and Dr. Ingo P. Waldmann.

• MSc in Physics
  December 2013 – October 2015
  Department of Physics and Chemistry, University of Palermo, Italy.
  Thesis title: "Exoplanetary atmospheres: simulation of high-resolution spectra for the iLocator and the HIRES instruments".
  Subjects: Transit modelling, simulating high-resolution spectral observations, data analysis and atmospheric characterization.
  Supervisors: Prof. Giovanni Peres and Dr. Giuseppina Micela.

• BSc in Physics Science
  November 2010 – December 2013
  Department of Physics and Chemistry, University of Palermo, Italy.
  Thesis title: "Exoplanets and stellar activity in the IR-band".
  Subjects: Transit modelling, stellar activity, effects of stellar activity to the planetary transits.
  Supervisors: Prof. Giovanni Peres and Dr. Giuseppina Micela.

Grants and Fellowships

• Multiple awarded STScI grants for HST and JWST observations, 2020-present.
• Jet Propulsion Laboratory (JPL/Caltech) Postdoctoral Fellowship, November 2018.
• ERC-INAF PhD studentship, December 2015.

Awards and Honors

• "JPL Voyager Bonus Awards" (2024), March and August 2024.
• "Tessera Preziosa del mosaico di Palermo", recognition for outstanding citizens of Palermo, September 2018.

Skills

• Languages
  • Italian (native)
  • English (proficient)
• Computing
  • Operating systems: Mac OS (excellent), Linux (excellent), Windows (excellent).
  • Programming: Python (excellent, including the most important libraries for data analysis and machine learning), Matlab (basic), C (basic).
  • Other: LaTeX (excellent), Apple softwares (excellent), Microsoft Office (excellent).

External personal pages

• NASA / Jet Propulsion Laboratory - Caltech | Mario Damiano's page