Mario Pasquato
Research Associate (CAP3)
Affiliation: NYU Abu Dhabi
Education: MSc. Scuola Normale Superiore (Pisa, Italy); Ph.D. Università di Pisa (Italy)
Research Websites: Galaxy Formation Group
Research Areas: Machine Learning for Astronomy
Mario Pasquato received his Ph.D. in Physics from Pisa university in 2010. In Pisa he also attended Scuola Normale Superiore, receiving a BSc. (2004) and MSc. (2006).
As a summer intern in Space Telescope Science Institute in Baltimore, MD he developed a strong interest in numerical astronomy, simulating star clusters on a hunt for intermediate-mass black holes. After a brief period in industry and a postdoc in Bologna (Italy) he moved to Yonsei University (Korea) where he spent five years as a fellow, falling in love with machine learning. In 2017 he came back to Padua (Italy) as a MSCA-COFUND fellow at the National Institute of Astrophysics on a mission to bring machine learning techniques to Astronomy.
Mario carries out his research at the CAP3 center at NYUAD, working with Prof. Macciò, among other projects on automated simulation-observation translation (Nihao-Alma) with deep learning and on applying sparse identification techniques to variable stars to infer their governing equations in collaboration with his fellow fellow Moe Abbas.
Current Research
Mario Pasquato's research interests here at CAP3 are:
- Variable star classification (RR Lyrae ab/c and other variables) to obtain better standard candles;
- Automatically learning the oscillator dynamics underlying variable stars;
- Image-to-image translation for converting simulations to observations and vice versa;
- Astrocladistics (cladistics methods from biology applied to galaxies).