Bruno Merín



Main Research Fields

We combine multi-wavelength analysis of star-forming regions to study the dissipation of disks and the transitional disks together with studies of young transiting exoplanets around young stars to link the properties of both samples of objects. We foresee observations with JWST, VLT and ALMA among others to support these investigations, including the use of ESA's 1m Optical Ground Station (OGS) for targetted exoplanet transit searches in young star-forming regions.

Recently, we have also started a new line of research on data science on ESA's Space Science Archives, applying Machine Learning algorithms (most typically clustering algorithms, dimensionality reduction algorithms, automatic image classifiers with Convolutional Neural Networks and recommendation engines) to the large datasets in ESA Space Science Archives, hosted at ESAC. The goals of these data science projects are two-fold: on one hand we seek revealing new information in full archival datasets not previously identified with traditional data exploitation methods and on the second hand, we seek identifying operational improvements for the provision of data to the scientists of the future, e.g. by providing advanced embedded data curation and navigation in ESA Science Archives.


  • Star and planet formation
  • Protoplanetary disk evolution
  • Transitional disks
  • Exoplanets
  • Data Science
  • Machine Learning
  • Artificial Intelligence
  • Citizen Science projects

Ongoing collaborations



Project/mission at ESA

ESAC Science Data Centre

Personal Homepage

Research Gate profile

Research Groups at ESAC: Exoplanets and protoplanetary disks group and Machine Learning group

Contact point: Bruno Merín

Interested in an ESA Research Fellowship in our group? Apply before the fall of 2021 (TBC) here.