THIS IS A DRAFT Jose M. Diego is a Spanish astrophysicist working on dark matter, gravitational lensing, galaxy clusters, and cosmology[1]. His research focuses on using galaxy clusters, (the largest reservoirs of dark matter in the universe), as tools to study the mysterious dark matter. He participated in the discovery of Icarus, the farthest star ever observed and has made key contributions in the field of microlensing near critical curves[2], or interference of gravitational waves due to microlensing [3]. He also discovered the lensed stars Godzilla, Quyllur and Mothra.
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Diego draft is…
Early life
editHe was born in Cantabria, in the North coast of Spain. He graduated in Physics in the University of Cantabria in the year 1996.
Career
editHe obtained his PhD in 2000 from the University of Cantabria. During his thesis he studied the Cosmic Microwave Background and the Sunyaev-Zeldovich effect. After his PhD he moved to the University of Oxford as a Marie Curie fellow where he continued working on the Sunyaev-Zeldovich effect. In 2003 he moved to the University of Pennsylvania and in 2004 he moved to MIT. During this period he worked on galaxy clusters and started working on gravitational lensing. He developed the code WSLAP+ in 2005, which has been used to study the gravitational lensing effect in galaxy clusters.
In 2005 he obtained a Ramon y Cajal contract and returned to Spain. In 2009 he joined the Consejo Superior de Investigaciones Cientificas as a staff researcher. After his return to Spain he became a Planck Scientist continued working on galaxy clusters in preparation for ESA's Planck mission. Hos work during these years focused on the study of the Sunyaev-eldovich effect in galaxy clusters with Plank data. Between 2011 and 2013 he was director of the Observatorio Astronómico de Cantabria] [4], an outreach and research facility of the Government of Cantabria. In 2014 he stared working more intensely on the gravitational lensing effect in galaxy clusters using data from the Hubble Frontier Fields program, that provided the best data set for this kind of study at the time.
Awards
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