Chiara Lepore

Chiara Lepore has extensive experience in climate change research and data analysis. Chiara currently works at Gro Intelligence as a Climate Change Data Scientist since 2022. Prior to that, they worked at Columbia University - Lamont-Doherty Earth Observatory as an Associate Research Scientist from 2014 to 2022. In this role, they led various projects involving cloud-based computing, development of Python packages, and forecasting models for severe weather activity. From 2008 to 2013, they were a Postdoctoral Associate at Massachusetts Institute of Technology, where they focused on landslide susceptibility and slope instability modeling. Additionally, Chiara worked as a Research Fellow at Instituto do Mar in 2007, conducting statistical analysis and developing rainfall hazard assessments. Chiara began their career as a student and PhD student at the University of Salerno from 1998 to 2005.

Chiara Lepore has a significant background in civil and environmental engineering with a focus on hydrology. Chiara pursued their education at the Università degli Studi di Salerno, where they completed a 5-year degree in Civil and Environmental Engineering from 1998 to 2004. Afterward, they furthered their studies at the same institution and obtained a PhD in Civil and Environmental Engineering specifically in hydrology from 2004 to 2007.

In 2006, Chiara Lepore had the opportunity to enhance their knowledge and expertise by attending the Massachusetts Institute of Technology (MIT) as a visiting scholar. During this period, they focused on hydrology, consolidating their understanding of the subject.

Summarizing their educational journey, from 1998 to 2004, Lepore earned a 5-year degree in Civil and Environmental Engineering from the Università degli Studi di Salerno. Chiara then pursued an advanced degree, completing a PhD in Civil and Environmental Engineering with a specialization in hydrology from 2004 to 2007. Additionally, in 2006, they engaged in a visiting scholar program at MIT to further their expertise in hydrology.