Giacomo Vianello

Giacomo Vianello has extensive work experience in the field of data science and research. From January 2019 to present, they have been a Distinguished Scientist at CAPE Analytics. Prior to this, they held the positions of Principal Data Scientist, Lead Data Scientist, and Senior Data Scientist at the same company.

In 2018, Giacomo worked as a Data Science Fellow at Insight Data Science, where they developed a tool called rmuse using various technologies such as Keras, TensorFlow, Python, Flask, AWS, HTML, CSS, JavaScript, and WebGL.

From 2010 to 2019, they worked at Stanford University in various roles, including Research Associate and Post-Doctoral student. During this time, they contributed to the development of algorithms and tools for inter-calibration of astronomical instruments, detection and studies of anomalies in astronomical data, and search for gamma-ray counterparts to Gravitational Wave bursts. Giacomo also developed a unique algorithm for the search of anomalies in archival data of the Chandra X-ray telescope and led the development of the Multi-Mission Maximum Likelihood framework.

Before that, from 2006 to 2009, Giacomo was a PhD Student at Iasf Milano.

Giacomo Vianello completed their Bachelor of Science degree in Physics from Università degli Studi di Milano, which they attended from 2000 to 2006. Following this, they pursued a PhD in Astronomy and Astrophysics from Università degli Studi dell'Insubria, where they studied from 2006 to 2009. In addition to their formal education, Giacomo has obtained several certifications to further enhance their knowledge and skills. These include completing the "Fast.ai Deep Learning Part I" course from The Data Institute, University of San Francisco in May 2020, the "Taming Big Data with Apache Spark and Python" course from Udemy in January 2019, and the "Machine Learning" certificate from Coursera Course Certificates in March 2016.