SpazioDati srl
Matteo Franchi has a diverse work experience in the field of data science and physics. Matteo started their career as a Museum Educator at MUSE - Museo delle Scienze in 2006 and later worked as a Social Networking and Web 2.0 Developer within the same organization. In 2010, they joined the University of Trento as a Ph.D. Student in Physics, where they conducted research on chaotic time series and developed new analytic approaches using various programming languages. While pursuing their Ph.D., they also served as a Graduate Teaching Assistant and Tutor, providing support and assistance in various physics courses. In 2015, Matteo transitioned to the industry and joined Atooma as a Data Scientist, where they worked until 2017, taking on the additional role of CTO. Following this, they joined Resonance AI as a Lead Data Scientist for a period of 9 months. Most recently, they have been working at SpazioDati srl as a Data Scientist since June 2017.
Matteo Franchi obtained a Bachelor's degree in Physics from Università di Trento, where they studied from 2005 to 2008. Matteo then pursued a Master's degree in Physics from both Università di Trento (2008-2011) and Lund University (2009-2010). Matteo continued their education at Università di Trento, completing their Doctor of Philosophy (Ph.D.) degree in Physics from 2011 to 2015.
In addition to their formal education, Matteo also obtained various certifications. In 2003, they received the European Computer Driving Licence from the Associazione Italiana per l'Informatica ed il Calcolo Automatico. Later, in 2015, they completed the course "Image and video processing: From Mars to Hollywood with a stop at the hospital" from Coursera. Matteo expanded their knowledge in the field of Artificial Intelligence by completing the certifications "Deep Learning" in 2016 and "Artificial Intelligence" in 2017, both from Udacity.
SpazioDati srl
By leveraging Big Data, Machine Learning & Semantic Web techs we are building a high-quality knowledge-graph derived from hundreds of sources. The graph powers Dandelion API, a state-of-the-art text analytics SaaS engine available at dandelion.eu ,and Atoka, next generation Sales & Marketing Intelligence platform available at atoka.io.From text to actionable data: extract meaning from unstructured text and put it in context with a simple API. We support a wide range of use cases like: enriching existing databases, building smart search engines and recommender systems on document collections, adding location knowledge to web apps, automatically tagging products on e-commerce sites, using data to create infographics and marketing research and many more!