Pietro Peterlongo
Data Scientist Delivery Lead at AgileLab (Consulting in Data for Enterprises), I am passionate about Open Source and Tech communities. Before AgileLab I worked for almost 9 years as a Data Scientist/Software Engineer in a product company for Supply Chain Planning and Optimization. Then I took a sabbatical where I went on a programming retreat (Recurse Center) and went all in on tech communities. I help organize the local Python Milan meetup and helped launch the PyData Milan meetup. I got the programming language bug thanks to an underdog programming language (Nim), this led me into Open Source (Nimib). I have a background as a mathematician and I did not complete a PhD in Math Applied to Climate Dynamics (that brought me to live two years in Paris).
Session
Programming languages used in Scientific Computing have evolved from Fortran to Python, but many languages are still actively used and are important in the ecosystem (C, C++, R). New languages made specifically for solving problems of the scientific ecosystem have been created (Julia). Is there space for one more? Why is Nim, a general purpose statically typed and compiled language, a good fit for Scientific Computing? We will make a quick travel around seven islands that represent important themes where Nim shows its powers. The talk will not hide where Nim falls short.