Fernando Chirigati
Editor In Chief at Springer Nature
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolFernando Chirigati is Editor in Chief of Nature Computational Science and a PhD-trained computer scientist with 14 years of research and editorial experience at the intersection of computational methods and real-world science. He transitioned from a strong academic track—PhD and postdoc at NYU Tandon, multiple summer research internships at Google and IBM, and early research at UFRJ—into leading a high-profile Nature Research journal that shapes cross-disciplinary computational work. Fernando combines deep expertise in data and database research with hands-on experience mentoring and managing peer review of cutting-edge algorithmic and tool-building studies. Based in New York but originally from Petrópolis, Brazil, he brings an international perspective and a long-standing commitment to reproducible, infrastructure-focused research that supports large scientific experiments. An attentive curator of interdisciplinary scholarship, he uniquely understands both the technical rigor of research and the editorial skill needed to translate it for broad scientific impact.
14 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at NYU Tandon School of EngineeringBachelor of Engineering (B.E.), Computer Engineering, Bachelor of Engineering (B.E.), Computer Engineering at Universidade Federal do Rio de JaneiroComputer Engineering, Computer Engineering at University of Central Florida
English, Portuguese
Github Skills (33)
reproducible-research10
docker10
archiving10
reproducible-science10
python10
computational-science10
linux10
temporal-data10
ptrace10
versioning10
science10
vagrant10
dataset-search10
data-science9
visualization9
Programming languages (5)
Github contributions (5)
ViDA-NYU/mongodb-vls
Jan 2016 - May 2016
Contributions:12 commits, 7 pushes, 1 branch in 4 months
VIDA-NYU/data-polygamy
Apr 2016 - Jun 2018
Data Polygamy is a topology-based framework that allows users to query for statistically significant relationships between spatio-temporal data sets.
Contributions:1 release, 198 commits, 172 pushes in 2 years 2 months
temporal-datanyucdsdatadata-science
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.