Riccardo Bertoglio
Junior Research Scientist at INRAE
Clermont-Ferrand, Auvergne-Rhône-Alpes, France
Summary
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Senior🎓
Top SchoolRiccardo Bertoglio is a junior research scientist with a decade of experience combining AI, machine learning, and robotics to make agriculture more sustainable and efficient. He holds an MSc in Computer Science Engineering and a PhD in Data Analytics and Decision Sciences, and has applied advanced ML techniques to crop detection and agricultural robotics at Politecnico di Milano and now INRAE. Beyond research, he teaches practical data science and hands-on computer vision labs, translating complex models into usable tools for students and practitioners. He has contributed backend optimizations to the widely used bibliometrix R package, improving performance of co-occurrence matrix computations and related visualization functions. Fluent in Python, PyTorch Lightning, and data engineering with a penchant for pragmatic performance fixes, he blends rigorous research with real-world impact in precision agriculture.
10 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD Data Analytics and Decision Sciences, Doctor of Philosophy - PhD Data Analytics and Decision Sciences at Politecnico di MilanoRagioniere programmatore Amministrazione Finanza e Marketing Sistemi informativi Aziendali (Ex corso Mercurio), Ragioniere programmatore Amministrazione Finanza e Marketing Sistemi informativi Aziendali (Ex corso Mercurio) at I.T.C. E. BELTRAMI
English, Italian, French
Github Skills (3)
r10
githubaction-workflow3
github-ci3
Programming languages (8)
Github contributions (5)
massimoaria/bibliometrix
Dec 2020 - Dec 2020
An R-tool for comprehensive science mapping analysis. A package for quantitative research in scientometrics and bibliometrics.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:7 commits, 3 PRs, 28 comments in 3 days
Contributions summary:Riccardo focused on optimizing the `cocMatrix` function within the `bibliometrix` R package. They addressed allocation problems by strategically selecting frequently occurring field values. Further contributions involved adapting `cocMatrix` optimizations to the `biblioshiny` application and other functions, including `thematicMap`, and `intellectualStructure`, ultimately improving performance. The user also addressed identified issues, such as missing brackets in the code.
correspondence-analysisquantitative-analysisrjournalbibliometrics
ricber/iacv_project
Jan 2019 - Jan 2019
Contributions:29 commits, 27 pushes, 1 branch in 1 day
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