Visiting Researcher at NATO Centre for Maritime Research and Experimentation (CMRE)
Geneva, Geneva, Italy
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Summary
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Rockstar
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Monica Dessole is a computational scientist and research software engineer with seven years’ experience applying high-performance computing, numerical linear algebra, and GPGPU optimization to scientific problems. She holds a PhD in Computational Mathematics from Università di Padova and has transitioned from academic research to applied roles at Leonardo, CERN, and now NATO CMRE as a visiting researcher. Monica contributes to prominent open-source projects such as ROOT, where she optimized matrix and sparse multiplication routines, demonstrating a knack for performance-critical backend work. Her background blends deep mathematical training with hands-on software optimization on modern architectures, and she frequently bridges theory and production-ready implementations. Based in Geneva, she brings a pragmatic focus on accelerating scientific workflows through careful algorithmic and low-level code tuning.
8 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD Computational Mathematics, Doctor of Philosophy - PhD Computational Mathematics at Università degli Studi di Padova
Master 2 Erasmus Student High Performance Computing Simulation specialized in Scientific Computing, Master 2 Erasmus Student High Performance Computing Simulation specialized in Scientific Computing at University of Lille 1 Sciences and Technology
The official repository for ROOT: analyzing, storing and visualizing big data, scientifically
Role in this project:
Back-end Developer
Contributions:44 reviews, 73 PRs, 34 pushes in 2 years 4 months
Contributions summary:Monica primarily contributed to the ROOT project by modifying and extending the matrix and vector math libraries. Their commits included bug fixes for matrix constructors and the implementation of a fast element setter method. Additionally, the user worked on adding dimension fields to vector classes and improving the performance of sparse matrix multiplication. These changes suggest a focus on optimizing core mathematical functionalities within the ROOT framework.
Contributions:126 pushes, 1 branch in 6 years 10 months
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