znasipak/FastEMRIWaveforms-Soton-Hackathon-2025
Sep 2025 – Sep 2025
1 Month active
Languages Used
CMakePython
Technical Skills
CI/CDCMake configurationGPU programmingPython developmentdata processing
Lorenzo Speri
PROFILE
Lorenzo Speri
Contributed a comprehensive update to the FastEMRIWaveforms-Soton-Hackathon-2025 repository, focusing on enabling multi-backend EMRI waveform generation with both GPU and CPU support. The work involved implementing mode selection functionality, integrating new Python-based data processing scripts, and enhancing CMake configuration to streamline deployment. Improvements to CI/CD workflows and documentation were also delivered, supporting reproducibility and faster release cycles. The technical approach emphasized maintainability and performance, aligning with the project’s hackathon objectives. By addressing both computational and workflow aspects, the update provided a robust foundation for future development and deployment of EMRI waveform generation across diverse hardware environments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
42,235
Activity Months1
Your Network
1 personShared Repositories
1
Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025In Sep 2025, delivered a comprehensive update to the FastEMRIWaveforms project focusing on multi-backend EMRI waveform generation (GPU and CPU) with supporting data processing scripts, enhanced documentation, and CI/CD workflows. Work completed under the Hackathon scope with a merge from the mode-selection-update branch, aligning delivery with performance and deployment readiness.
1 Commits • 1 Features
Sep 1, 2025In Sep 2025, delivered a comprehensive update to the FastEMRIWaveforms project focusing on multi-backend EMRI waveform generation (GPU and CPU) with supporting data processing scripts, enhanced documentation, and CI/CD workflows. Work completed under the Hackathon scope with a merge from the mode-selection-update branch, aligning delivery with performance and deployment readiness.
September 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
CMakePython
Technical Skills
CI/CDCMake configurationGPU programmingPython developmentdata processing
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