Rafa Garnero

MSc Photonics graduate (UPC/ICFO, Sep 2026) with hands-on experience in photonic integrated circuit characterization and LiDAR-based sensing systems. Skilled in optical transmission measurements on silicon-based PICs, Python-driven data analysis, and algorithm development for 3D point cloud processing and multi-target tracking. Seeking an R&D or engineering role in photonic integration, sensing, or space and defense applications.

Master's Thesis — Automated Detection Strategies in LiDAR Sensing for Small Targets at CD6 — Centre for Sensors, Instruments and Systems Development (2026-01 – Present)

• Developed full 3D point cloud processing pipeline using Open3D: voxel downsampling, RANSAC ground plane removal, and adaptive DBSCAN clustering, applied to a proprietary LiDAR sensor dataset.
• Implemented multi-target Kalman filter tracker with greedy nearest-neighbour association, benchmarked against online SOTA LiDAR drone detection methods (performance metrics confidential).
• Built modular Python scripts for segmentation, statistical filtering, object tracking, and performance evaluation.
• Explored computer vision and ML techniques for target discrimination in cluttered environments.

Bachelor's Final Project — Characterisation of PICs in Nanocrystalline Silicon at Nanophotonics Technology Center (NTC) — European project MAGNIFIC (2025-02 – 2025-06)

• Characterised nanocrystalline silicon optomechanical cavities (symmetric and asymmetric) using loop fibre coupling, tunable laser sources, and optical power meters.
• Performed optical transmission measurements and extracted cavity Q-factors via Python and MATLAB analysis.
• Compared nanocrystalline silicon with SOI platform for photonic integration suitability.

MSc in Photonics in Photonics – UPC / ICFO / UB / UAB (2025-09 – 2026-09)

Bachelor's Degree in Physics Engineering – Universidad Politecnica de Valencia (2021-09 – 2025-01)

High School Exchange Programme – Ennis Community College (2018-08 – 2019-01)