Electrical Engineer focused on computer vision, sensor fusion, and embedded ML systems.
Currently pursuing an M.Sc. at UFRGS (PPGEE) on object orientation estimation from RGB images, combining classical CV features and machine learning approaches.
5 years of experience in defense, transportation, and energy sectors, building production-grade systems and leading engineering teams across international programs.
Core areas
- Computer vision — feature extraction, projective geometry, homography, 3D-2D projection, triangulation, terrain matching
- Sensor fusion — image + GPS + IMU, bundle adjustment, real-time localization
- Embedded ML — model training, quantization, on-device deployment (ESP32, Raspberry Pi)
- Systems engineering — V&V, HIL testing, avionics hardware, automated test scripts, requirements traceability, ARP-4754/4761
- Optimization — genetic algorithms, PSO, simulated annealing, applied to CV parameter tuning, hardware design, and ML pipelines
- Data engineering — end-to-end pipelines, REST APIs, SQL, real-time processing
Tech
Selected projects
| Repository | Description |
|---|---|
| object-orientation-estimation | Pose estimation pipeline using HOG, Hu moments, and shape features — trained with sklearn, deployed on ESP32 via emlearn |
| Terrain-Matching | Image-based terrain matching using classical CV features and heuristic optimization |
| Instrumentation_Project | Neural network for density estimation of natural gas samples |
| Quantum-reaction-rate | Deep neural network for chemical reaction rate estimation |
| circuit-optimization | Heuristic optimizer for electronic circuit design |
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