Ferran Gamonal is a Computer Vision R&D Engineer with nine years of hands-on experience applying deep learning to real-world video analysis and surveillance problems. Currently at DAVANTIS, he focuses on designing, training and deploying optimized models—particularly for camera tampering detection—and integrates runtime accelerations such as OpenVINO. Trained with a Master's in Computer Vision from a multi-university program, his research background includes variational optical flow and speed-up optimization from a stint at UPF. He blends academic rigor with production engineering, having implemented C++/Bash pipelines for 4K streaming workflows and contributed to cross-disciplinary projects in computational photography, medical imaging and autonomous driving. Based in Badalona, Ferran is known for bringing research-grade methods into efficient, deployable systems and enjoys mixing vision techniques into novel application areas.
9 years of coding experience
1 year of employment as a software developer
Master in Computer Vision, Computer Vision and Pattern Recognition, 8.946/10, Master in Computer Vision, Computer Vision and Pattern Recognition, 8.946/10 at Universitat Autònoma de Barcelona
General Certificate of Education, Technological plan, 7.48/10, General Certificate of Education, Technological plan, 7.48/10 at IES Isaac Albéniz
Contributions:35 commits, 42 pushes, 10 branches in 1 year 6 months
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Ferran Gamonal - Computer Vision R&D Engineer at DAVANTIS