Summary
Pablo Gonzalez is a Computer Vision Engineer with 13 years of experience combining deep academic expertise—PhD in Machine Learning and Computer Vision—with hands-on industry work in real-time GPU algorithms and lightweight ML model deployment. He has led research and implementation efforts spanning semantic segmentation, video prediction, 6D pose and grasp estimation, and synthetic data generation (UnrealROX+) for training vision models. At The TMRW Foundation he built GPU pipelines for real-time human reconstruction from RGB-D streams and deployed ultra-lightweight background segmentation models in MediaPipe, demonstrating production-ready optimization skills. Comfortable with hardware and robotics, Pablo also has CUDA optimization and teaching experience, making him effective at translating research into high-performance, explainable systems. Based in Alicante, Spain, he blends rigorous academic publishing with pragmatic engineering and a talent for clear technical communication and presentations.
13 years of coding experience
7 years of employment as a software developer
PhD in Computer Science, Computer Science, Cum Laude, PhD in Computer Science, Computer Science, Cum Laude at University of Alicante
Master Degree in Computer Graphics, Games and Virtual Reality, Computer Science, 8.28, Master Degree in Computer Graphics, Games and Virtual Reality, Computer Science, 8.28 at King Juan Carlos University
Bachelor Degree in Computer Science, Computer Science, 9.18, Bachelor Degree in Computer Science, Computer Science, 9.18 at Alicante University
English, Spanish, Catalan