Summary
Gabriel Humpire-mamani is a Senior AI Researcher with 15 years working at the intersection of computer vision and applied AI, and eight years of industry experience delivering research-grade systems into production. He earned a PhD in medical imaging with highly cited work and a pending patent on CT segmentation, then transitioned to lead cross-functional teams that recovered delayed projects and improved real-time system performance by 30%. Hands-on across the stack, he builds pipelines in Python and C++, trains and optimizes models in TensorFlow/PyTorch, deploys with TensorRT/OpenCV, and fine-tunes LLMs and diffusion models for generative 3D and vision tasks. Recent work includes automating 3D product design from text prompts using LLMs, diffusion and NeRFs and deploying autonomous drone vision systems with strict latency constraints. He balances technical leadership and mentorship, driving both precision-critical AI (90%+ precision in industrial settings) and scalable production engineering. Based in Barcelona, he focuses on next-generation vision systems that marry accuracy, reliability, and real-world impact.
8 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy - PhD Machine learning applied to medical imaging, Doctor of Philosophy - PhD Machine learning applied to medical imaging at Radboud University
Master's degree Computer Science, Master's degree Computer Science at USP - Universidade de São Paulo
Bachelor's degree Computer Science, Bachelor's degree Computer Science at Universidad Nacional de San Agustín
Spanish, English, Portuguese