Daniel Oñoro is a research scientist based in Heidelberg with over a decade of experience applying machine learning to image data across domains such as autonomous vehicles, mobile vision, medical imaging, and video surveillance. His research career began in 2009 with the Fast-RNN clustering algorithm and has grown through academic and industry roles, including an ongoing appointment at NEC Laboratories Europe and a PhD in Computer Vision from Universidad de Alcalá. He has hands-on experience delivering production-aware computer vision solutions for Android devices, perception stacks for autonomous systems, and image search engines, often bridging research and engineering by leading teams of engineers and students. Comfortable with sensor fusion, ROS, and embedded perception, he brings a practitioner’s eye for systems that run in constrained environments as well as for large-scale image understanding. Colleagues value him for combining long-term research depth with practical product-oriented development and cross-cultural collaboration across Europe and Asia.
Doctor of Philosophy - PhD, Computer Vision, Doctor of Philosophy - PhD, Computer Vision at Universidad de Alcalá
Örebro University
Engineer's Degree, Perception for Autonomous Vehicles, Master, Engineer's Degree, Perception for Autonomous Vehicles, Master at Korea University of Technology and Education
Contributions:45 commits, 17 pushes, 1 comment in 2 years 9 months
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