Summary
Evin Örnek is a Computer Vision and Machine Learning Engineer with 11 years of experience, currently working on 3D scene understanding at Apple after a PhD stint at TUM focused on monocular depth and representation learning. She has a strong track record translating research into product-ready solutions, including SOTA work on generalizable 6-DoF pose estimation at Meta and on-device integration for XR. Her background spans robotics and embodied perception (Amazon Astro, Max Planck) and vision-language zero-shot learning, with publications and demos across IROS, CVPR workshops and IEEE Robotics and Automation Letters. Evin combines rigorous academic training (TUM PhD/MSc, Bogazici BS, KU Leuven exchange) with hands-on systems experience from industry internships at Google and startups, making her adept at shipping robust, generalizable models under practical constraints. Notably, she has secured a Google research gift during her PhD, reflecting early recognition of her work’s impact.
10 years of coding experience
2 years of employment as a software developer
Master's degree Erasmus Exchange, Computer Science, Master's degree Erasmus Exchange, Computer Science at KU Leuven
Master of Science - MS, Informatics, 1,3, Master of Science - MS, Informatics, 1,3 at Technical University Munich
High School, Science and Maths, High School, Science and Maths at Ankara Atatürk Anadolu Lisesi
Bachelor of Science (BS), Computer Engineering, Bachelor of Science (BS), Computer Engineering at Boğaziçi Üniversitesi / Bogazici University
Turkish, English, Spanish, German