Aiden Aiden Ryu
Senior Image Processing Researcher @Faurecia
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WORK HISTORY
Senior Image Processing Researcher @Faurecia
CA
Delivered 11+ successful PoC projects, transitioning advanced algorithms into automotive-grade solutions with 7+ academic papers and 6+ international patents.Research and technical interests include machine learning and analytical approaches for automotive image processing and computer vision, including:Advanced Display Systems: Immersive driving-scene transfer, local dimming compensation, and power-saving algorithms for OLED/Transparent displays.Perceptual Enhancement: Image quality enhancement (IQE) and visibility improvement based on perceptual measurement.In-Cabin Monitoring: Interior monitoring systems (DMS/OMS) and driver attention retargeting.ADAS & Safety: Advanced e-mirror systems and sensor-based ADAS solutions.
EDUCATION
Yonsei University
Doctor of Philosophy (PhD), Electrical and Electronics Engineering
Yonsei University
Bachelor of Science (BS), Electrical and Electronics Engineering
SKILLS
ABOUT AIDEN AIDEN RYU
I am an Applied Research Scientist specializing in computer vision, image processing, and machine learning. My work focuses on transforming early-stage ideas into validated technologies and deployable features through tight alignment between research, engineering, and product teams.Currently at Forvia, I lead research projects end-to-end—from ideation and algorithmic innovation, through PoC development and perceptual validation, to product-level integration. I work closely with software, system, and data engineering teams to ensure research outcomes meet real-world constraints and deliver measurable product impact.Previously, I worked on 3D computer vision, 3D imaging, and deep learning at AIRY3D, and on real-time thermal-based object detection systems for autonomous driving at TOVIS. I earned my Ph.D. from Yonsei University, collaborating with Samsung, LG, Microsoft Research Asia, and government projects, resulting in top-tier publications and patents.My strength lies in bridging exploratory research and engineering execution, connecting novel insights at the edge of existing knowledge into cohesive, system-level solutions.
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