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About

Yu-Lun Chen is a leading researcher in automotive radar systems and intelligent sensing technologies, with a particular focus on surround-view radar architectures for next-generation vehicles. His most-cited work, "Toward Automotive Surround-View Radars" (2019, 34 citations), lays foundational groundwork for integrating multiple radar sensors to create comprehensive 360-degree environmental perception—a critical enabler for autonomous driving and advanced driver-assistance systems (ADAS). Chen’s contributions address the convergence of wireless connectivity, clean energy, and secure transactions in future mobility, envisioning a shift from vehicle ownership to service-based transportation. His research bridges hardware design and system-level integration, helping to make autonomous driving safer and more reliable. By tackling challenges in sensor fusion and real-time data processing, Chen’s work has influenced both academic research and industrial development in automotive radar. His insights into the evolving role of vehicles—whether human-driven or autonomous—underscore his impact on shaping the intelligent transportation systems of tomorrow.