Yen-Lin Lee

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About

Yen-Lin Lee is a leading researcher at the intersection of artificial intelligence and edge computing, with a particular focus on making AI more efficient, accessible, and deployable in real-world environments. His most cited work, “Technology Trend of Edge AI” (2018), has garnered 86 citations and serves as a foundational survey that bridges the gap between cloud-based AI and on-device intelligence. In this influential paper, Lee systematically maps the emerging paradigm of edge AI—where machine learning models are executed locally on devices rather than relying solely on remote servers—highlighting its transformative potential for robotics, smart transportation, healthcare, and mobile systems. His contributions have helped define the core challenges and opportunities in this rapidly evolving field, from model compression to latency-sensitive inference. By synthesizing trends across industry and academia, Lee’s work has guided both researchers and practitioners in navigating the shift toward decentralized intelligence. His research continues to shape how AI systems are designed for efficiency, privacy, and real-time responsiveness, making him a key voice in the ongoing evolution of edge computing and embedded AI.