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About

Jiyan Dai is a leading researcher at the intersection of artificial intelligence, edge computing, and biomedical engineering. His work focuses on deploying real-time AI systems on resource-constrained devices and advancing AI-driven medical diagnostics. Dai’s most influential contribution is his pioneering approach to real-time object detection on edge devices using TensorFlow Lite, a method that enables accurate, low-latency computer vision for autonomous driving and outdoor robotics without relying on cloud infrastructure—a paper that has garnered 22 citations. He has also shaped the future of healthcare through his visionary article “Artificial intelligence for medicine 2025: Navigating the endless frontier,” which outlines how integrating clinical, imaging, and omics data can revolutionize diagnostics and treatment; this work has already received 21 citations. More recently, Dai developed a novel fiber Bragg grating tactile perception system based on a cross-modal transformer, demonstrating his ability to merge sensor technology with advanced AI architectures for robotic tactile sensing. His research not only pushes the boundaries of efficient AI deployment but also bridges the gap between computational methods and practical medical applications, making him a key figure in the evolution of intelligent systems.