Biography
Prof. Jee Youl Ryu is a Professor and Co-Supervisor of the laboratory. He has been actively involved in research and education in the areas of System-on-Chip (SoC), VLSI, embedded systems, and computing technologies. His research focuses on designing innovative and efficient computing architectures that address the growing demands of modern intelligent and connected systems. His work also explores the integration of Artificial Intelligence and Machine Learning with advanced hardware architectures, with an emphasis on improving computational performance, energy efficiency, and system reliability. Through research and collaboration, he contributes to the development of emerging technologies for next-generation semiconductor and intelligent computing systems. As a Co-Supervisor, Prof. Ryu provides academic guidance and research mentorship to students and researchers. He encourages interdisciplinary collaboration, innovative thinking, and practical research approaches, supporting the development of new ideas and technologies in the fields of SoC, AI hardware, embedded systems, and advanced computing.
Research Interests
Prof. Jee Youl Ryu's research interests encompass System-on-Chip (SoC) design, VLSI, embedded systems, and advanced computing architectures. His research focuses on developing efficient, reliable, and high-performance hardware and software solutions for next-generation computing systems. System-on-Chip (SoC) Design and Architecture VLSI and Digital System Design Embedded Systems and Computing Hardware–Software Co-Design AI and Machine Learning Hardware Low-Power and High-Performance Computing Semiconductor and Integrated Circuit Technologies Intelligent and Next-Generation Computing Systems
Publications
-
Low-Latency Signal Processing for 5G New Radio
M. Stamm, S. Kris et al. · IEEE Transactions on VLSI Systems (2024)
-
Design and Analysis of Low-Power SRAM Cells
M. Hackett, S. Auer et al. · ACM Transactions on Embedded Computing (2024)
-
Robust Wireless Sensor Network Protocols for IoT Environments
M. Fay, S. Dickens et al. · IEEE Communications Letters (2022)
Students
-
Lee Sun-woo
PhD · Deep Learning for Image Recognition, Hardware accelerator (RTL design)
-
Gi Hong Park
MSc · FPGA-Based Signal Processing
-
Prof. Robbie Von I
BSc · Wireless Sensor Networks
-
Weldon Stanton II
BSc · Optical Fiber Communication