Low-Power and High-Performance VLSI Laboratory
Research Field
Dr. Lih-Yih Chiou is a full Professor in the Department of Electrical Engineering at National Cheng Kung University. He currently serves as the Program Director for Integrated Circuit Design at the Academy of Innovative Semiconductor and Sustainable Manufacturing and as the Chief Technology Officer for the Miin-Wu School of Computing, expanding the impact on the integrated circuit design domain through education, research, and international collaboration.
Our laboratory develops next-generation, power-efficient circuits and systems by integrating hardware innovation with software optimization. As a hardware-intensive group, we offer students the rare chance to bridge theoretical architecture and physical silicon via frequent IC tape-outs. Our research follows two pillars: Frontier Edge Intelligence, pioneering CIM-based transformers, high-efficiency accelerators, and brain-inspired Spiking Neural Networks; and Secure Cyber-Physical Architectures, focusing on RISC-V SoC platforms with post-quantum cryptographic engines and hardware-security primitives. We emphasize the physical realization and rigorous validation of hardware architectures ready for the next wave of secure, autonomous computing.
His research expertise spans energy-efficient VLSI design, encompassing emerging memory circuits, processing-in-memory, and hardware security for edge devices. He has demonstrated a significant impact through over 60 peer-reviewed publications, 21 granted patents (in Taiwan, the US, and internationally), and five successful technology transfers. His extensive industry and National Science and Technology Council project experience includes (1) the design and tape-out of high-energy-efficient CIM-based accelerators for CNNs and LLMs, (2) the development and tape-out of robust hardware security circuits and systems for edge devices, (3) innovative circuit and system designs leveraging non-volatile ReRAM, and (4) comprehensive power and thermal analysis for System-on-Chip architectures.
- General Chair, the 36th VLSI Design/CAD Symposium, 2026
- Executive Committee Member, RISC-V Taiwan Association, 2025 - Date
- Member of the Council, Taiwan IC Design Society (TICD), Taiwan, 2024- Date
- Third Prize in the design category (out of 200 teams), 19th Macronix Golden Silicon Award, Taiwan, 2022
- Third Prize in the design category (out of 253 teams), 17th Macronix Golden Silicon Award, Taiwan, 2020
- Future Tech Award, Ministry of Science and Technology, Taiwan, 2019
- Best Paper Award, 2018 Int. SoC Design Conference, 2018
- General Chair, 2018 Int. Sym. on VLSI-DAT, 2018
- Outstanding Award for Student Mentoring, College of Electrical Engineering and Computer Science, NCKU, Taiwan, 2017
- Chapter Chair, Circuit and System Society, IEEE Tainan Section, 2015 - 2016
- Excellent Teaching Award, National Cheng Kung University, Taiwan, 2014
- Outstanding Project Award for Integrated Research Projects, Ministry of Science and Technology, Taiwan, 2013
- Outstanding Teaching Award, National Cheng Kung University, Taiwan, 2011
Dr. Chiou received a B.S. degree in Electrical Engineering from National Cheng-Kung University, Tainan, Taiwan, in 1988, an M.S. degree from the University of Louisiana, Lafayette, LA, USA, in 1993, and a Ph.D. degree from Purdue University, West Lafayette, IN, USA, in 2003. Since 2003, he has been a faculty member of the Electrical Engineering Department at National Cheng Kung University, Taiwan, and is currently a professor.
Job Description
The internship may involve research on SRAM-based Compute-in-Memory (CIM) macro design or CIM architectures to address the Von Neumann Bottleneck in AI. The intern is expected to gain research experience in circuit-level simulation, SRAM peripheral design, and hardware acceleration for neural networks.
Preferred Intern Educational Level
Senior undergraduate students, Master’s students, or early-stage PhD students in Electrical Engineering, Computer Engineering, or related fields.
Skill sets or Qualities
Basic knowledge of SRAM circuits, VLSI design, or Computer Architecture
Interest in AI hardware acceleration and energy-efficient memory-centric computing
Good communication skills and willingness to work on interdisciplinary research projects
Self-motivated and responsible attitude