Zhipeng Liao obtained a bachelor's degree in Microelectronics Science and Engineering from South China University of Technology in 2023 and a master’s degree in Electronic Engineering from the University of Southampton in 2024. In October 2024, he joined CenBRAIN Neurotech Center of Excellence at Westlake University as a visiting student and started working as a research assistant in December 2025. He will pursue his Ph.D degree under the supervision of Professor Mohamad Sawan from September 2026.

Zhipeng Liao is dedicated to the design and optimization of neuromorphic computing chips, high-performance computing architectures, and edge artificial intelligence systems. His work focuses on developing innovative hardware solutions for edge intelligence, including FPGA-based accelerators, in-memory computing strategies, and energy-efficient neuromorphic platforms. In the future, he plans to integrate advanced chip design techniques and machine learning algorithms to enable applications in edge artificial intelligence, biomedical signal processing, and neural interface systems.

[1] LIAO Z., LI T., SHEN Z., FANG C., YANG J., SAWAN M., “NeuroPlat: An FPGA-based Neuromorphic. Computing Platform with Optimized Toolchain for Efficient SNN Deployment”, International Conference on Machine Intelligence and Nature-Inspired Computing (MIND), Xiamen, China, Oct. 31-Nov. 2, 2025. (Best Poster Award)

[2] LIAO Z., LI T., SHEN Z., FANG C., YANG J., SAWAN M., “A Pipeline-Driven FPGA Accelerator with Memory-Scheduling for Neuromorphic Computing", IEEE APCCAS, Busan, Korea, 12-15 October 2025. (Oral Presentation)

[3] LIAO Z., ZHAO K., YU J., ZHAO L., CHENG T., TSUI C., YANG J., SAWAN M., “A Memory-Friendly. Retrieval Architecture for RAG-Enabled Wearable Medical LLMs-Agents”, IEEE-BioCAS, Abu Dhabi, UAE, Oct. 16-18, 2025. (Poster).