Chaoming Fang received his B.S. degree in Instrumentation Science and Technology from Beihang University, Beijing, China, in 2021. He joined the Center of Excellence in Biomedical Research on Advanced Integrated-on-chips Neurotechnologies (CenBRAIN Neurotech), School of Engineering, Westlake University, Hangzhou, China in 2021, where he is currently pursuing his Ph.D. degree.

Chaoming is interested in energy-efficient processing algorithms and machine learning accelerator VLSI design for biomedical applications. He is now working on the design for biosignals’ processor with reconfigurable on-chip learning and inference of neuromorphic computing. The purpose of his project is to achieve high adaptability to different patients and low-power consumption for real-time monitoring.

[1] C. Fang, Z. Shen, S. Zhao, C. Wang, F. Tian, J. Yang and M. Sawan, “A 0.078 pJ/SOP Unstructured Sparsity-Aware Spiking Attention/Convolution Processor with 3D Compute Array, ” IEEE Custom Integrated Circuits Conferences (CICC), 2024

[2] C. Fang, C. Wang, S. Zhao, F. Tian, J. Yang and M. Sawan, "A 510μW 0.738-mm2 6.2-pJ/SOP Online Learning Multi-Topology SNN Processor with Unified Computation Engine in 40-nm CMOS, ” IEEE Transactions on Biomedical Circuits and Systems, 2023

[3] C. Fang, F. Tian, C. Wang, J. Yang and M. Sawan, " A 217.8 MSOPs/W FPGA-based online learning SNN processor using unified event-driven structure and topology aware data reuse strategies," IEEE Asian Solid-State Circuits Conference (A-SSCC), 2022