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Zhengwu Liu

Research Assistant Professor

The University of Hong Kong

Neuromorphic Computing & Brain-Computer Interfaces

Bridging artificial intelligence and neuroscience through memristor-based computing

About Me

I am a Research Assistant Professor in the Department of Electrical and Computer Engineering at the University of Hong Kong. I received my Ph.D. from Tsinghua University in 2023 and B.E. from the University of Electronic Science and Technology of China in 2018.

My research focuses on memristor-based neuromorphic computing, compute-in-memory (CIM) chips, brain-computer interfaces (BCIs), AI hardware accelerators and AI healthcare.

Academic Highlights

  • Published in Nature Electronics, Nature Communications, Science Advances, IEDM, DAC and etc.
  • PI of projects funded by Hong Kong RGC and NSFC

Selected Awards

  • HUANAO China BCI Prize Rising Star Award, 2025
  • Falling Walls Science Breakthrough of the Year, Shortlist (Engineering & Technology), 2025
  • China Top 10 Semiconductor Research Achievements, 2025
  • China Society of Image and Graphics (CSIG) Outstanding Doctoral Dissertation Award, 2025
  • China Major Science, Technology and Engineering Advancements, 2020

Professional Services

  • TPC member: ICCAD (2023-2025), ASPDAC (2025-2026)
  • Editorial Board: Scientific Reports (Springer Nature), BPEX (IOP Publishing), BMEF (a Science partner journal, junior), AI for Science (IOP Publishing, junior), etc.
  • Reviewer: Nature Communications, Nano Letters, Journal of Neural Engineering, etc.

Recent News

Feb 2026
Science Advances Paper on secure edge AI system using memristor chips published
Nov 2025
Nature Communications Paper on memristor-based adaptive ADC published
Feb 2025
Nature Electronics Adaptive neuromorphic decoder for BCIs published
Feb 2025
DAC 2025 One paper accepted at DAC 2025

Featured Research

Secure edge AI Research
Science Advances 2026

Privacy-preserving data analysis using a memristor chip with colocated authentication and processing

Zhengwu Liu*, Zhongrui Wang, Chenchen Ding, Bohan Lin, Jianshi Tang, Bin Gao, Ngai Wong*, and Huaqiang Wu*

Secure AI CIM Pysically Unclonable Function (PUF)
Paper
BCI Decoder Research
Nature Electronics 2025

A memristor-based adaptive neuromorphic decoder for brain–computer interfaces

Zhengwu Liu†, Jie Mei†, Jianshi Tang, Minpeng Xu, Bin Gao, Kun Wang, Sanchuang Ding, Qi Liu, Qi Qin, Weize Chen, Yue Xi, Yijun Li, Peng Yao, Han Zhao, Ngai Wong, He Qian, Bo Hong, Tzyy-Ping Jung, Dong Ming, Huaqiang Wu

BCI Neuromorphic Computing Co-evolution
Paper
ADC Research
Nature Communications 2025

Memristor-based adaptive analog-to-digital conversion for efficient and accurate compute-in-memory

Haiqiao Hong, Zhiyuan Du, Mingrui Jiang, Ruibin Mao, Yuan Ren, Fuyi Li, Wei Mao, Muyuan Peng, Wei Zhang, Zhengwu Liu*, Can Li*, Ngai Wong*

CIM ADC AI hardware
Paper
Medical Imaging Research
Nature Communications 2023

Energy-efficient high-fidelity image reconstruction with memristor arrays for medical diagnosis

Han Zhao†, Zhengwu Liu†, Jianshi Tang*, Bin Gao, Qi Qin, Jiaming Li, Ying Zhou, Peng Yao, Yue Xi, Yudeng Lin, He Qian, Huaqiang Wu

Medical Imaging Image Reconstruction Healthcare AI
Paper
Neural Signal Analysis
Nature Communications 2020

Neural signal analysis with memristor arrays towards high-efficiency Brain-Computer interfaces

Zhengwu Liu, Jianshi Tang*, Bin Gao, Peng Yao, Xinyi Li, Dingkun Liu, Ying Zhou, He Qian, Bo Hong*, Huaqiang Wu*

Epilepsy BCI Neuromorphic computing
Paper
Parallel Processing
Science Advances 2020

Multichannel parallel processing of neural signals in memristor arrays

Zhengwu Liu, Jianshi Tang*, Bin Gao, Xinyi Li, Peng Yao, Yudeng Lin, Dingkun Liu, Bo Hong, He Qian, Huaqiang Wu*

BCI Multichannel Energy Efficiency
Paper

Join Our Research Group

We are looking for self-motivated master's students, PhD students and postdoctoral researchers interested in neuromorphic computing, BCIs, and AI hardware.

Get in Touch

(Last updated on March, 2026)