ZOU Zhuo

Micro-Nano System Center

Professional Title:Professor

Position: Principal investigator


Visiting Address:


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Curriculum Vitae

- Ph.D. (2012) KTH Royal Institute of Technology, Sweden

Research Interests

Research Interests

  •  Chips and Systems for AIoT

  •  Energy-Efficient Processing and Application-Specific Processor Design

  •  Embedded and Distributed Intelligence Systems

  •  Brain-Inspired Computing and Neuromorphic System


Education and Working Experience

Short Bio: Zhuo Zou received his Ph.D. degree in Electronic and Computer Systems from KTH Royal Institute of Technology, Sweden, in 2012. Currently, he is with Fudan University Shanghai as a Full Professor, where he is conducting research on intelligent chips and systems for AIoT. Prior to joining Fudan, he was the assistant director and a project leader at VINN iPack Excellence Center, KTH, Sweden. His current research interests include low-power circuits, energy-efficient SoC, neuromorphic computing, and their applications in AIoT and autonomous systems. Dr. Zou has also been an adjunct professor and docent at the University of Turku, Finland. He is vice chairman of IFIP WG-8.12 and a senior member of IEEE.


My research group is primarily affiliated with Fudan University in Shanghai. Ph.D., Postdoc, and research fellows vacancies are open




- Introduction to Electronic System Design (BSc)

- Computer Architecture (BSc)

- Intelligent Computing Systems (MSc)

- Low-Power Integrated Circutes Design (MSc and PhD)

- VLSI Engineering (MSc and PhD)

- Embedded System and Application (MSc)


Recent & Selected Publications

  • - Event-Driven Processing and Neuromorphic System

1. H. Chu, et al. "A Neuromorphic Processing System with Spike-Driven SNN Processor for Wearable ECG Classification."  IEEE TBioCAS 2022

2. C. Ding, et al, "A Hybrid-Mode On-Chip Router for the Large-Scale FPGA-Based Neuromorphic Platform," IEEE TCAS-I 2022

3. D. Wang, et al. "A Memristor-Based Learning Engine for Synaptic Trace-Based Online Learning." IEEE TBioCAS 2023

4. C. Liu, et al. "A Low-Power Hybrid-Precision Neuromorphic Processor With INT8 Inference and INT16 Online Learning in 40-nm CMOS." IEEE TCAS-I 2023

5. Y. Yan, et al. "Graph-Based Spatio-Temporal Backpropagation for Training Spiking Neural Networks." IEEE AICAS 202
6. H. Chu, et al. "A Neuromorphic Processing System for Low-Power Wearable ECG Classification."  IEEE BioCAS 2021

7. F. Yang, et al. "TSCM: a TCAM-Based Sparse Connection Memory Architecture in Neuromorphic Computing System for Cortical Simulation." IEEE ISCAS 2024

8. A. Xiao, et al. "Spiking-HDC: a Spiking Neural Network Processor with HDC Classifier Enabling Transfer Learning ." IEEE ISCAS 2024

9.  Y. Yan, et al. "Backpropagation With Sparsity Regularization for Spiking Neural Network Learning," Frontiers in Neuroscience 2022

10. D. Wang, et al. "Mapping the BCPNN Learning Rule to a Memristor Model," Frontiers in Neuroscience 2021.

- Energy-Efficient Chips for AIoT

11. B. Huang, et al. " IECA: An In-Execution Configuration CNN Accelerator with 30.55 GOPS/mm2 Area Efficiency." IEEE TCAS-I 2021
12. J. Xu, et al. "ASLog: An Area-Efficient CNN Accelerator for Per-Channel Logarithmic Post-Training Quantization." TCAS-I 2023
13. D. Bao, et al. "A Wirelessly Powered UWB RFID Sensor Tag with Time-Domain Analog-to-Information Interface." IEEE JSSC 2018

14. Y. Huan, et al. "A 101.4 GOPS/W Reconfigurable and Scalable Control-Centric Embedded Processor for Domain-Specific Applications." IEEE TCAS-I 2016

15.D. Wang, et al. "FPGA-Based HPC for Associative Memory System." ASP-DAC 2024 

16. S. Tan, et al. "A Near-Eye DVS-Based End-to-End Eye Tracking Processor for AR/VR Applications." IEEE ISCAS 2024

  • - IoT Systems and Applications

17. Y. Jin, et al. "Edge-based Collaborative Training System for Artificial Intelligence-of-Things." IEEE TII 2022
18. Y. Yan, et al. "An IoT-Based Anti-Counterfeiting System Using Visual Features on QR Code." IEEE Internet of Things Journal, 2020
19. L. Gong, et al. "An IoT-Based Wearable Labor Progress Monitoring System for Remote Evaluation of Admission Time to Hospital." IEEE JBHI, 2023

20. L. Qian, et al. "MCU-Enabled Epileptic Seizure Detection System With Compressed Learning."  IEEE Internet of Things Journal, 2023

Link to my Publication List from Google Scholar and DBLP

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