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 energy-efficienct chips and systems for intelligent computing and 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 intelligent computing systems. Dr. Zou has also been an adjunct professor and docent at the University of Turku, Finland. He is vice chair of IFIP WG-8.12 and a senior member of IEEE. 

Link to my Publication List from Google Scholar and DBLP

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My research group is primarily affiliated with Fudan University in Shanghai. Ph.D., Postdoc, and research fellows vacancies are open. We have joint activities on research and education with the TIERS group at UTU. 

Recent & Selected Publications​​​​​​​

• Brain-Inspried Chips and Neuromorphic Computing

1. F. Yang, et al. "CorTile: A Scalable Neuromorphic Processing Core for Cortical Simulation With Hybrid-Mode Router and TCAM." IEEE TCAS-I 2024.

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

3. 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. 

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

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

6. D. Wang, et al. "Scalable Multi-FPGA HPC Architecture for Associative Memory System." IEEE TBioCAS 2024.

7. J. Yang, et al. "A 40nm 0.05-1.4uJ/inference Sample-Wise-Adaptive Spiking Neural Network Processor with Dynamic Neuron-Pruning and Unstructured-Model-Aware Architecture." CICC 2025

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.

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

•  Energy-Efficient Processors and AISC

12. H. Ji, et al. "A Communication-Aware and Resource-Efficient NoC-based Architecture for CNN Acceleration", EEE JETCAS 2024

13. J. Huang, et al. "A Reconfigurable Near-Sensor Processor for Anomaly Detection in Limb Prostheses."  IEEE TBioCAS 2024

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

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

18. S. Tan, et al. "Towards Efficient Eye Tracking in AR/VR Devices: A Near-Eye DVS-Based Processor for Real-time Gaze Estimation." IEEE TCAS-I 2025

19. Z. Yu, et al. "DuoQ: A DSP Utilization-aware and Outlier-free Quantization for FPGA-based LLMs Acceleration." DAC 2025

20. D. Ji, et al. "A Computation and Energy Efficient Hardware Architecture for SSL Acceleration." ASP-DAC 2025 

• Edge AI Systems and AIoT Applications

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

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

25. Y. Chen, et al. "CDL-H: Cluster-Based Decentralized Learning With Heterogeneity-Aware Strategies for Industrial Internet of Things," IEEE Internet of Things Journal, 2025