Zhuo Zou
 


zhuo.zou@utu.fi








Areas of expertise
- Chips and Systems for AIoT
- Energy-Efficient Processing and Application-Specific Processor Design
- Embedded and Distributed Intelligence Systems
- UWB based Sensing and Perception for IoT


Biography

Zhuo Zou (Senior Member, IEEE) received the Ph.D. degree in electronic and computer systems from the KTH Royal Institute of Technology, Stockholm, Sweden, in 2012. He is currently a Full Professor with Fudan University, Shanghai, China, 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 with VINN iPack Excellence Center, KTH. He has also been an Adjunct Professor and Docent with the University of Turku, Turku, Finland. His current research interests include low-power circuits, energy-efficient SoC, neuromorphic computing, and their applications in AIoT and autonomous systems. He is the Vice Chairman of IFIP WG-8.12.

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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. 



Research

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

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

5. Y. Yan, et al. "Graph-Based Spatio-Temporal Backpropagation for Training Spiking Neural Networks." IEEE AICAS 2021
6. C. Ding, et al. "An Ultra-Low Latency Multicast Router for Large-Scale Multi-Chip Neuromorphic Processing." IEEE AICAS 2021
7. H. Chu, et al. "A Neuromorphic Processing System for Low-Power Wearable ECG Classification."  IEEE BioCAS 2021



  • - Energy-Efficient Chips for AIoT

8. B. Huang, et al. " IECA: An In-Execution Configuration CNN Accelerator with 30.55 GOPS/mm2 Area Efficiency." IEEE TCAS-I 2021
9. J. Xu, et al. "A Memory-Efficient CNN Accelerator Using Segmented Logarithmic Quantization and Multi-Cluster Architecture." TCAS-II 2020
10. D. Bao, et al. "A Wirelessly Powered UWB RFID Sensor Tag with Time-Domain Analog-to-Information Interface." IEEE JSSC 2018
11. Y. Huan, et al. "A 101.4 GOPS/W Reconfigurable and Scalable Control-Centric Embedded Processor for Domain-Specific Applications." IEEE TCAS-I 2016



  • - IoT Systems and Applications

12. Y. Jin, et al. "Edge-based Collaborative Training System for Artificial Intelligence-of-Things." IEEE TII 2022
13. Y. Yan, et al. "An IoT-Based Anti-Counterfeiting System Using Visual Features on QR Code." IEEE Internet of Things Journal, 2020
14. L. Liu, et al. "A Smart Dental Health-IoT Platform based on Intelligent Hardware, Deep Learning, and Mobile Terminal." IEEE JBHI, 2019

15. Y. Jin, et al. "Self-aware Distributed Deep Learning Framework for Heterogeneous IoT Edge Devices." Future Generation Computer Systems, 2021



Publications


Last updated on 2023-12-07 at 11:53