Zhuo Zou


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


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 integrated circuits and systems for IoT and ubiquitous intelligence. Prior to joining Fudan, he was the assistant director at VINN iPack Excellence Center, KTH, Sweden, where he coordinated the research project on ultra-low-power embedded electronics for wireless sensing. 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. We have joint activities on research and education with the TIERS group at UTU. 


Research Topics, and Recent&Selected Publications:

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

  • - Energy-Efficient Chips for AIoT
4. B. Huang, et al. " IECA: An In-Execution Configuration CNN Accelerator with 30.55 GOPS/mm2 Area Efficiency." IEEE TCAS-I 2021
5. J. Xu, et al. "A Memory-Efficient CNN Accelerator Using Segmented Logarithmic Quantization and Multi-Cluster Architecture." TCAS-II 2020
6. D. Bao, et al. "A Wirelessly Powered UWB RFID Sensor Tag with Time-Domain Analog-to-Information Interface." IEEE JSSC 2018
7. 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
8. Y. Jin, et al. "Self-aware Distributed Deep Learning Framework for Heterogeneous IoT Edge Devices." Future Generation Computer Systems, 2021
9. Y. Yan, et al. "An IoT-Based Anti-Counterfeiting System Using Visual Features on QR Code." IEEE Internet of Things Journal, 2020
10. L. Liu, et al. "A Smart Dental Health-IoT Platform based on Intelligent Hardware, Deep Learning, and Mobile Terminal." IEEE JBHI, 2019


Last updated on 2021-09-09 at 17:30