邹卓 - 复旦大学 - 信息科学与工程学院

个人简介

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. 学习工作经历 Ph.D. in Electronic and Computer Systems, KTH -Royal Institute of Technology, Sweden (2012) M.Sc. in Electrical Engineering (System-on-Chip Design), KTH - Royal Institute of Technology, Sweden (2007) B.Sc. in Information Engineering，Beijing Institute of Technology, China (2005) MBA (minor), Turku School of Economics, University of Turku, Finland (2012) 获奖情况国家青年特聘专家，2018 上海市浦江人才，2017

研究领域

从事面向物联网应用的智能电子系统研究：包括低功耗电路与系统芯片设计、无线感知系统、智能系统集成与应用。面向AIoT的智能芯片与系统高能效处理与专用处理器设计神经拟态系统与电路物联网在工业与健康领域的应用

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Event-Driven Processing and Neuromorphic System H. Chu, et al. "A Neuromorphic Processing System with Spike-Driven SNN Processor for Wearable ECG Classification." IEEE TBioCAS 2022 C. Ding, et al, "A Hybrid-Mode On-Chip Router for the Large-Scale FPGA-Based Neuromorphic Platform," IEEE TCAS-I 2022 D. Wang, et al. "A Memristor-Based Learning Engine for Synaptic Trace-Based Online Learning." IEEE TBioCAS 2023 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. Y. Yan, et al. "Graph-Based Spatio-Temporal Backpropagation for Training Spiking Neural Networks." IEEE AICAS 202 H. Chu, et al. "A Neuromorphic Processing System for Low-Power Wearable ECG Classification." IEEE BioCAS 2021 F. Yang, et al. "TSCM: a TCAM-Based Sparse Connection Memory Architecture in Neuromorphic Computing System for Cortical Simulation." IEEE ISCAS 2024 A. Xiao, et al. "Spiking-HDC: a Spiking Neural Network Processor with HDC Classifier Enabling Transfer Learning ." IEEE ISCAS 2024 Y. Yan, et al. "Backpropagation With Sparsity Regularization for Spiking Neural Network Learning," Frontiers in Neuroscience 2022 D. Wang, et al. "Mapping the BCPNN Learning Rule to a Memristor Model," Frontiers in Neuroscience 2021. Energy-Efficient Chips for AIoT B. Huang, et al. " IECA: An In-Execution Configuration CNN Accelerator with 30.55 GOPS/mm2 Area Efficiency." IEEE TCAS-I 2021 J. Xu, et al. "ASLog: An Area-Efficient CNN Accelerator for Per-Channel Logarithmic Post-Training Quantization." TCAS-I 2023 D. Bao, et al. "A Wirelessly Powered UWB RFID Sensor Tag with Time-Domain Analog-to-Information Interface." IEEE JSSC 2018 Y. Huan, et al. "A 101.4 GOPS/W Reconfigurable and Scalable Control-Centric Embedded Processor for Domain-Specific Applications." IEEE TCAS-I 2016 D. Wang, et al. "FPGA-Based HPC for Associative Memory System." ASP-DAC 2024 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 Y. Jin, et al. "Edge-based Collaborative Training System for Artificial Intelligence-of-Things." IEEE TII 2022 Y. Yan, et al. "An IoT-Based Anti-Counterfeiting System Using Visual Features on QR Code." IEEE Internet of Things Journal, 2020 L. Gong, et al. "An IoT-Based Wearable Labor Progress Monitoring System for Remote Evaluation of Admission Time to Hospital." IEEE JBHI, 2023 L. Qian, et al. "MCU-Enabled Epileptic Seizure Detection System With Compressed Learning." IEEE Internet of Things Journal, 2023

学术兼职

Senior Member, IEEE Vice-chairman, IFIP WG8.12 AE of JIII AE of Frontiers in Neuroscience (Neuromorphic Engineering)