自拍偷拍 - 自拍偷拍真实实战社区

研究方向：

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• 数字专用集成电路 （ASIC）

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• 高能效处理架构与专用处理器
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• 类脑芯片与神经形态计算
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• 边缘AI与分布式AIoT系统
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【New Positions 2026】: 国家重点研发计划智能机器人专项、其他重大项目 （面向LLM的高性能计算芯片与系统、面向类脑具身智能与机器人的专用芯片、异构多核SoC设计、FPGA for autonomous system and HPC）

• 2026硕士生、2027年免试推荐博士生、硕士生、自拍偷拍 卓博计划
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• 助理研究员、副研究员 （专任岗）、超级博士后
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【--以下岗位长期有效--】

【欢迎申请自拍偷拍 本博贯通“卓博计划”】

【Open Positions : 硕士（2026/27秋季入学）/博士研究生 （2027免试推荐）、博士后研究员 （上海超博项目、联合培养等）、Faculty Positions 】：

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4. 数字系统设计以及SoC设计与优化。欢迎具有以下兴趣（之一）的申请者：（1）SoC架构与数字系统开发验证流程；（2）FPGA开发；（3）领域专用架构或人工智能处理器设计 
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10. 超大规模神经拟态计算平台。欢迎具有以下兴趣的申请者：（1）高速数字系统开发；（2）FPGA、高层次综合、HW-SW Codesign；（3）NoC/interconnection network的设计（4）类脑计算与SNN；（5）2.5D、3D、Wafer level Integration

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16. 面向AIoT的低功耗智能芯片与系统。欢迎具有以下兴趣的申请者：（1）低功耗数字电路的设计与优化方法；（2）高能效信号处理算法或算法-架构协同优化方法；（3）神经型态处理与系统；（4）时域脉冲驱动/事件驱动的处理方法与系统

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22. 面向工业应用的分布式物联网智能系统。欢迎具有以下兴趣的申请者：（1）熟悉嵌入式系统开发以及HW-SW Codesign；（2）在嵌入式平台开发人工智能(如TinyML、LLM的边缘部署等)；（3）具有轻量级边缘智能算法与应用（如agent-based optimization、time series、anomaly detection等）研究的经验。

Research Interests

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• Energy-Efficient Processors and ASIC

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• Brain-Inspired Chips and Neuromorphic Computing

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• Edge AI and Distributed AIoT Systems

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Senior Member, IEEE

Vice-chair, IFIP WG8.12 

AE of JIII

AE of Frontiers in Neuroscience (Neuromorphic Engineering)

全球前2％顶尖科学家，2023-2025

自拍偷拍 卓识杰出人才，2023

国家青年特聘专家，2018

上海市浦江人才，2017

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• 2012 瑞典皇家理工学院 电子与计算机系统 博士 

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• 2007 瑞典皇家理工学院 电子工程（片上系统）硕士

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• 2005 北京理工大学 信息工程 学士

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• Ph.D. in Electronic and Computer Systems, KTH -Royal Institute of Technology, Sweden (2012)
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• M.Sc. in Electrical Engineering (System-on-Chip Design), KTH - Royal Institute of Technology, Sweden (2007)
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• B.Sc. in Information Engineering，Beijing Institute of Technology, China (2005)
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• MBA (minor), Turku School of Economics, University of Turku, Finland (2012)

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. 

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• 电子系统导论 （Introduction to Electronic Systems）- 本科生

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• 计算机体系结构（Computer Architecture）- 本科生 

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• 低功耗集成电路设计 - 数字与系统方向 (Low-power Integrated Circuits Design，Digital & Systems) - 研究生

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• 嵌入式系统与应用 (Embedded Systems and Applications) - 研究生

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• 智能计算系统 (Intelligent Computing Systems) - 研究生

Recent & Selected Publications

 Link to my Publication List from Google Scholar and DBLP

• Brain-Inspired Chips and Neuromorphic Computing

1. Y. He, et al. "CAMPRO: A CAM-Based Processing-in-Memory Processor for Hyperdimensional Computing." IEEE TCAS-I 2025.

2. F. Yang, et al. "PHENICS: A Scalable Neuromorphic FPGA Architecture for Million-Neuron Cortical Simulation With 4.6x Real-Time Acceleration." IEEE TCAS-I 2026.

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

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

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

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

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

9. 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

10. J. Yang, et al. ."A 0.66-mm2 0.49 pJ/SOP SNN Processor with Temporal-Spatial Post-Neuron-Processing and Model-Adaptive Crossbar in 40-nm CMOS." IEEE TBioCAS 2025

11. H. Zhang, et al. "A Neuromorphic Controller with On-Chip Learning for Robot Motion Control." IEEE TCAS-II 2025. 

•  Energy-Efficient Processors and AISC

12. Z. Yang, et al. "An Always-On Event-Triggered DVS Fall Detection Processor with Precision-Adaptive Inference in 40-nm CMOSs." IEEE TCAS-I 2026.

13. A. Xiao, et al. "A 40-nm Sub-mJ/transfer HDC-SNN Hybrid Processor Enabling On-Chip Few-Shot Transfer Learning for IoT Applications." IEEE TCASAI 2026.

14. 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

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

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

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

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

• Edge AI Systems and AIoT Applications

21. Z. Yu, et al. "SAIndust: A Self-Aware Heterogeneous Computing Framework for Industrial Internet of Things." IEEE Internet of Things Journal, 2025

22. 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

23. H. Jia, et al. "A domain-specific accelerator for ultralow latency market data distribution system" IEEE TII, 2022

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

25. Y. Jin, et al. "Edge-based Collaborative Training System for Artificial Intelligence-of-Things." IEEE TII 2022