FACULTY
Research and Industry-Academia Collaboration
研究?産学連携
WANG Zhishang
Assistant Professor
- Affiliation
- Department of Computer Science and Engineering/Division of Information Systems
- Title
- Assistant Professor
- zwang@u-aizu.ac.jp
- Web site
- https://u-aizu.ac.jp/~zwang/
Education
- Courses - Undergraduate
- IT08 Signal Processing and Linear System (Exercise)
IE03 Integrated Exercise for Software I (Exercise)
IT03 Image Processing (Exercise)
FU06 Operating Systems
- Courses - Graduate
Research
- Specialization
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High performance computing
Perceptual information processing
Intelligent informatics
Intelligent robotics
Trustworthy AI in distributed systems
Green Energy Computing
Neuromorphic computing for adaptive android
- Educational Background, Biography
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Ph.D. in Computer Science, The University of Aizu, Japan, Apr. 2020 – Mar. 2023
M. Sc in Computer Science, University of Freiburg, Germany, Apr. 2016 – Mar. 2019
B. Sc in Information Security, University of Wuhan, China PR, Sep. 2010 – Jun. 2014
Zhishang Wang received the M.S. degree in computer science from University of Freiburg, Germany, in 2019, and the Ph.D. degree in computer science from The University of Aizu, Japan, in 2023. From April 2023 to March 2025, he was a postdoctoral researcher at the University of Aizu. Since April 2025, he has been an assistant professor with the Division of Computer Engineering, Department of Computer Science and Engineering, The University of Aizu. His current research interests are in the field of Machine Learning Systems, Edge Computing, Blockchain, and Trustworthy AI. He is also interested in event-driven neuromorphic systems targeted for a new generation of brain-inspired computing technologies and adaptive edge computing systems.
- Current Research Theme
- Driving Sustainable Computing
Trustworthy AI-Enabled Computing in Distributed Systems
Neuromorphic Android System with Multi-Modal Sensing and Distributed Intelligence
- Key Topic
- Sustainable and Energy-Efficient Computing
Trustworthy AI
Distributed Machine Learning and Edge Intelligence
Blockchain for Security and Data Integrity
Neuromorphic Computing and Spiking Neural Networks
Multimodal Sensing and Signal Integration
Human-Robot Interaction and Android Systems
- Affiliated Academic Society
- IEEE (Institute of Electrical and Electronics Engineers)
ACM (Association for Computing Machinery)
Main research
- AIzuHand: Real-time Neuromorphic Prosthetic Hand Platform
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Prosthetic limbs can significantly improve the quality of life of people with amputations or neurological disabilities. With the rapid evolution of sensors and mechatronic technology, these devices are becoming widespread therapeutic solutions. However, unlike living agents that combine different sensory inputs to perform a complex task accurately, most prosthetic limbs use uni-sensory input, which affects their accuracy and usability. Moreover, the methods used to control current prosthetic limbs (i.e., arms and legs) generally rely on sequential control and power-hungry strategies with limited natural motion and long and complicated training procedures. This project develops an advanced real-time neuromorphic prosthesis hand, AIzuHand, with sensory integration and feedback sensing. In addition, we investigate a user-friendly software tool for calibration, real-time feedback, and functional tasks.
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- N-HuRo: Neuromorphic Humanoid Robotics
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We advance next?generation adaptive autonomous systems through neuromorphic AI, anthropomorphic prosthetics, and intelligent robotic platforms. Our work integrates neuroscience, AI, neuromorphic computing, and robotics to develop lifelike systems that operate autonomously while adapting to human intent and dynamic environments. Using neuromorphic architectures and spiking neural networks, we design control frameworks enabling natural interaction between artificial limbs, androids, and biological users.
We also develop non?invasive neural interfaces for continuous intent decoding, and advanced sensory?processing models that give androids human?like perception and real?time responsiveness. Extending these capabilities to distributed anthropomorphic robots, we study multi?agent coordination, shared perception, and scalable autonomy. This research forms the foundation for future assistive technologies, human augmentation, and adaptive humanoid systems.
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Dissertation and Published Works
1) Zhishang Wang (2023). "Trustworthy AI-Enabled Systems and Algorithms for Power Management in Networks of Electric Vehicles. Doctoral dissertation," The University of Aizu, Japan.
2) Z. Wang, M. Hisada and A. B. Abdallah, "A Hybrid Clustered Approach for Enhanced Communication and Model Performance in Blockchain-Based Collaborative Learning," in IEEE Access, vol. 12, pp. 16975-16988, 2024, doi: 10.1109/ACCESS.2024.3359272.
3) Z. Wang and A. Ben Abdallah, "A Robust Multi-Stage Power Consumption Prediction Method in a Semi-Decentralized Network of Electric Vehicles," in IEEE Access, vol. 10, pp. 37082-37096, 2022, doi: 10.1109/ACCESS.2022.3163455.
4) Z. Wang, M. Ogbodo, H. Huang, C. Qiu, M. Hisada and A. B. Abdallah, “AEBIS: AI-Enabled Blockchain-Based Electric Vehicle Integration System for Power Management in Smart Grid Platform," in IEEE Access, vol. 8, pp. 226409-226421, 2020, doi: 10.1109/ACCESS.2020.3044612.
5) M. Maatar, Z. Wang, K. N. Dang and A. B. Abdallah, "BTSAM: Balanced Thermal-State-Aware Mapping Algorithms and Architecture for 3D-NoC-Based Neuromorphic Systems," in IEEE Access, vol. 12, pp. 126679-126692, 2024, doi: 10.1109/ACCESS.2024.3425900.
6) Y. Liang, Z. Wang and A. B. Abdallah, "Robust Vehicle-to-Grid Energy Trading Method Based on Smart Forecast and Multi-Blockchain Network," in IEEE Access, vol. 12, pp. 8135-8153, 2024, doi: 10.1109/ACCESS.2024.3352631.
7) Y. Liang, Z. Wang and A. B. Abdallah, "V2GNet: Robust Blockchain-Based Energy Trading Method and Implementation in Vehicle-to-Grid Network," in IEEE Access, vol. 10, pp. 131442-131455, 2022, doi: 10.1109/ACCESS.2022.3229432.