- Adaptive Systems Laboratory
- Professor, Head of the Computer Engineering Division
- Web site
- Courses - Undergraduate
- - Computer Architecture
- Introduction to Computer Systems
- Parallel Computer Systems
- Courses - Graduate
- - Advanced Computer Organization
- Embedded Real-Time Systems
- Parallel and Distributed Computing
- Fault-tolerance and Robustness; Emerging Interconnect Technologies for Multi-core Architectures;
Neuro-inspired Architectures/Chips; AI and Machine Learning Systems; Ultra-low power Embedded and Multicore SoCs
- Educational Background, Biography
- 2002.4 Research Associate, the University of Electro-Communications at Tokyo (UEC)
- 2007.10 Assistant Professor, the University of Aizu (UoA)
- 2011.4 Associate Professor, the University of Aizu (UoA)
- 2011/3, 2012/3, 2013/3, 2014/3, 2015/3 Visiting Professor, Huazhong University of Science and Technology (HUST)
- 2012.4 Senior Associate Professor, the University of Aizu (UoA)
- 2010/3, 2011/3, 2012/3, 2013/3 Visiting Professor, Hong Kong University of Science and Technology (KUST)
- 2014.4 Professor, the University of Aizu (UoA)
- 2014.4 Head of the Division of Computer Engineering, the University of Aizu (UoA)
- 1994.6 BEng, Huazhong University of Science and Technology (HUST)
- 1997.6 MEng, Huazhong University of Science and Technology (HUST)
- 2002.3 Ph.D., the University of Electro-Communications Tokyo (UEC)
- Current Research Theme
- Neuromorphic Computing Systems: Building large-scale scalable neuromorphic implementations using application-specific hardware and embedded FPGA chips.
- Key Topic
- - Adaptive/self-organizing systems,
- Emerging interconnect technologies for parallel architectures,
- Power and reliability-aware architectures,
- Neuromorphic engineering
- Affiliated Academic Society
- -Senior member of IEEE, -Senior member of ACM -Member of IEICE
- Reading and visiting historical places
- School days' Dream
- To become a school teacher!
- Current Dream
- Achieve outstanding research results that can benefit the whole humanity.
- Simple is the best!
- Favorite Books
- " You Can Heal Your Life ".
- Messages for Students
- Concentration and organization are the keys to your research success.
- Publications other than one's areas of specialization
- Low-power event-driven adaptive neuromorphic processing system for autonomous cognitive behavior
Artificial intelligence (AI) has many applications in today's society, including robots intelligence, traffic control, data analytics, image recognition, and speech understanding. The growing size and complexity of AI Algorithms require high-performance computation and memory resources. Application-specific hardware and emerging devices/systems are needed to achieve orders of magnitude improvement in performance and energy efficiency of AI algorithms.
The goal of this project is to research and develop algorithms, architectures, and digital implementations of spiking neural networks technology that will have a big impact on IoTs, robotics, as well as prosthetic devices. The approach is to develop a robust, real-time, and low-power neuro-inspired solutions targeted for full-custom system-on-chip integration and featuring the followings: (1) adaptive configuration method which enables reconfiguration of different network parameters (spike weights, routing, hidden layers, topology, etc.), (2) a mixture of different deep neural network topologies, (3) an efficient fault-tolerant spike routing algorithm, and (4) online learning mechanism. To demonstrate the performance of our processors/systems, an FPGA implementation shall be developed. Besides, a VLSI implementation shall be established.
Dissertation and Published Works
 The H. Vu,Yuichi Okuyama, Abderazek Ben Abdallah, “Comprehensive Analytical Model and Shortest-path K-means based Multicast Routing Algorithms and Architecture for 3D-NoC of Spiking Neurons,” ACM Journal on Emerging Technologies in Computing Systems, Special Issue on Hardware and Algorithms for Energy-Constrained On-chip Machine Learning, (to appear)
 The Vu, Ogbodo Mark Ikechukwu, Abderazek Ben Abdallah, ''Fault-tolerant Spike Routing Algorithm and Architecture for Three Dimensional NoC-Based Neuromorphic Systems,'' IEEE Access, Vol 7, pp. 90436-90452, 2019, DOI: 10.1109/ACCESS.2019.2925085
 Khanh N. Dang, Akram Ben Ahmed, Yuichi Okuyama, and Abderazek Ben Abdallah, ”Scalable Design Methodology and Online Algorithm for TSV-cluster Defects Recovery in Highly Reliable 3D-NoC Systems”, IEEE Transactions on Emerging Topics in Computing, 2017 (in press). DOI: 10.1109/TETC.2017.2762407.
 Khanh N. Dang, Akram Ben Ahmed, Xuan-Tu Tran, Yuichi Okuyama, Abderazek Ben Abdallah, ”A Comprehensive Reliability Assessment of Fault-Resilient Network-on-Chip Using Analytical Model”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 25, Issue: 11, pp. 3099 – 3112, Nov. 2017. DOI:10.1109/TVLSI.2017.2736004.
Complete list of publications: http://www.u-aizu.ac.jp/~benab/publications.html