- Adaptive Systems Laboratory
- Professor, Head of the Computer Engineering Division
- Courses - Undergraduate
- -Computer System Engineering<br>-Embedded Systems
- Courses - Graduate
- -Advanced Computer Organization,<br>-Embedded Real-Time Systems,<br>-Multicore Computing,<br>-Distributed Computing.
- Computer System and Architecture, Adaptive Systems
- 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 B.S. Degree, Huazhong University of Science and Technology (HUST)
- 1997.6 M.S. Degree, Huazhong University of Science and Technology (HUST)
- 2002.3 Ph.D. Degree, the University of Electro-Communications at Tokyo (UEC)
- Current Research Theme
- Adaptive Neuro-inspired Computing System and Platform for Complex Cognition Tasks
- Key Topic
- Adaptive and reconfigurable multi/manycore and processor architectures; photonic interconnects; on-chip networks; power- and reliability-aware computing; neuro-inspired computing; High-performance Computing
- Affiliated Academic Society
- -Senior member of IEEE, <br>-Senior member of ACM<br>-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
- 2010 Tunisian Presidential Prize
- 2009-2011 Member of the Governmental High Level Committee for Science and Technology (The High Level Committee for Science and Technology), Tunisia (Nominated by the President of the country).
- 2010 Best Paper Award at the 5th International Conference on Broadband, Wireless Computing, Communication and Applications (BWCCA-2010), Fukuoka, Japan,
- 2007 Best Paper Award at Eighth International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT 2007), Adelaide, Australia, Dec. 3-6, 2007.
- 2009 Best Presentation Award at The 19th Intelligent System Symposium (FAN2009), Aizu-Wakamatsu, Japan (Student presentation), Sept. 2009.
- Power-efficient Neuro-Inspired Architectures/Chips with Fault-tolerant Scalable Interconnect for learning in Networks of Spiking Neurons
The neuro-inspired technology based on spiking neural network (SNN) is one of the efficient solutions for brain-inspired cognitive computing in both learning and inference tasks. Hardware implementations of spiking neural network systems are power-efficient and effective methods to provide cognitive functions on a chip compared with the conventional stored-program computing style. In SNN based systems, there is no global clock; the neurons only fire when they have reached an activation level. The challenges that need to be solved toward building such a spiking-neuron computing paradigm include building a small-size massively parallel architecture with efficient neuro-coding schemes, robust neuron on-chip interconnect, and lightweight on-chip learning algorithms.
The goal in this project is to research and develop an ultra-low-power neuro-inspired spiking massively multicore Chip/SoC based on new deep neuronal algorithms and scalable reconfigurable interconnects. We are also investigating the computational properties of neural processing systems by developing new systems that emulate the principles of computation in the neural systems. We are researching and developing FPGA and ASIC Chips/SoCs for vision and learning for implementation in adaptive architecture/systems, cognitive IoT, and autonomous vehicles.
Dissertation and Published Works