FACULTY
Research and Industry-Academia Collaboration
研究・産学連携
DANG Nam Khanh
Associate Professor
- Affiliation
- Department of Computer Science and Engineering/Division of Computer Engineering
- Title
- Associate Professor
- khanh@u-aizu.ac.jp
- Web site
- https://u-aizu.ac.jp/~khanh/
Education
- Courses - Undergraduate
- PL03: JAVA Programming I (Ex.), University of Aizu, Undergraduate, Q1.
FU05: Computer Architecture (Ex.), University of Aizu, Undergraduate, Q1.
SE08: Introduction of Big Data Analytics (Ex.), University of Aizu, Undergraduate, Q3.
FU06: Operating Systems (Ex.), University of Aizu, Undergraduate, Q4.
- Courses - Graduate
- SYA14: Neuromorphic Computing, University of Aizu, Postgraduate, Q2.
Research
- Specialization
-
Control and system engineering
Electron device and electronic equipment
Computer system
High performance computing
Computational science
Intelligent informatics
- Neuromorphic Computing
- Machine Learning
- Fault-tolerance
- Educational Background, Biography
-
Educational Background
- Ph.D. in Computer Science and Engineering, The University of Aizu, Japan, 2017
- M.Sc. in Information Systems & Technology, University of Paris-XI, France, 2014
- B.Sc. in Electronics & Telecommunications, VNU University of Engineering and Technology, Vietnam, 2011
Work Experience
- Associate Professor, The University of Aizu, 2022 April - now.
- Assistant Professor, VNU University of Engineering and Technology, Vietnam National University, Hanoi, 2017 November - 2022 March.
- Visiting Researcher, The University of Aizu, 2020 November - 2021 March.
- Visiting Researcher, The University of Aizu, 2019 May - 2019 September.
- Researcher, SISLAB, Vietnam National University, Hanoi, 2011-2014.
- RTL Designer, Dolphin Vietnam Inc., 2010-2011.
- Current Research Theme
- Neuromorphic engineering
- Key Topic
- Neuromorphic Computing, Faul-tolerance, VLSI, 3D Integrated Circuits
- Affiliated Academic Society
Others
- Hobbies
- Football, Chess,Analog Photography
- School days' Dream
- Be a person that can change the world!
- Current Dream
- Be a good teacher :)
- Motto
- Fundamentals Are Everything :)
- Favorite Books
- The Fountainhead - Ayn Rand
- Messages for Students
- I strongly believe in learning fundamentals before doing anything advanced. Please spend some time to read, study, and practice basic topics like mathematics, English and programing. I will certainly help you in a long career ahead. You need to build a strong foundation, not a house of card. You can be slower than your peers for now, but can move forward way futher with good fundanmentals understanding. Life is not sprint, it's a marathon.
Main research
- Neuromorphic Computing Algorithms and Systems
-
Neuromorphic computing uses spiking neuron network models to solve machine learning problems in a more power/energy-efficient way when compared to the conventional artificial neural networks.We research adaptive low-power spiking neuromorphic systems and SoCs empowered with our earlier developed fault-tolerant three-dimensional on-chip interconnect technology. In particular, we investigate innovative algorithms and neuromorphic systems, including adaptive configuration methods to enable the reconfiguration of different network parameters (spike weights, routing, hidden layers, topology, etc.), fault-tolerance, thermal-aware mapping methods, and on-line learning algorithms. The target applications include anthropomorphic robotics and edge computing.
Dissertation and Published Works
Patent:
- A. Ben Abdallah, Khanh N. Dang, Masayuki Hisada, “TSV Error Tolerant Router Device for 3D Network On Chip”, 特許第7239099号, Japan patent.
Selected Publication:
- Ngo-Doanh Nguyen, Akram Ben Ahmed, Abderazek Ben Abdallah, Khanh N. Dang, “Power-aware Neuromorphic Architecture with Partial Voltage Scaling 3D Stacking Synaptic Memory“, IEEE Transactions on Very Large Scale Integration Systems (TVLSI), accepted, 2023.
- Ngo-Doanh Nguyen, Xuan-Tu Tran, Abderazek Ben Abdallah, Khanh N. Dang, “An In-situ Dynamic Quantization with 3D Stacking Synaptic Memory for Power-aware Neuromorphic Architecture”, IEEE Access, vol. 11, pp. 82377-82389, 2023.
- Khanh N. Dang, Nguyen Anh Vu Doan, Abderazek Ben Abdallah “MigSpike: A Migration Based Algorithm and Architecture for Scalable Robust Neuromorphic Systems”, IEEE Transactions on Emerging Topics in Computing (TETC), [DOI: 10.1109/TETC.2021.3136028].
- Khanh N. Dang, Akram Ben Ahmed, Abderazek Ben Abdallah, Xuan-Tu Tran, “HotCluster: A thermal-aware defect recovery method for Through-Silicon-Vias Towards Reliable 3-D ICs systems”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE, Volume 41, No. 4, pp. 799-812, April 2022. [DOI: 10.1109/TCAD.2021.3069370].
- Khanh N. Dang, Akram Ben Ahmed, Ben Abdallah Abderrazak and Xuan-Tu Tran, “TSV-OCT: A Scalable Online Multiple-TSV Defects Localization for Real-Time 3-D-IC Systems”, IEEE Transactions on Very Large Scale Integration Systems (TVLSI), IEEE, Volume 28, Issue 3, pp. 672 - 685, 2020. [DOI: 10.1109/TVLSI.2019.2948878].
- Khanh N. Dang, Akram Ben Ahmed, Yuichi Okuyama, 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 (TETC), IEEE, Volume 8, Issue 3, pp. 577-590, 2020. [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 Systems (TVLSI), IEEE, Volume 25, Issue 11, pp. 3099-3112, 2017. [DOI: 10.1109/TVLSI.2017.2736004].
More details: https://u-aizu.ac.jp/~khanh/