PUBLICATIONS
Selected Previous Publications
Journal and conference papers from ISLAB before 2026
Robust Training to Secure Automated AI Accelerator Generation Against Malicious Platforms
C. Guo and Y. Shi
International Conference on Neural Information Processing (ICONIP), Nov. 2025, pp. 76–89.
Artificial Intelligence
Hardware Security
AI Accelerator
Bennet’s Doubler-Extended Converter With Optimized Bias for Enhanced Energy Extraction From Triboelectric Nanogenerators
Y. Su and Y. Shi
IEEE Transactions on Power Electronics (IF: 7.1), vol. 40, no. 9, pp. 12026 – 12030, 2025.
Energy Harvesting
TENG
Bennet Doubler
DSE-Based Hardware Trojan Attack for Neural Network Accelerators on FPGAs
C. Guo, M. Yanagisawa, and Y. Shi
IEEE Transactions on Neural Networks and Learning Systems (IF: 9.7), vol. 26, no. 7, pp. 13036 – 13050, 2025.
Artificial Intelligence
Hardware Security
AI Accelerator
A Novel Security Threat Model for Automated AI Accelerator Generation Platforms
C. Guo and Y. Shi
IEEE Access (IF: 4.2), vol. 13, pp. 61237 – 61249, 2025.
Artificial Intelligence
Hardware Security
AI Accelerator
An FPGA-Based YOLOv6 Accelerator for High-Throughput and
Energy-Efficient Object Detection
X. Sha, M. Yanagisawa, and Y. Shi
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. e-108A, no. 3, pp. 473- 481, 2025.
YOLO
AI Accelerator
FPGA
An Efficient Multiplier-Less Processing Element on Power-of-2 Dictionary-Based Data Quantization
J. Li, M. Yanagisawa, and Y. Shi
Integrated Circuits and Systems, vol. 1, no. 1, pp. 53- 62, 2024.
SNN
AI Accelerator
FPGA
A Dual-Output Rectifier-Based Self-Powered Interface Circuit for Triboelectric Nanogenerators
Y. Su, M. Yanagisawa, and Y. Shi
IEEE Transactions on Power Electronics (IF: 6.6), vol. 39, no. 6, pp. 6630 – 6634, 2024.
Energy Harvesting
TENG
Bennet Doubler
Dataflow Optimization through Exploring Single-Layer and Inter-Layer Data Reuse in Memory-Constrained Accelerators
J. Ye, M. Yanagisawa, and Y. Shi
Electronics, vol. 11, no. 15, 2022.
Neural Network
Layer Fusion
Accelerator
Power-Efficient Deep Convolutional Neural Network Design Through Zero-Gating PEs and Partial-Sum Reuse Centric Dataflow
L. Ye, J. Ye, M. Yanagisawa, and Y. Shi
IEEE Access (IF: 3.476), vol. 9, pp. 17411 – 17420, 2021.
Artificial Intelligence
AI Accelerator
FPGA
Transition Detector-Based Radiation-Hardened Latch for Both Single- and Multiple-Node Upsets
S. Tajima, M. Yanagisawa, and Y. Shi
IEEE Transactions on Circuits and Systems II: Express Briefs (IF: 3.691), vol. 67, no. 6, pp. 1114 – 1118, 2020.
Radiation-Hardened Latch
SNU/MNU
ASIC
Robust Secure Scan Design Against Scan-Based Differential Cryptanalysis
Y. Shi, N. Togawa, M. Yanagisawa, and T. Ohtsuki
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 20, no. 1, pp. 176 – 181, 2012.
Hardware Security
Robust Scan
Circuit
Improved Launch for Higher TDF Coverage With Fewer Test Patterns
Y. Shi, N. Togawa, M. Yanagisawa, and T. Ohtsuki
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 29, no. 8, pp. 1294 – 1299, 2010.
Scan Test
Transition Delay Fault
Test patterns