Biography
I’m currently a PhD student in Hara Lab at Tokyo Tech, supervised by Prof. Yuko Hara. My research focuses on FPGA-based ML accelerator design for IoT security scene.
Interests
- FPGA
- Efficient Machine Learning
- Embedded System
- Internet of Things
- Intrusion Detection System
- Computer Architecture
Education
PhD in Information and Communications Engineering, 2023.10 ~ present
Institute of Science Tokyo (formerly Tokyo Institute of Technology)
MEng in Information and Communications Engineering, 2021.10 ~ 2023.09
Tokyo Institute of Technology
BEng in VLSI Design & System Integration, 2017.09 ~ 2021.06
Nanjing University
Skills
Hardware
FPGA application, AI accelerator design
Algorithm
Machine learning, Deep learning, Imbalanced learning
Intrusion Detection System
DL-based IDS, FPGA-accelerated IDS
Professional Experience
Visiting Researcher
Université libre de Bruxelles
Hosted by ULB Cybersecurity Research Center, I’m now studying embedded system security.
Research Assistant
Tokyo Institute of Technology
I work as a research assistant for Trustworthy Architecture, Cryptography, and Evaluation for IoT systems and Green-niX.
Research Intern
Polytechnique Montreal
I worked as a short-term researcher. The project codes and document are available through the link. My major research content included:
- Matrix multiplication optimization study
- Algorithm prototype implementation
- Hardware design with Verilog
Accomplishments
2023 SLDM Work-in-progress (WIP) Best Presentation Award
See certificate
Publications
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(2025).
Lightweight Real-Time Detection of DDoS Attacks on IoT Devices via Power Side-Channel Analysis.
IEEE International Conference on Communications (ICC), Jun. 2025. (*accepted).
(2024).
Real-Time Detection of DDoS Flood Attacks on IoT Devices Using Power Side-Channel Signals.
International Workshop on Security (IWSEC), Kyoto, Japan, Sept. 17th, 2024 [Peer-reviewed, Poster Presentation].
(2024).
Hardware/Software Codesign of Real-Time Intrusion Detection System for Internet of Things Devices.
IEEE Internet of Things Journal, 2024. Vol. 11, Issue 12, pp.22351-22363, Jun. 2024.
(2024).
FPGA-Accelerated Random Forest for Real-Time IoT Intrusion Detection.
IEICE Tech. Rep., vol. 123, no. 374, RECONF2023-100, pp. 99-104, Jan. 2024.