Hyunjae Kim (Combined Graduate Student)

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Graduate Student (M.S), Embedded System-on-Chip Integrator
AI-Embedded System/Software on Chip (AI-SoC) Lab
School of Electronics Engineering, Kyungpook National University
Phone: +82 053 940 8648
E-mail: kei0042 [@] naver [DOT] com
[Google Scholar] [SVN]

Repository Commit History

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Introduction

Full Bio Sketch

Mr. Kim is currently pursuing his undergraduate degree in Electronics Engineering at Kyungpook National University, Daegu, Republic of Korea. His research interests focus on embedded systems, computer architecture, parallel/concurrent processor design, and hardware/software co-design for efficient data processing systems. He have worked on RISC-V processor implementation, FPGA/RTL-based hardware design, and LiDAR data processing architectures for adaptive cruise control systems. His current research interests focus on efficient processor and accelerator architectures, memory hierarchy optimization, and real-time embedded computing system.

Research Topic

Direct Sparse LiDAR Streaming for Profile-Adaptive ACC

hjkim2_topic1.jpg LiDAR-based adaptive cruise control (ACC) requires real-time processing of large spatial sensor data, but storing and processing all LiDAR samples as dense frames can introduce significant input staging and memory-access overhead. My research focuses on a CPU-accelerator co-design architecture that validates and quantizes incoming LiDAR distance samples before dense-frame storage, packetizes only valid samples into 4×4 sparse tile packets, and streams them directly to the accelerator. The accelerator performs tile-level pooling, object-slot tracking, and side-static filtering to generate compact object metadata such as bounding boxes, object counts, and representative distance information. The metadata is exposed to the CPU through MMIO registers, enabling metadata-based ACC policy without directly processing the full LiDAR frame. This structure also supports frame-latched profile-adaptive execution, allowing different quantization settings and processing profiles to be applied according to driving conditions while maintaining deterministic frame-level behavior.

Publications

Journal Publications (SCI 0, KCI 0)

Conference Publications (Intl. 2)

  • Hyunjae Kim and Daejin Park. Under Blind Review In IEEE APCCAS 2026, 2026.

  • Hyunjae Kim and Daejin Park. Under Blind Review In IEEE A-SSCC 2026, 2026.

Participation in International Conference

  • IEEE IPFA 2026, Singapore, Singapore

  • IEEE APCCAS 2026, Fukuoka, Japan

  • IEEE A-SSCC 2026, Taipei, Taiwan

Last Updated, 2026.06.17