Hyunjae Kim (Combined Graduate Student)
Repository Commit History
IntroductionFull Bio SketchMr. 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 TopicDirect Sparse LiDAR Streaming for Profile-Adaptive ACChjkim2_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. PublicationsJournal Publications (SCI 0, KCI 0)Conference Publications (Intl. 2)
Participation in International Conference
Last Updated, 2026.06.17 |