Research Topics
About Research
SYDLAB envisions the future of computing for artificial intelligence.
As large-scale AI models continue to grow in scale, memory systems—not computation—have become the primary performance bottleneck. We develop memory-centric architectures, digital circuit designs, and next-generation AI accelerators, along with hardware-software co-designed systems that enable efficient execution of LLMs, multimodal AI, and distributed agent systems.
We aim to redefine how intelligent systems are built and deployed by bridging the gap between hardware and AI, enabling scalable, adaptive, and efficient computing platforms that power the next generation of intelligent machines across cloud, edge, and physical environments.
Memory-Centric Computing
We design next-generation AI memory systems using CXL, HBM, and heterogeneous memory architectures to accelerate large language models and data-intensive AI workloads.
AI Accelerators & Digital Circuits
We design NPU, GPU, FPGA, and ASIC accelerators for efficient AI inference, focusing on high-performance digital architectures and domain-specific hardware.
AI Model Optimization
We accelerate AI models using quantization, pruning, speculative decoding, sparsity, and GPU-aware optimization for efficient LLM and vision model deployment.
Computer Architecture
We explore next-generation AI computer systems integrating CPUs, GPUs, NPUs, CXL memory, and high-bandwidth interconnects.
Agent Systems & Collaboration
We develop multi-agent AI systems that communicate, coordinate, and reason efficiently using shared memory, distributed execution, and collaborative intelligence.
AI-native Visual Computing
We build next-generation visual AI systems using Gaussian representations, multimodal models, and efficient video understanding for robotics and Physical AI.
Chae Eun Rhee, PhD
Principal Investigator of SYDLAB
Chae Eun Rhee received the B.S., M.S., and Ph.D. degrees in Electrical Engineering and Computer Science from Seoul National University, Seoul, Republic of Korea, in 2000, 2002, and 2011, respectively.
From 2002 to 2005, she was with the Digital TV Development Group, Samsung Electronics Company Ltd., Suwon, South Korea, as an Engineer, where she was involved in bus architecture and MPEG decoder development. She was a Professor with the Department of Information and Communication Engineering, Inha University, South Korea, from 2013 to 2024. In 2024, she joined the Department of Electronic Engineering, Hanyang University, South Korea, where she is currently a Professor.
Her current research focuses on next-generation AI computing systems, including memory-centric architectures, AI accelerators, efficient AI model optimization, AI agent collaboration, and AI-native visual computing through hardware-software co-design.
Our Projects
Projects Area
On Going Project
- 스마트모빌리티 인공지능 시스템반도체 연구센터
- 뉴로컴퓨팅 플랫폼 연구센터
- 딥러닝 기반 양방향 협력적 뉴로모픽 영상센서 시스템 설계기술 개발
- Near-display processing (NDP) 기반의 테라급 라이트 필드 디스플레이 시스템 개발
- 온디바이스용 플래시메모리 기반 인공지능반도체 프로세서 기술 개발
- GS-Streamer:3차원 가우시안 스플래팅 기반 실시간 스트리밍 최적화를 위한 압축 및 투영 기법 연구
Image Processing Project
- Volumetric 영상 부호화 및 전송을 위한 기술
- Development of reference frame compression/decompression algorithm
- 실시간 실감 영상 전송을 위한 라이트 필드 데이터의 구조 및 압축 연구
- 서버 향 동영상 스트리밍의 압축 효율 향상을 위한 전처리 연구 개발
- 라이트 필드 기반 실감 미디어 통합 플랫폼
Hardware Accelator Project
- 스마트모빌리티 인공지능 시스템반도체 연구센터
- CMOS Image Sensor 영상 처리를 위한 저전력 deep learning HW IP 설계 기술 개발
- 인공지능 반도체 융합전문인력육성사업
- 스마트모빌리티 인공지능 시스템반도체 연구센터
- 저전력, 고성능 빅데이터 서버용 프로세서-메모리-스토리지 통합 구조 원천기술 개발
Research Center Project
- 스마트모빌리티 인공지능 시스템반도체 연구센터
- 산업융합형 차세대 인공지능 혁신인재교육 연구단
- 인공지능 반도체 융합전문인력육성사업
- 멀티미디어 시스템 반도체 연구 센터 ITRC 사업
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