AI system
LLM inference and serving, agentic AI pipelines, PEFT/LoRA fine-tuning, and Mixture-of-Experts model efficiency.
DONGGUK UNIVERSITY
동국대학교 시스템 시스템 및 네트워크 연구실
We explore the synergy between system and network for AI, and AI for system and network. Our research targets faster, more efficient, and more reliable computing infrastructures from edge devices to cloud and datacenter-scale systems.
We are looking for highly motivated undergraduate interns and graduate students!Our research theme is System for AI — building the system software and networking infrastructure that makes AI faster, more efficient, and more reliable.
LLM inference and serving, agentic AI pipelines, PEFT/LoRA fine-tuning, and Mixture-of-Experts model efficiency.
Traffic splitting, programmable SDN, bandwidth isolation, and high-performance networking for cloud and AI workloads.
IoT packet processing, edge service placement, efficient AI for constrained devices, and cloud-edge pipeline design.
Assistant Professor
Department of Computer Science and Artificial Intelligence
yeonho.yoo@dgu.ac.krSystems, networking, and AI infrastructure research.
Myungseo Kim, Hyunil Jeon, Sumin Han, Jonguk Han, Dongmin Baek, and Seonghwan No.
Contact
Students interested in system software, networking, cloud/edge computing, distributed AI training, and AI-driven optimization are welcome to contact the lab.
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