Resource-Efficient Multi-Task LoRA for Edge Devices
In ProgressExploring parameter-efficient multi-task adaptation for deploying multiple AI tasks on resource-constrained edge devices.
Graduate Student Research Project Program · Selected · 2026
Dongguk University, M.S. Student in Computer Science & Artificial Intelligence
I am interested in building computing systems that connect the digital and physical worlds. My research focuses on personalized learning, IoT, and edge computing, exploring how systems can adapt to users, devices, and real-world constraints.
Investigating personalized federated learning methods for heterogeneous edge devices with varying computational and data resources.
Exploring parameter-efficient multi-task adaptation for deploying multiple AI tasks on resource-constrained edge devices.
Graduate Student Research Project Program · Selected · 2026
Selected projects demonstrating experience in IoT, software systems, and real-world problem solving.
19th Open Source Developer Competition · Special Award
🔗 GitHubA VS Code extension that automatically finds and fixes web accessibility problems in real time, helping developers build websites that are usable by everyone, including people with disabilities.
E2GEE Lab Makeathon · Grand Prize
A smart power strip for pet-owning households that watches for overheating and fire risk at each outlet, alerts owners in real time, and automatically cuts power to prevent accidents.
A web service that organizes on-site 3D-printing requests at hackathons and events — teams submit orders online and everyone can track progress in real time, replacing manual, paper-based tracking.
Dongguk University, Dept. of Computer Science & Artificial Intelligence · iSN Lab
Dongguk University
AIoT Track Vice Lead (2026)