About MIVLab
Machine Intelligence and Vision (MIV) Lab, led by Prof. Chaehwa Yoo in the School of Electrical Engineering at Chungbuk National University, advances cutting-edge research in Artificial Intelligence, Computer Vision, and Image/Signal Processing.
Our research focuses on developing robust and secure AI methodologies capable of efficient learning, adaptation, and collaboration under minimal data and resource constraints. Specifically, we target the core bottlenecks of modern AI, including massive data dependency, data bias, high computational costs, excessive energy consumption, and privacy vulnerabilities. Bridging fundamental algorithm design and practical deployment, we actively apply these efficient intelligence models to solve real-world problems across diverse domains, including healthcare, energy systems, and defense.
Research Area
Robust AI focuses on developing secure, reliable, and high-efficient intelligence systems that can effectively learn, adapt, and collaborate under constraints such as data scarcity, bias, high computational and storage costs.
- Transfer Learning
- Adversarial Learning
- Federated Learning
- Test-time Adaptation
- Model Compression
- Video Coding for Machine (VCM)
Secure AI focuses on developing trustworthy, privacy-preserving, and transparent intelligence systems that can protect sensitive data and explain complex black-box models under strict security and regulatory demands.
- Data-free Adaptation
- Model-free Adaptation
- Explainable AI
- Trustworthy AI
Real-world Applications focuses on bridging fundamental algorithm design and practical deployment to solve critical challenges across various domains.
- Healthcare & Medical AI
- Autonomous Driving
- Power & Smart Energy Systems
- Smart Factory
- Military and Defense
Ongoing Projects
- Development of Federated Black-Box Domain Adaptation Technologies for Medical AI, National Research Foundation (NRF) of Korea, 2026-2029 (Role: Principal Investigator)
Completed Projects
- Domain Adaptation Regression for AI Model under Non-linear and Continual Domain Shift, Chungbuk National University, 2025-2026 (Role: Principal Investigator)
- Development of Language‐Guided Cross‐Modal Domain Adaptation, Ewha Womans University, 2024-2025 (Role: Principal Investigator)
- Deep learning-based COVID‐19 diagnosis system: On designing an explainable architecture, Center for Women in Science, Engineering and Technology (WISET) of Korea, 2021 (Role: Principal Investigator)