Development of On-Device Personalized Next-Generation Generative AI Technologies

• Duration: 2025.03.01–2030.02.28
• Funding: NRF (한국연구재단)
• Total Budget: KRW 1,250,000,000
• Summary: This project aims to develop next-generation generative models for on-device environments by leveraging diffusion models and 3D NeRF representations. Our goal is to enable personalized, efficient, and high-fidelity content generation under limited computational resources.

Development of Ultra-Large AI-Based Smart City Healthcare Technologies Using Multimodal Biometric Data

• Duration: 2024.04.01–2031.12.31
• Funding: IITP (정보통신기획평가원)
• Total Budget: KRW 8,000,000,000
• Summary: This project focuses on predicting individual health states by integrating diverse multimodal biometric data. We develop a GPT-based framework that provides interpretable and personalized explanations for health risk assessment and decision support.

BK21 Smart Energy Program

• Duration: 2025.03.01–2027.08.31
• Funding: NRF (한국연구재단)
• Summary: Our laboratory participates in the Brain Korea 21 (BK21) Phase 4 project, focusing on advanced research and graduate education. Through this program, we contribute to training high-level researchers and developing core technologies in our research fields.

Development of a General-Purpose Artificial Intelligence Platform for Multi-Sensory Integrated Control of Next-Generation Social Robots

• Duration: 2025.04.01–2025.12.31
• Funding: IITP (정보통신기획평가원)
• Total Budget: KRW 375,000,000
• Summary: We develop a Vision–Language–Action (VLA) model for multi-sensory integrated control of next-generation social robots. The goal is to enable robust and generalizable robot decision-making across diverse real-world interactions.

Development of Behavioral Response–Based Psycho-Cognitive AI Technologies for Early Screening of Developmental Disorders in Infants and Children

• Duration: 2023.03.01–2025.12.31
• Funding: ETRI
• Total Budget: KRW 132,000,000
• Summary: This project aims to develop AI technologies for early screening of autism spectrum disorder in infants and children based on behavioral and psycho-cognitive responses. The proposed approach supports objective and data-driven assessment for early developmental risk identification.

Development of Core Generative Adversarial Network Technologies for High-Quality Video Generation

• Duration: 2022.03.01–2025.02.28
• Funding: NRF (한국연구재단)
• Total Budget: KRW 90,000,000
• Summary: This project studied GAN-based video generation techniques for producing high-quality images. We focused on advancing core components of generative adversarial networks to improve visual fidelity.

Research Service on Improving Automatic Rail Surface Defect Detection Networks

• Duration: 2023.03.01–2025.12.31
• Funding: KRI (한국철도기술연구원)
• Total Budget: KRW 70,000,000
• Summary: This project develops semantic segmentation–based methods for automatic detection of surface defects on railway tracks. We focus on improving detection accuracy and robustness of neural networks under real-world rail inspection conditions.