Research

We pursue academic excellence with real-world impacts.

In pursuing the following goals, we use a two-track system for research and education: Individual Academic Research + Group R&D Project

• Knowledge discovery on the representation, prediction, generation, and control by machines

• Applied data science and the intelligence development for real-world services in industry and society

 

Examples of ongoing Group R&D Projects

• 정보통신기획평가원 SW스타랩, 잡음과 변동에 강건한, 일반화가능한 시계열 특화 자기지도학습 기술 개발 및 다양한 서비스 도메인에의 응용 (Time-Series Self-Supervised Learning Technologies with Noise-and-Variability Robustness and Generalizability: Development and Applications for Multiple Service Domains), 2024-2031.

• 한국연구재단 우수연구-중견연구(유형1), 제어와 튜닝이 어려운 생성 AI 서비스의 작업 맥락 맞춤화를 위한 생성 결과 편집 모델 개발 및 실증: 작업 맥락의 잠재된 다목적 최적화 접근 (Generation Result Edit Model for Task-context-customized Use of Bounded Generative AI Services: Approach to Optimizing the Latent Context Objectives and Its Real-world Applications), 2024-2026.

• 정보통신기획평가원 컴퓨팅핵심기술, 강건하고 일반화가능한 생체전기신호 파운데이션 모델 구축 및 이를 활용한 질환 진단 모델들의 임상적 유용성 연구 (Development of Foundation Models for Bioelectrical Signal Data and Validation of Their Clinical Applications: A Noise-and-Variability Robust, Generalizable Self-Supervised Learning Approach), 2024-2026.

• 한국연구재단 기초연구실 심화형, 금속 적층제조 다단계공정 품질제어를 위한 물리지식기반 인공지능 연구실: 반도체 히트싱크 대상 검증 연구 (Physics-informed AI for Multistage Process Quality Control in Metal Additive Manufacturing and Its Validation for Semiconductor Heat Sinks), 2024-2027.

Examples of outcomes from Individual Academic Research