전기전자공학과

• 터치스크린 지문 센싱
• 체내 혈당 연속 측정
• 무선전력전송
• 에베네센트를 이용한 전력전송 및 통신
• 통신을 위한 아날로그/디지털 통합회로 설계

• 영상 개선 및 영상 복원
• 반사 제거
• 연무 제거
• 수중 영상
• 사람 검색
• 객체 검출
• 3차원 포인트 클라우드
• 딥러닝

• Nonstationary Degradation Identification & Restoration
• Design of Efficient Deep Neural Networks & Applications
• Product Quality Inspection & Process Automation

• Inverse problems for various imaging modalities:
  - natural image restorations (super-resolution, denoising, deblurring, etc.)
  - medical image reconstructions (MRI, CT, SIM, Cryo-EM, DOT, EEG, fMRI, etc.)
• Bridging between signal processing and deep learning communities:
  - providing a design principle for deep learning architectures
  - network analysis using topological data analysis (TDA)
• Deep generative models:
  - developing a high fidelity and diverse image-to-image translation model
  - improving generative models based on theoretical understandings

In a broad sense, my research direction is to develop novel learning algorithms which overcome remaining challenges of deep-learning techniques. 

• The current deep learning algorithms are
  i) dependent on a massive amount of training data,
  ii) hard to generalize to unseen tasks and iii) difficult to learn a new concept on the learned knowledge. 

• To tackle these problems, I`m interested in following topics:
  - few-shot learning, meta-learning, lifelong learning (continual and incremental learning)
  - meta-reinforcement Learning and causal learning.

• 5G를 넘어서 6G를 상용화 하기위한 THz-range transceiver 및 beam-tracking technology
• 자율주행을 위한 센싱 기술인 CMOS Radar 기술과 connected car를 위한 C-V2X 트랜시버의 개발
• Massive IoT를 위한 초고속, 저전력 transceiver 연구
• AI SoC의 computing performance를 높이고 전력 소모를 낮추기 위해 analog domain에서 Neuromorphic computing hardware를 연구
• 반도체 디자인에 들어가는 시간과 비용을 획기적으로 줄이기 위해 Analog IC design의 자동화 기술에 대해서 연구

1. Surface-enhanced Infrared Absorption Spectroscopy
   We are developing a novel class of plasmonic structures for Surface-enhanced infrared absorption (SEIRA) spectroscopy. Extremely high near-field enhancement and enhanced sensing area formed at various plasmonic metamaterial structures may provide a promising sensing platform for future applications of ultrasensitive biological and chemical sensing and detection.
2. Active metasurfaces
   We are developing ultra-fast electrically-tunable plasmonic metasurfaces based on coupling of plasmonic resonances in metallic nanostructures with intersubband transitions in multiple-quantum-well (MQW) structures.
3. Nonlinear metasurfaces
   We are developing highly-nonlinear metasurfaces based on coupling of electromagnetically-engineered plasmonic nanoresonators with quantum-engineered intersubband nonlinearities.

• Real-time Access Network Architechture for  Edge Cloud Services using SDN/NFV/CCN
   - distributed cloud service architecture
  - real time wireless access architectue
• Multi-path TCP
  - QoS enhancement for multi interface network
  - Data scheduling for MPTCP in wireless netwrok
• Open IoT Software Platform Development for IoT Services
  - Sensor Network Life time  Enhance ment /Energy efficient  Protocol design
  - Sustainable Service Network Management architecture

• Deep learning processor architecture
• Quantization methods for deep neural networks
• Resistive Random Access Memory (ReRAM)
• In-memory computing
• Energy efficiency
• Reconfigurable architecture
• Compilers

• 전동기 구동 시스템(Motor drive system)
• 계통 연계형 컨버터(Grid connected converter)
• 고전압 직류 송/배전 시스(High voltage DC transmission/distribution)