Jung Jaewoong Lab
Jung Jaewoong Lab
KAIST · Electrical Engineering
Professor
Prof. 정재웅
Professor's page · publicationsAbout
KAIST 전기및전자공학부 정재웅(Jae-Woong Jeong) 교수의 Bio-Integrated Electronics and Systems Lab이다. 헬스케어·바이오메디슨을 위한 차세대 '소프트' 생체 융합 전자소자와 시스템을 개발하며, 유연·신축성 전자소자, 광학 마이크로시스템, 마이크로유체 소자를 설계·제작한다. 무선 신경 임플란트, 광유전학, 액체금속 기반 신축성 전자소자 등을 다룬다.
Research keywords
Selected publications
- IoT-enabled wireless neural implant for chronic, programmable neuropharmacology and optogeneticsScience Advances · 2025
- Skin-like blind-spot-free tactile sensing via phase-programmable multimode liquid metal pressure sensorsnpj Flexible Electronics · 2025
- Liquid Metals for Reconfigurable BioelectronicsAdvanced Materials · 2025
- Integrating artificial intelligence and optogenetics for Parkinson's disease diagnosis and therapeutics in male miceNature Communications · 2025
- Phase-change metal ink with pH-controlled chemical sintering for versatile fabrication of variable stiffness electronicsScience Advances · 2025
- A stealthy neural recorder for the study of behaviour in primatesNature Biomedical Engineering · 2024
- Body-temperature softening electronic ink for additive manufacturing of transformative bioelectronics via direct writingScience Advances · 2024
- A temperature-responsive intravenous needle that irreversibly softens on insertionNature Biomedical Engineering · 2024
Other labs in this department
- Kim Dongjoon LabRecruiting
Dongjun Kim
Computer architecture, interconnection networks, mobile systems, hardware security
- Kim Moonchul LabRecruiting
Munchurl Kim
Video coding, pattern recognition, visual communications
- Kim Minjun LabRecruiting
Min Jun Kim
Physical robot interaction, collaborative robots, aerial manipulation
- Kim Seongmin LabRecruiting
Song Min Kim
Wireless systems and networks, mobile computing, IoT
- Kim Yonghoon LabRecruiting
Yong-Hoon Kim
Atomic-scale device simulations, high-performance/machine-learning scientific computing
- Kim Junmo LabRecruiting
Junmo Kim
Statistical signal processing, image processing, computer vision, information theory