Bio Computing & Machine Learning Lab
At BCML, we explore the intersection of biology, computation, and machine learning to push computational neuroscience forward.
Our research focuses on Spiking Neural Networks, Reinforcement Learning, and Medical AI to advance healthcare innovation.
Department of Computer Engineering, Kwangwoon University, Seoul, South Korea
Research Projects
Explore our cutting-edge research
An end-to-end AI workflow that captures nailfold capillaroscopy (NFC) images, enhances capillary visibility, and quantifies biomarkers for autoimmune and vascular disease screening.
Developing energy-efficient robotic control systems using SNNs with R-STDP and TD3 reinforcement learning
HAR using multiple sensors including RGB, depth, IMU, and event-based sensors with advanced feature fusion
De-identifying and classifying bedridden patient actions using RGB-DVS hybrid sensors for privacy-preserving healthcare
Designing third-generation neural networks that use discrete spikes to analyze ECG, PPG, and tactile sensing streams with neuromorphic efficiency.
Latest Publications
(2025).
Deep Reinforcement Learning-Based Adaptive Bandpass Filter With Reconfigurable Frequency and Bandwidth.
IEEE Microwave and Wireless Technology Letters.
(2025).
GEMMAS: Graph-based Evaluation Metrics for Multi Agent Systems.
In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track.
(2025).
EMG와 DVS를 이용한 SNN 기반 팔 동작 모방 로봇 팔 제어 방법.
한국 특허 10-2023-0142845.
(2025).
GPT API를 사용한 네트워크 이상치 탐지 방법.
한국 특허 10-2023-0139066.
(2025).
몽유병을 감지하는 엣지 디바이스.
한국 특허 10-2022-0164099.