Research Interests of EI Lab
Remote sensing for water environment
- Multi-spectral and radar satellite monitoring
- Droneborne monitoring
- In-situ water quality monitoring
- Remote sensing algorithm development for water quality variables (Harmful algae, fecal coliform, orgamic carbon, nutrients, etc)
Advanced deep learning modeling for predicting and classifying water environment
- Design and optimize convolutional neural network (CNN) architecture
- Fusion of deep learning and physical models
- Explainable artificial intelligence (XAI) application
- Generative aritifical intelligence (Generative AI) implementation
Edge AI design for demonstrating real time water quality prediction
- Deep learning model quantization
- Circuit and field-programmable gate array (FPGA) design for remote sensing sensor
- Deep learning embedded system optimization
- Demonstration of edge AI system for water quality prediction