Research

Area 1: AI/Deep Learning for big data

Our lab researches effective deep learning for uncovering the power hidden in the big data, and efficient deep learning for making wearable/edge computing ultra-low-power. Cutting-edge deep learning technologies, such as Convolutional Neural Network, Long Short-term Memory, Deep Reinforcement Learning, Deep Autoencoder, Generative Adversarial Network, and more have been thoroughly researched and implemented to deal with diverse kinds of challenges in big data, like multimodal, noisy, highly nonlinear, abnormal, and long-term dynamics.

Area 2: Wearable Computer & IoT Sensor for big data

Our lab also designs and builds wearable computers and IoT sensing devices, to capture real-time long-term big data from human, environment, and generally the physical objects and world. Novel devices and software/hardware systems are customized for multimodal, wireless, ultra-low-power and intelligent perception of different kinds of biomedical and physical dynamics, which establish the big data and are then learned by AI algorithms designed in our lab.

Research Multidisciplinary Technologies for Systematic Innovations

Pervasive Embedded Intelligence; Artificial Intelligence; Wearable Massive-sensor Computer; Mobile Health; Wearable Intelligence; Edge Computing; IoT Sensing and Communication Platform; Wearable Sensing Devices; Signal Processing; Image Processing; Smart Health/Home/World Big Data.