Participate in the complete life cycle of deep learning model application and product development. Including data collection, data cleansing, data preprocessing, model design, model training, model deployment, model performance evaluation, etc. Develop related technologies such as classification, detection, segmentation, and generation of video/audio data, and use deep reinforcement learning to programming and scheduling related issues. Applications include: smart city, smart communications, and smart factory.