Towards Efficient Model Deployment and Serving of Deep Neural Network

Huaizheng’s research interests lie at the intersection of large-scale serving system and deep multimodal learning. Specifically, he develops deep learning (DL)-based frameworks to utilize real-world multi-modal datasets and architect user-friendly cloud-based systems to deploy these models for automatic and efficient DL inference. In this area, he has produced fruitful results, including nine published papers, two pre-prints, three research awards, and five open-source software (earned more than 1700 stars on GitHub). He did a six-month internship at ByteDance AI Lab as an AI system research intern. More about Huaizheng’s research are available on his website:

Click on the video below to view a presentation on the research project!