Zhiwei Jiang's primary research interests lie in Natural Language Processing (NLP) and Deep Learning. He focuses on fundamental problems of applying novel machine learning techniques, such as deep learning, graph learning, few-shot learning, weakly supervised learning, etc., in the field of NLP. The relevant tasks include text quality assessment, sentiment analysis, intent detection, sequence labeling, and more. Additionally, he also explores the application of NLP techniques in other related domains, such as software engineering and multimodal data processing. In recent years, he has published over twenty academic papers in top conferences and journals within the relevant domain, including ACL, SIGIR, WWW, AAAI, IJCAI, MM, TOIS, and others.