His research interests focus on machine learning/deep learning algorithms on natural language processing/speech processing, including pre-trained language model, neural machine translation, music generation, text summarization, neural architecture search for NLP, audio speech recognization, text-to-speech synthesis and etc.

Currently, I am focused on the following research topics:
General NLP methods (e.g., pre-trained modeling, architecture design, efficient training and inference) for understanding/generation/other applications.
Speech/NLP technologies in disease diagnosis (e.g., Cleft Palate or Alzheimer’s detection).
Designing solutions for solving clinical NLP and Biomedical applications, including generation and understanding.
Long-Sequence Understanding in NLP applications (e.g., Translation and Summarization).