Chaoyue brings a decade of proficiency in artificial intelligence generated content (AIGC). He has authored over 60 academic works published in prestigious journals and conferences such as IEEE T-PAMI, T-EVC, IEEE T-IP, NeurIPS, ICLR, CVPR, ECCV, IJCAI, among others. Renowned for his research such as TDGAN (first author), which secured the Distinguished Student Paper Award at IJCAI-17, and E-GAN (first author), celebrated as the Best of Physics by MIT TR and 2018's Best GAN Paper by DTRANSPOSED. The Super Deep Learning project in which he was involved has been selected as WAIC-22's SAIL Top30. In early 2022, Chaoyue led the writing of the globe's inaugural “AIGC white paper”, foreseeing the transformative impact of foundational generative models. His research projects have been covered by various media outlets, including China Global Television Network (CGTN), Scientific American, MIT Tech Review, Sina, Sohu, Tencent News, and AI Technology Review, etc.

He currently focuses on developing foundation visual content generative models that are generalizable, controllable, and interpretable. He aims to conduct cutting-edge research and applied algorithm applications in the areas of "Pre-training of fundament visual content generative models", "Controllable and personalized visual content generation", and "High-efficiency inference and low-cost deployment". In the end, his technical vision is to promote the versatility, safety, and convenience of AIGC technology development.