Short-duration heavy precipitation is one of the most substantial severe convective disasters in China and is prone to causing urban waterlogging and secondary geological disasters, such as mountain torrents, mudslides, and landslides. This paper reviews recent progress in short-duration heavy precipitation research in China and briefly compares relevant findings from the United States and Europe. It covers the spatiotemporal distribution characteristics and diurnal variation patterns of short-duration heavy precipitation, atmospheric circulation patterns and environmental conditions that influence its occurrence and development in major regions of China, radar echo characteristics and raindrop distributions, impact of topography and urbanization on its formation and development, and application of artificial intelligence in potential forecasting, short-term forecasting, and nowcasting of short-duration heavy precipitation in China. With global warming, the frequency and intensity of short-duration heavy precipitation events have increased. In the future, further research will be required to enhance understanding of the formation mechanisms and environmental conditions, improve the spatiotemporal resolution of observations, expand the use of new observation data, and enhance forecasting capabilities in high-resolution, rapid-update cycle assimilation numerical weather prediction models through the fusion and analysis of dense multisource observation data. Additionally, optimizing deep learning models and algorithms—particularly in the development of largescale deep learning models—will be crucial for improving forecasting and early warning capabilities for short-duration heavy precipitation.