In-Situ Techniques on GPU-Accelerated Data-Intensive Applications. - Yi Ju; Mingshuai Li; Adalberto Perez; Laura Bellentani; Niclas Jansson; Stefano Markidis; Philipp Schlatter; Erwin Laure (e-Science, 2023)

A Generative Data Augmentation Trained by Low-quality Annotations for Cholangiocarcinoma Hyperspectral Image Segmentation. - Kaijie Dai; Zehao Zhou; Song Qiu; Yan Wang 033; Mei Zhou; Mingshuai Li; Qingli Li (IJCNN, 2023)

A generative adversarial network with multi-scale convolution and dilated convolution res-network for OCT retinal image despeckling. - Xiaojun Yu; Mingshuai Li; Chenkun Ge; Perry Ping Shum; Jinna Chen; Linbo Liu (Biomed. Signal Process. Control., 2023)

Detecting depression tendency based on deep learning and multi-sources data. - Weijun Ma; Song Qiu; Jue Miao; Mingshuai Li; Ziqing Tian; Boyuan Zhang; Wanzhu Li; Rui Feng; Chunhui Wang; Yong Cui; Chen Li; Kyoko Yamashita; et al. (Biomed. Signal Process. Control., 2023)

Loss-balanced parallel decoding network for retinal fluid segmentation in OCT. - Xiaojun Yu; Mingshuai Li; Chenkun Ge; Miao Yuan; Linbo Liu; Jianhua Mo 001; Perry Ping Shum; Jinna Chen (Comput. Biol. Medicine, 2023)

TokenRing: An Efficient Parallelism Framework for Infinite-Context LLMs via Bidirectional Communication. - Zongwu Wang; Fangxin Liu; Mingshuai Li; Li Jiang 002 (CoRR, 2024)

MM-Tracker: Visual Tracking With A Multi-Task Model Integrating Detection and Differentiating Feature Extraction. - Zhihui Wang 003; Mingshuai Li; Zhiyuan Li 013; Xing-Li Zhang 001; Ming Li 065; Zhao Li 007; Weiping Ding 001; Xindong Wu 001 (IEEE Trans. Emerg. Top. Comput. Intell., 2025)