I am a postdoc of Prof. Yu Li at the Department of Computer Science and Engineering, Chinese University of Hong Kong. Before that, I am fortunate to have a one-year internship with Prof. Chenglin Liu at the National Laboratory of Pattern Recognition of the Institute of Automation, Chinese Academy of Sciences. I received my Ph.D. degree in computer science from the Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences under a joint project at the Chongqing University of Posts and Telecommunications in 2023. And I obtained my master’s degree and bachelor’s degree from the University of Chinese Academy of Sciences in 2019 and Sichuan Normal University in 2016 respectively. My research interests include AI for science (healthcare and bioinformatics) and big data analysis (eg. recommender systems, evolutionary computation). I am open to discussion or collaboration. Feel free to contact me if you are interested.

Preprints

• Qing Li, Yixuan Wang, Yimin Fan, and Yu Li, “Alignment and Projection of scRNA-seq and Spatial Transcriptomics in Whole Transcriptome Space,” 2024.
• Qing Li and Mingsheng Shang, “Adversarial Swarm Optimizer for Adaptive Latent Factor Analysis,” 2024.
• Tianyi Wang*, Qing Li*, Yu Li, and Xiaolin Qin, “Test Time Adaptation for RGB-D Multi-modal Semantic Segmentation,” 2024.
• Xin Lan, Xiaolin Qin, Qing Li#, and Yu Li, “Omnidirectional Multi-scale Network for Oriented Object Detection,” 2024.
• Peiyang Wei, Mingsheng Shang, Qing Li, et al, “An Efficient Temporal Convolutional Neural Network with Evolutionary Algorithm for Radar Image Extrapolation,” 2024.
• Xin Lan, Lei Li, Qing Li, Shaolin Zhang, Yu Li, and Xiaolin Qin, “The Shape-Guided Selection and Loss for Oriented Object Detection in Aerial Images,” 2024.
• Yu Li, Tianyi Wang, Xu Gu, Qing Li, and Xiaolin Qing, “CFBERT: Contrastive Learning for Sentence Embeddings with Clustering and Fine Grained Ranking Information,” 2024.
• Yixuan Wang, Yimin Fan, Xuesong Wang, Tingyang Yu, Yongshuo Zong, Xinyuan Liu, Meitong Liu, Qing Li, Kin hei Lee, Khachatur Dallakyan, Junjie Huang, Gengjie Jia, Jiao Yuan, Ting-Fung Chan, Xin Gao, Irwin King, and Yu Li, “SCMBench: Benchmarking Domain-specific and Foundation Models for Single-cell Multi-omics Data Integration,” 2024.

Selected Publications

• Qing Li, Zhihang Hu, Yixuan Wang, Lei Li, Yimin Fan, Irwin King, Le Song, Gengjie Jia, Sheng Wang, and Yu Li, “Progress and Opportunities of Foundation Models in Bioinformatics”, Briefings in Bioinformatics, 25(6):bbae548, 2024. [Full text]
• Qing Li, Lei Li, and Yu Li, “Developing ChatGPT for Biology and Medicine: A Complete Review of Biomedical Question Answering”, Biophysics Reports, 10(3):152-171, 2024. [Full text]
• Qing Li, Bingqing Du, Xiaolin Qin, Jiguang Zhang, and Shibiao Xu, “Multi-scale Global Consistency Residue Feature Enhancement based Protein Structure Analysis”, In Proceedings of the 2023 9th International Conference on Communication and Information Processing, Association for Computing Machinery, New York, NY, USA, 24–30, 2024. [Full text]
• Qing Li, Diwen Xiong, and Mingsheng Shang, “Adjusted Stochastic Gradient Descent for Latent Factor Analysis”, Information Sciences, 588:196-213, 2022. [Full text]
• Qing Li, Guansong Pang, and Mingsheng Shang, “An Efficient Annealing-Assisted Differential Evolution for Multi-parameter Adaptive Latent Factor Analysis”, Journal of Big Data, 9(1):95, 2022. [Full text]
• Qing Li and Mingsheng Shang, “BALFA: A Brain Storm Optimization-based Adaptive Latent Factor Analysis Model”, Information Sciences, 578:913-929, 2021. [Full text]
• Qing Li and Mingsheng Shang, “A Compressed Sensing and Porous 9-7 Wavelet Transform-based Image Fusion Algorithm”, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 4185-4191, 2020. [Full text]

Patents

• Nengfeng Zhang, Qing Li, Xin Luo, “An Alzheimer’s disease detection device based on support vector machines.” CN112155550A, 2021.