About me

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, Zhihang Hu, Yixuan Wang, Lei Li, Yimin Fan, Irwin King, Le Song, and Yu Li, “Progress and Opportunities of Foundation Models in Bioinformatics”, arXiv preprint arXiv:2402.04286, 2024.[Full text]
  • Qing Li, Lei Li, and Yu Li, “Developing ChatGPT for Biology and Medicine: A Complete Review of Biomedical Question Answering”, aarXiv preprint arXiv:2401.07510, 2024.[Full text]

Selected Publications

  • 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]
  • Leming Zhou, Qing Li, and Mingsheng Shang, “Chronic Disease Detection via Non-negative Latent Feature Analysis”, IEEE International Conference on Networking, Sensing and Control, 1:1-6, 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]
  • Qing Li, Lige Zhang, Xiaolin Qin, and Weiyi Chen, “NSA-CSIPSO: satellite navigation signal acquisition method based on compressed sensing using improved particle swarm optimization”, 2018 10th International Conference on Communication Software and Networks (ICCSN), 290-295, 2018.[Full text]

Patents

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