I am a postdoc of Prof. Yu Li at the Department of Computer Science and Engineering, Chinese University of Hong Kong. Before that, I had 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 University of Posts and Telecommunications under a joint project at the Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences 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 current research interests include healthcare and bioinformatics, AI for science, big data analysis, and evolutionary computation, in which I have published papers in SCI Information Sciences, Journal of Big Data, CCF SMC, and IEEE ICCSN, etc, and served as a reviewer for many essential journals and conferences such as IEEE/CAA Neurocomputing, JAS, CCF SMC, etc.
- Qing Li, Diwen Xiong, Mingsheng Shang, “Adjusted Stochastic Gradient Descent for Latent Factor Analysis”, Information Sciences, 588:196-213, 2022.[Full text]
- Qing Li, Guansong Pang, 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, 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, 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, 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, etc., “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]
- Nengfeng Zhang, Qing Li, Xin Luo, “An Alzheimer’s disease detection device based on support vector machines.” CN112155550A, 2021.