Zhiqiang Li

About

Zhiqiang Li received the Ph.D. degree in pattern recognition and intelligent systems from Shanghai Jiao Tong University, Shanghai, China, in 2009. He was a Post-Doctoral Researcher with the Key Laboratory of Geographic Information Science (Ministry of Education of China) and the School of Geographical Sciences, East China Normal University, Shanghai. He was a Researcher with the Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai. He was a Quantitative team leader of Shanghai Thunder Asset Management Co., Ltd.
Now, Zhiqiang Li is a Researcher of Donghai Laboratory, and also a part-time Researcher with computer vision team of Ningbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences.
His research interests include pattern recognition, image processing, visual large model, deep learning, computer vision, and quantitative finance.
Dr. Li serves as a peer reviewer for the IEEE Transactions on Geoscience and Remote Sensing, the Engineering Applications of Artificial Intelligence, and the Geoscience and Remote Sensing letters.

Employment

• Donghai Laboratory Researcher
  2024 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (17)

• Rapid and Hierarchical UAV Exploration via Adaptive Regional Viewpoint Generation
  ICRA 2026 2026
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• AT-FinGPT: Financial risk prediction via an audio-text large language model
  Finance Research Letters 2025 DOI: 10.1016/j.frl.2025.106967
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• RUSH: Rapid UAV Spatial Hierarchical Exploration via Regional Viewpoint Generation for Large-scale Environments
  IEEE Robotics and Automation Letters 2025 DOI: 10.1109/lra.2025.3604699
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• Scale-pyramid dynamic atrous convolution for pixel-level labeling
  Expert Systems with Applications 2024 DOI: 10.1016/j.eswa.2023.122695
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• Dense-scale dynamic network with filter-varying atrous convolution for semantic segmentation
  Applied Intelligence 2023 DOI: 10.1007/s10489-023-04935-4
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• Coupled Global–Local object detection for large VHR aerial images
  Knowledge-Based Systems 2023 DOI: 10.1016/j.knosys.2022.110097
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• An online continual object detector on VHR remote sensing images with class imbalance
  Engineering Applications of Artificial Intelligence 2023 DOI: https://doi.org/10.1016/j.engappai.2022.105549
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• A novel loss function of deep learning in wind speed forecasting
  Energy 2022 DOI: 10.1016/j.energy.2021.121808
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• Cascaded Multiscale Structure With Self-Smoothing Atrous Convolution for Semantic Segmentation
  IEEE Transactions on Geoscience and Remote Sensing 2022 DOI: 10.1109/tgrs.2021.3088902
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• Superdense-scale network for semantic segmentation
  Neurocomputing 2022 DOI: 10.1016/j.neucom.2022.06.103
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