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Rui Kang

I am currently employed at NJAU, Nanjing, where I work on hyperspectral microscopic imaging, agri-food rapid detection technology, and deep learning, etc. Before that, I also did my Master and PhD at College of Engineering at NJAU, where I was co-advised by Prof. Kunjie Chen and Prof. Bosoon Park. I was funded by CSC and worked at USDA as a senior visiting scholar for two years. After 2020, I was employed at JAAS, where I conducted research related to smart agriculture. In 2023, I was appointed as a visiting professor at McGill University, collaborating with Professor Shangpeng Sun to develop a high-performance optical phenotyping platform for plants. In 2024, I was recruited as a globally high-level talent by Nanjing Agricultural University and appointed as an associate professor, where I engage in both scientific research and teaching activities.

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News

  • 08/2024, I joined the College of AI in NJAU and served as Associate Professor.
  • 04/2024, Our manuscript about 3D-AI-assisted HMI technology has been accepted by SNB.
  • 04/2024, Our manuscript about Fruit Detection and Tracking technology has been accepted by Plant Phenomics.
  • Recent Projects

    Currently, I am working on devoloping smart algorithms to accelerate the detection of foodborne pathogens occured in various food matrics. I also start to build tiny and intelligent optical systems to ensure the food quality and safety. We are now searching for the advanced optical imaging and sensing techniques for smart farming.

  • Hyperspectral Microscope Imaging Technology


  • Supported by NSFC, No 321016482

    In this project, we combined advanced deep learning framework with hyperspectral and microscope technology to identify various foodborne bacteria. This technology can realize non-invasive classification of foodborne pathogens at the single-cell level, this digital diagnostic approach has potential for commercial applications.


  • High Throughput Plant Phenotyping Platforms


  • In this project, we developed rapid optical detection methods for plant phenotyping in both indoor and field towards real-world scenery, especially for the health monitoring task for cherry tomato growths. The advanced optical sensors and mobile platforms have been developed to meet the requirements in various tasks.


  • Agricultural Smart Factory


  • In this project, we proposed a totally intelligent automation solution for growing tomatoes in the green house. By adopting our methods, the distributed processing equipment will be centrally managed and controlled automatically.

    Talks

  • 07/2019, Deep learning methods for STEC Classification at IAFP 2019 workshop.
  • Research

    I'm interested in developing efficient intelligent tools for smart agriculture implementation (e.g. classification, detection, and spatial-spectral fusion) using optical, automatic, and robotic devices.

    Publications:

    1. Rapid identification of foodborne bacteria with hyperspectral microscopic imaging and artificial intelligent classification algorithms
      Rui Kang, Bosoon Park, Qin Ouyang, Ni Ren
      Food Control 2021 | Paper

    2. Physicochemical indicators coupled with multivariate analysis for comprehensive evaluation of matcha sensory quality
      Jizhong Wu, Qin Ouyang, Bosoon Park, Rui Kang, Bosoon Park, Zhen Wang, Quansheng Chen
      Food Chemistry 2021 | Paper

    3. Simultaneous quantification of chemical constituents in matcha with visible-near infrared hyperspectral imaging technology
      Qin Ouyang, Li Wang, Bosoon Park, Rui Kang, Bosoon Park, Quansheng Chen
      Food Chemistry 2021 | Paper

    4. Classification of foodborne bacteria using hyperspectral microscope imaging technology coupled with convolutional neural networks
      Rui Kang, Bosoon Park, Qin Ouyang, Kunjie Chen
      Applied Microbiology and Biotechnology 2020 | Paper

    5. Assessment of matcha sensory quality using hyperspectral microscope imaging technology
      Qin Ouyang, Li Wang, Bosoon Park, Rui Kang, Zhen Wang, Quansheng Chen, Zhiming Guo
      LWT 2020 | Paper

    6. Single-cell classification of foodborne pathogens using hyperspectral microscope imaging coupled with deep learning frameworks
      Rui Kang, Bosoon Park, Matthew Eady, Qin Ouyang, Kunjie Chen
      Sensors and Actuators B: Chemical 2020 | Paper

    7. An experimental study of stunned state detection for broiler chickens using an improved convolution neural network algorithm
      Changwen Ye, Zhenwei Yu, Rui Kang, Khurram Yousaf, Chao Qi, Kunjie Chen, Yuping Huang
      Computers and Electronics in Agriculture 2020 | Paper

    8. A novel hyperspectral microscope imaging technology for rapid evaluation of particle size distribution in matcha
      Qin Ouyang, Yongcun Yang, Bosoon Park, Rui Kang, Quansheng Chen, Zhiming Guo, Huanhuan Li
      Journal of Food Engineering 2021 | Paper

    9. Identifying non-O157 Shiga toxin-producing Escherichia coli (STEC) using deep learning methods with hyperspectral microscope images
      Rui Kang, Bosoon Park, Kunjie Chen
      Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2019 | Paper

    10. Automatic Identification of Asian Rice Plant-Hopper Based on Image Processing
      Jialiang Wang, Rui Kang, Kunjie Chen, Deying Liu, Haiming Yu
      Applied Engineering in Agriculture 2017 | Paper

    11. Development of Online Detection and Processing System for Contaminants on Chicken Carcass Surface
      Rui Kang, Kai Yang, Xiaxia Zhang, Wei Wu, Kunjie Chen
      Applied Engineering in Agriculture 2016 | Paper

    Services

  • Program Members of ASABE, IJABE, AOCBFE , etc.

  • Awards

  • 2017, CSC Scholarship

  • 2016, National Scholarship for Graduate Students

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