College of Agriculture and Bioresources

Research Area(s)

  • Food microbiology and molecular microbiology
  • Food safety
  • Microbial ecology
  • Fermentation


Department of Food and Bioproduct Sciences

Research Interests

Dr. Kaidi Wang’s research program is centered on studying food microbiology to improve the safety, quality and sustainability of agri-food products. Dr. Wang primarily works on the microbial ecology of foodborne pathogens (e.g., Salmonella) to better understand its survival in the agroecosystem, emphasizing on biofilm and viable but non-culturable (VBNC) state. She is also broadly interested in the detection and characterization of foodborne pathogens using a range of advanced techniques, including but not limited to optical tweezers, microfluidic “lab-on-a-chip”, vibrational spectroscopy, machine learning, transcriptomics sequencing, and metabolomics. Additionally, her research extends to the application of novel molecular tools, sensor-enabled data, and artificial intelligence to study microbial behavior in food fermentation. The knowledge gained from her research aims to contribute to a safe and sustainable food supply chain.


Ph.D. (Food Science), McGill University

M.Sc. (Food Science), University of British Columbia

B. Eng. (Food Science and Engineering), Zhejiang University, China

Selected Recent Publications

Wang, K., Chen, J., Martiniuk, J., Ma, X., Li, Q., Measday, V., & Lu, X.* (2023). Species identification and strain discrimination of fermentation yeasts Saccharomyces cerevisiae and Saccharomyces uvarum using Raman spectroscopy and convolutional neural networks. Applied and Environmental Microbiology, 89, e01673-23.

Wang, K.#, Ma, X.#, Chou, K. C., Li, Q., & Lu, X.* (2022). Conditional generative adversarial network for spectral recovery to accelerate single-cell Raman spectroscopic analysis. Analytical Chemistry, 94(2), 577-582.

Wang, K., Chen, L., Ma, X., Ma, L., Chou, K. C., Cao, Y., Khan, U. H. I., Gölz, G., & Lu, X.* (2020). Arcobacteridentification and species determination using Raman spectroscopy combined with neural networks. Applied and Environmental Microbiology86, e00924-20.

Wang, K.#, Han, L.#, Ma, L., Delaquis, P., Bach, S., Feng, J., & Lu, X.* (2020). Rapid determination of viable but non-culturable Escherichia coli O157:H7 and Salmonella enterica in fresh produce by loop-mediated isothermal amplification coupled with a propidium monoazide treatment. Applied and Environmental Microbiology, 86,e02566-19.

(# Co-first author; * Corresponding author)