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Conferences

Conference Publications

  1. Kamruzzaman, M., & Villordon, A. (2022). Quality assessment and grading of sweet potato using VNIR hyperspectral imaging. 2022 ASABE Annual International Meeting. ASABE Paper No. 2201112. St. Joseph, MI: ASABE.
  2. Ahmed, M. W., Esquerre, C., Singh, V., Leakey, D.B., & Kamruzzaman, M. (2023). NIR spectroscopy and chemometrics for detecting some selected components of lipid-producing sorghum biomass for biofuels. 2023 Omaha, Nebraska, July 9–12, 2023.
  3. Lee, D.H., & Kamruzzaman, M. (2023). Fully polymer-based, hemecofactor mimetic-contained nanozyme. 266th American Chemical Society National Meeting, August 15, 2023, San Francisco, CA.
  4. Lee, D.H., & Kamruzzaman, M. (2023). EpCAM: Eco-friendly, Polymer-based nanozyme integrated with colorimetric sensing platform for agricultural biomolecule detection. 266th American Chemical Society National Meeting, August 17, 2023, San Francisco, CA.
  5. Ahmed, M. T., Lu, Y., Villordon, A., & Kamruzzaman, M. (2023). Prediction of firmness of sweetpotatoes using VNIR hyperspectral imaging and machine learning. 2023 ASABE Annual International Meeting. Paper No. 2301414.
  6. Sobreira, C. H., Ferreira, M. V. D. S., & Kamruzzaman, M. (2023). Authentication of premium tea based on geographical origin using NIR spectroscopy and multivariate analysis. 2023 ASABE Annual International Meeting.
  7. Song, D., Ngumbi, E., & Kamruzzaman, M. (2023). Rapid and low-cost measurement method of normalized difference vegetation index in different scenes. 2023 ASABE Annual International Meeting. Paper No. 2300864.
  8. Lee, D.H., & Kamruzzaman, M. (2023). FODMAP: Food and Agriculture-Friendly, Organic Compound-Based, Degradable Nanozymes Integrated with an Optical Sensing Platform for Toxic Molecules Detection on Food Samples. Materials Research Society (MRS) Fall Meeting, November 26–December 1, 2023, Boston, MA.
  9. Lee, D.H., & Kamruzzaman, M. (2024). SNIFF: Sustainable, next-generation nanozyme integrated with optical sensing system for food and agricultural biomolecule sensing. Gordon Research Seminar, June 22–23, 2024, Manchester, NH.
  10. Lee, D.H., & Kamruzzaman, (2024). SNIFF: Sustainable, next-generation nanozyme integrated with optical sensing system for food and agricultural biomolecule sensing. Gordon Research Conference, June 23–28, 2024, Manchester, NH.
  11. Ahmed, M. W., Khaliduzzaman, A., Emmert, J. L., & Kamruzzaman, M. (2024). Non-destructive prediction of eggshell strength using FT-NIR spectroscopy combined with PLS Regression. 2024 Anaheim, California, July 28–31, 2024.
  12. Ahmed, M. T., & Kamruzzaman, M. (2024). Hyperspectral imaging and optimized convolutional neural network for quality assessment of sweetpotato. 2024 ASABE Annual International Meeting. Paper No. 2400873.
  13. Song, D., & Kamruzzaman, M. (2024). Corn chlorophyll content detection based on spectral reflectance inversion absorptance. 2024 ASABE Annual International Meeting. Paper No. 2400699.
  14. Lee, D.H., & Kamruzzaman, M. (2024). Nexus: Next-generation, sustainable organic nanozymes and their application for effective biomolecule detection. 268th American Chemical Society National Meeting, August 18, 2024, Denver, CO.
  15. Lee, D.H., & Kamruzzaman, M. (2024). Afoot: Amino-acid-based, food and agricultural-targeted, organic nanozyme for allergic biomolecule detection in food. 268th American Chemical Society National Meeting, August 21, 2024, Denver, CO.
  16. Wu, Q., & Kamruzzaman, M. (2025). Novel organic material-based A-C-Fe nanozyme for sensitive colorimetric detection of Hg2+. ACS Spring Conference, March 23-27, 2025, San Diego, CA
  17. Khaliduzzaman, A., Emmert, J. L., & Kamruzzaman, M. (2025). Detection of early dead embryos using hyperspectral imaging system. 2025 International Poultry Scientific Forum, January 27-28, 2025, Atlanta, GA.
  18. Monjur, O, Ahmed, M. T., Ahmed, M. W., & Kamruzzaman, M. (2025). Agro-Net: A Convolution-Attention Fusion based hyperspectral model for agro-food quality assessment. Accepted in MetaFood Workshop, CVPR-2025.

 

Khaliduzzaman

Dr. Khaliduzzaman earned his PhD in Bio-Sensing Engineering from Kyoto University, Japan. During his doctoral studies, he focused on non-destructive optical sensing techniques and imaging technologies for  egg and poultry industry. Following his PhD, he served as a JSPS Postdoctoral Fellow at Kyoto University. As a postdoctoral researcher at IOSNEL, his work focused on hyperspectral imaging  to enhance quality control and efficiency in the egg and poultry industries through the integration of advanced sensing and machine learning.​

1. Khaliduzzaman, A., Emmert, J. L., & Kamruzzaman, M (2025). Detection of early dead embryos using hyperspectral imaging system. 2025 International Poultry Scientific Forum, January 27-28, 2025, Atlanta, GA