Mohammed Kamruzzaman

Mohammed Kamruzzaman is an Assistant Professor in the Department of Agricultural and Biological Engineering at the University of Illinois at Urbana-Champaign (UIUC), with affiliations to the Center for Digital Agriculture and the National Center for Supercomputing Applications (NCSA). His research focuses on advancing food safety and agricultural quality assessment through innovative technologies like hyperspectral imaging, near-infrared spectroscopy, and nanozyme-based sensing systems.

Key research areas include non-destructive food quality analysis, smart sensor development, and AI-driven solutions for agriculture. He explores applications ranging from detecting adulteration in food products to optimizing biomass characterization for biofuels. His work integrates machine learning and chemometrics to enhance precision in agricultural and biomedical diagnostics.

Recent publications highlight advancements in hyperspectral imaging for egg and hatchery industry applications, AI-enabled optical sensing for food drying processes, and sustainable nanozyme platforms for toxin detection. His contributions bridge engineering, chemistry, and computer science to address global challenges in food security and environmental sustainability.

Collaborations span academia and industry, with a focus on translating research into practical tools for farmers, food processors, and environmental monitoring systems. He actively publishes in high-impact journals like Artificial Intelligence Review, Food Chemistry, and Computers and Electronics in Agriculture.