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Illinois Optical Sensing and
Nanozyme Engineering Lab

About us

Welcome to the Illinois Optical Sensing and Nanozyme Engineering Lab (IOSNEL)

At IOSNEL, we advance the frontiers of analytical sensing and intelligent systems through the integration of spectroscopy, hyperspectral imaging, explainable artificial intelligence (XAI), and nanozyme technologies. Our work bridges deep learning with sensor-based platforms to drive innovation in agriculture and food systems monitoring.

Our research leverages a diverse suite of optical sensing tools including NIR spectroscopy, FTIR spectroscopy, and RGB and hyperspectral imaging for rapid and non-destructive analysis. We also develop deep learning-based hyperspectral image reconstruction methods to enhance data quality and usability from standard RGB imaging.

Our lab is pioneering the development of fully organic nanozymes as biocompatible and sustainable alternatives to traditional inorganic nanozymes for point-of-use diagnostics and portable sensor systems for detecting toxic agricultural biomolecules. These nanozyme-enabled platforms allow sensitive, low-cost detection of toxins, allergens, and contaminants across various matrices.

By integrating sensor technology, AI, and nanoengineering, we are building intelligent, scalable systems for real-world applications. Whether you’re a researcher, industry partner, or student, we invite you to explore our work and collaborate in shaping the future of smart sensing and sustainable innovation.

Our lab is committed to ensuring digital accessibility for people with disabilities. We are continually improving the user experience and applying relevant accessibility standards. If you encounter any issues, please contact us at mkamruz1@illinois.edu

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