Michael Kudenov

Bio

Dr. Kudenov completed his BS degree in Electrical Engineering at the University of Alaska Fairbanks in Fairbanks, AK in 2005. Upon graduation, his personal interest in astronomy and photography lead him to obtain his PhD in Optical Sciences at The University of Arizona (UA) in Tucson, AZ in 2009. Following his PhD, he remained as an Assistant Research Professor at the UA until departing for North Carolina State University in 2012. Research performed at the UA included visible and infrared imaging polarimetry, spectroscopy, 3D profilometry, interferometry, active learning, and lens design.

His current research is focused on developing novel imaging systems, interferometers, detectors, and anisotropic materials related to polarization and spectral sensing, for wavelengths spanning ultraviolet through the thermal infrared. He is particularly interested in developing novel anisotropic materials and detector technologies that better enable snapshot systems, which are capable of maximizing the spatial, spectral, and/or polarimetric information contained within a single image. Applications include biomedical imaging, remote sensing, food safety, 3D Imaging, and atmospheric monitoring.

Dr. Kudenov has authored 13 journal articles, 15 conference proceedings, 2 patents (pending), 1 book contribution, and is in the process of writing a new book on instrumentation. He is currently interested in obtaining undergraduate and graduate student researchers.

Publications

• Automated pipeline for leaf spot severity scoring in peanuts using segmentation neural networks , PLANT METHODS (2025)
• Deployment and analysis of instance segmentation algorithm for in-field yield estimation of sweet potatoes , PLANT PHENOME JOURNAL (2025)
• Drone-based polarization imaging system for leaf spot severity determination in peanut plants , PLANT PHENOME JOURNAL (2025)
• Enhancing peanut pre-sizing with PodTracker: A multiple pod tracking algorithm , PLANT PHENOME JOURNAL (2025)
• High-throughput classification and quantification of skinning phenotype in sweet potatoes , PLANT PHENOME JOURNAL (2025)
• Knowledge and Opportunities for Managing Plant-Parasitic Nematodes Using Decision Intelligence , PHYTOFRONTIERS (2025)
• Polarimetric peanut drone images of peanut crop infected with leaf spot , (2025)
• Polarimetric peanut drone images of peanut crop infected with leaf spot , (2025)
• Polarimetric peanut drone images of peanut crop infected with leaf spot , (2025)
• A Comparison of Three Automated Root-Knot Nematode Egg Counting Approaches Using Machine Learning, Image Analysis, and a Hybrid Model , Plant Disease (2024)