Bio

Dr. Cranos Williams is the Goodnight Distinguished Professor of Agricultural Analytics at NC State University with primary and secondary appointments in the electrical and computer engineering and plant and microbial biology departments, respectively.  He also serves as the Platform Director of the Data-Driven Plant Sciences research platform of the North Carolina Plant Sciences Initiative (https://cals.ncsu.edu/psi/) and is the head of the EnBiSys Research Laboratory (https://research.ece.ncsu.edu/enbisys/).  Dr. Williams’ research lab develops methodologies familiar to other areas of electrical and computer engineering (e.g. computational intelligence, machine learning, system identification, nonlinear systems analysis and control, computer vision, and signal processing) to quantify, model, and predict the impact that genetic and environmental perturbations have on overall plant response.

Area(s) of Expertise

Machine Learning and AI
Communications, Controls, Signal Processing, and Learning
Bioelectronics Engineering

Publications

• KeySDL: sparse dictionary learning for keystone microbe identification from steady-state observations using a dynamical-systems model , BioData Mining (2026)
• Reflectance and interactance spectroscopy for detecting root knot nematode galls in harvested sweetpotatoes , Postharvest Biology and Technology (2026)
• Data from: Deployment and analysis of instance segmentation algorithm for in-field yield estimation of sweet potatoes , Open MIND (2025)
• Deployment and analysis of instance segmentation algorithm for in‐field yield estimation of sweet potatoes , The Plant Phenome Journal (2025)
• High‐throughput classification and quantification of skinning phenotype in sweet potatoes , The Plant Phenome Journal (2025)
• In-season yield forecasting using multitemporal remote sensing environmental observations and machine learning: Applications for sweetpotato in North Carolina, USA , European Journal of Agronomy (2025)
• KeySDL: Sparse Dictionary Learning for Keystone Microbe Identification , bioRxiv (Cold Spring Harbor Laboratory) (2025)
• Knowledge and Opportunities for Managing Plant-Parasitic Nematodes Using Decision Intelligence , PhytoFrontiers™ (2025)
• No more laborious stem counting: AI-powered computer vision enables identification and quantification of solid and hollow alfalfa stems at the pixel level , Smart Agricultural Technology (2025)
• Spatiotemporal dynamics of NF-κB/Dorsal inhibitor IκBα/Cactus in Drosophila blastoderm embryos , iScience (2025)

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