Alexis Suero Mirabal (Ph.D. Student): Alexis is a dedicated researcher specializing in the integration of advanced computer vision techniques for high-throughput phenotyping in horticultural crops. Currently pursuing a PhD at NC State, he collaborates with interdisciplinary teams to develop innovative optical sensing methods and data-driven models for crop monitoring and phenotypic analysis. With a strong background in horticulture from Virginia Tech and Zamorano Pan-American School of Agriculture, Alexis combines expertise in data analysis, remote sensing, and agricultural production to drive impactful research in horticulture.
Caiwang Zheng (Postdoctoral Research Associate): Caiwang earned his Ph.D. in Geomatics from the University of Florida. His research specializes in remote sensing, UAV-based high-throughput phenotyping, and geospatial data science. He focuses on developing automated imaging platforms and deep learning models to extract plant traits—such as biomass, canopy structure, and stress indicators—across diverse cropping systems. His work emphasizes the integration of multi-scale remote sensing data—from satellite and airborne platforms to UAV-based imagery—combining multispectral, hyperspectral, and LiDAR sources for agricultural and ecological applications.
Jay Jinesh Shah (Research Assistant): Jay holds an M.S. in Computer Science from NC state and contributes to the program through computer vision research on a series of specialty crops. He is passionate about software development and the application of large language models in plant science. Jay has also played a key role in developing practical tools for plant breeders across multiple commodities, supporting data-driven decision-making in breeding programs.