_{Versión en español ↓}

I am an agricultural economist and lecturer-researcher in the Agricultural Science program at the Universidad Técnica de Machala, Ecuador. I develop and evaluate artificial intelligence methods for agricultural production and food quality, with a focus on computer vision, near-infrared (NIR) spectroscopy and machine learning.

My work centers on rigorous model evaluation: partitions that respect the experimental unit, leakage prevention, calibration, uncertainty, domain shift and reproducibility. As an economist, I also aim to quantify the costs, benefits and productive effects of these technologies.

Machine-learning classification of INIAP rice grains  
_{Comparison of machine-learning algorithms for classifying rice grains by morphology · DOI 10.3390/agriengineering8030100}

Shell-egg storage time from portable NIR spectra  
_{Storage-time estimation from portable spectra with validation that keeps each egg in a single partition}

Barley exposure stages from NIR spectra  
_{Plate-wise nested validation, spectral interpretation and out-of-fold predictions}

Geometric invariance in bean and rice morphometrics  
_{Representation sufficiency and evaluation of morphometric descriptors with documented partitions}

Morphometric classification of INIAP dry beans  
_{Classical and tabular models, TabPFN, calibration, selective prediction and redundancy analysis}

Class–source confounding and domain shift in maize images  
_{Provenance audit, class–source confounding and stability of architecture selection under domain shift}

Banana ripeness under experiment shift  
_{Leave-one-experiment-out validation, prospective spectral normalization and probabilistic reliability}

Persimmon storage time from hyperspectral imaging  
_{Baseline-referenced models, fruit-disjoint nested validation and matched null controls}

Pig instance segmentation and operational reliability  
_{Three architectures and three seeds: segmentation, counting, geometry and calibration on FaroPigSeg with date-disjoint partitions}

AgroVisión: from pixel to decision  
_{Computer vision applied to oil palm and broiler chickens (book in Spanish)}

_{Chemolab: Chemometrics and Intelligent Laboratory Systems.}

Area
Languages and data
Machine learning and vision
Environments and publishing

• B.Sc. in Agricultural Economics · Universidad Técnica de Machala (UTMACH), Ecuador
• M.Sc. in Information Systems, Business Intelligence and Big Data Analytics · Universidad Estatal de Milagro (UNEMI), Ecuador
• M.Sc. in Economics, Applied Artificial Intelligence · Universidad Estatal de Milagro (UNEMI), Ecuador
• Ph.D. student in Systems Engineering · Universidad Nacional del Callao, Peru

Statistics and Probability · Advanced Programming · Data Analysis and Modeling · Digital Image Processing · Technologies for the Agricultural Sector

Each repository documents its scope, data availability, licenses and limitations. I distinguish recorded results from reproduced runs, and internal evaluation from external validation. The editorial status and citation details of each work are given in its own repository.

I welcome collaboration on AI model evaluation, computer vision, NIR spectroscopy and the economic assessment of agricultural technologies.

Soy economista agropecuario y docente investigador de la carrera de Agropecuaria en la Universidad Técnica de Machala. Desarrollo y evalúo métodos de inteligencia artificial para la producción agropecuaria y la calidad de alimentos, con énfasis en visión por computador, espectroscopía NIR y aprendizaje automático, y en la evaluación rigurosa de los modelos: particiones acordes con la unidad experimental, prevención de fuga de información, calibración, cambio de dominio y reproducibilidad.

Los proyectos y su estado editorial están en las secciones anteriores; cada repositorio incluye su propia documentación. Me interesa colaborar en evaluación de modelos de IA, visión por computador, espectroscopía NIR y valoración económica de tecnologías agropecuarias.