Database, And Machine Learning Intern
• Develop a back-end database in MariaDB to manage soil and plant analysis data, enabling efficient data storage and retrieval crucial for digital agronomist projects.• Evaluate and enhance the current data imputation methods using machine learning and statistical techniques to fill in missing values to enhance data accuracy and reliability.• Collaborate with an international team of developers and students to build an interactive dashboard; write SQL queries, stored procedures, and develop APIs to support seamless data visualization and analysis.• Contribute to a multi-disciplinary project that formed the backbone of a $1M SBIR federal proposal grant to the USDA.