Team Leader
Megha Poyyara Saiju
Texas A&M University
Animal Science
megha.poyyarasaiju@ag.tamu.edu
Project Type
Research
Who Can Join
Staff/Postdoctoral Scholars, Graduate Students, Masters Students, Undergraduate Students
Project Description
This project focuses on developing and applying the Economic Index—an innovative genetic selection tool to improve profitability, sustainability, and efficiency in dairy herds. The goal is to identify, breed, and retain cattle that maximize lifetime production, feed conversion efficiency, and longevity while reducing methane emissions and environmental impact.
A core component of this project is the development of a Large Language Model (LLM) designed to support breeding decisions related to genetic selection. The LLM will integrate genomic, phenotypic, and economic data to provide real-time, explainable recommendations for optimal breeding strategies. Students will participate in agent based simulation modeling, data analysis, LLM development and fine-tuning, and creation of a web-based decision tool that merges simulation, machine learning, and LLM outputs. This tool will help producers, consultants, and policymakers make informed, data-driven breeding decisions in real-time.
Team Needs
We welcome students with skills in data analysis, programming (Python/R), simulation modeling, generative AI (skills or strong interest), GitHub proficiency, and scientific writing. Experience in statistical modeling or machine learning is preferred. Weekly team meetings will be conducted in person or virtually.
Special Opportunities
Participants will gain experience in genomic selection strategies, simulation modeling, LLM-based decision support systems, and web-based decision tool development. Opportunities include presenting research at conferences, co-authoring scientific publications, and collaborating with industry leaders. This project is ideal for students seeking to apply data science, artificial intelligence, and genetics to real-world challenges in sustainable agriculture.