Rajesh Neupane

I am Rajesh Neupane, a graduate researcher and teaching assistant at Texas A&M University, working in the field of precision dairy management. My research focuses on developing AI- and sensor-based tools to improve animal health, welfare, and productivity in modern dairy systems.

My current projects include:

• Lameness detection: Using computer vision and machine learning for the preclinical detection of gait abnormalities in dairy cattle.
• Heat stress quantification: Designing systems to estimate panting scores from video data to monitor animal responses under heat load.
• Water efficiency in dairy cows: Analyzing data from rumen bolus sensors to identify water-efficient cows and reduce water use in dairy operations.
• Sensor development: Building Arduino and raspberry pi based sensors for dairy farming industry.
• Robotic milking efficiency: Studying failed milking attempts, teat connection patterns, and automation performance.
• Digital dermatitis detection: Applying computer vision for early detection of hoof lesions to improve animal welfare.

In addition to research, I serve as a teaching assistant for ANSC 107 and ANSC 108 (Basic Animal Science), where I support student learning, manage online accommodations, and lead discussions. I also actively participate in the Nepalese Student Association at Texas A&M University, helping to organize events and community activities.

I am passionate about combining data science, sensor technologies, and animal science to solve real-world challenges in livestock production. My long-term goal is to contribute to sustainable, resilient, and welfare-friendly livestock farming systems.

Outside of academics, I enjoy exploring agricultural innovations, engaging with community organizations, and reflecting on the future of small family farms vs. corporate farming systems—a topic I deeply care about in terms of food security and resilience.