Student Spotlight: Sumit Sharma
June 29, 2026
Sumit Sharma is a doctoral student in animal science from Butwal, Nepal. He earned his bachelor of veterinary science and animal husbandry at the Agriculture and Forestry University in Nepal and now studies the use of data science and artificial intelligence to help dairy farmers make better-informed decisions under the guidance of Miel Hostens at Cornell.
What is your area of research and why is it important?
My research is about helping dairy farmers make faster, better-informed decisions using data science and artificial intelligence. Every day, dairy producers face a stream of choices: which animals may be at risk of disease, when to adjust nutrition, and how to respond to early warning signs in herd health. While modern farms generate large amounts of data through sensors, cameras, milking systems, and management software, these systems often operate independently and do not communicate effectively with one another. As a result, valuable information can be difficult to use in real time.
My work focuses on developing mathematical and computational tools, including artificial intelligence and machine learning, that bring these different sources of information together and turn them into practical insights. The goal is simple: help farmers make better decisions, improve efficiency and animal care, and make smarter use of the data that farms are already generating every day.
What are the larger implications of this research?
Dairy farming sits at the intersection of food security, resource efficiency, and environmental sustainability. The broader implication of this research is that better, data-driven decision-making at the farm level can scale into meaningful global impact. When individual farms make better data-driven decisions, ultimately in the long run improved herd health and management lead to higher productivity, less feed waste, lower greenhouse gas emissions per unit of milk, and reduced antibiotic use through earlier disease detection. This improves animal welfare while optimizing scarce resources such as feed, labor, and veterinary inputs and also supports equity by making advanced decision-support tools accessible to both small and large farms. At scale these changes contribute to a more sustainable and resilient livestock system for a growing global population.
What does it mean to you to have been selected for the FFAR Fellows Program?
It means a lot, honestly. Being selected as an FFAR Fellow is both an honor and a source of encouragement. Coming from a veterinary background and growing up in Nepal, I have seen firsthand how important practical, science-based solutions can be for farmers. The fellowship recognizes not only my research but also the potential impact that this work can have on agriculture. It is especially meaningful to join a cohort of scholars who are working to address some of the most pressing challenges facing food and agricultural systems. The opportunity motivates me to continue pursuing research that bridges scientific innovation and real-world application.
What will participating in the FFAR Fellows Program allow you to do that you may not have been able to otherwise?
The FFAR Fellows Program provides opportunities that extend beyond traditional graduate training. I am particularly excited about the mentorship, leadership development, and exposure to professionals working across academia, industry, and nonprofit organizations. Because my research sits at the intersection of animal science and artificial intelligence, learning from experts with different perspectives will help me think more broadly about how research can be translated into tools that producers can actually use. The program will also allow me to build a network of peers and mentors who share a commitment to advancing agriculture through innovation and collaboration. FFAR’s industry mentorship is especially valuable because it brings practical questions into focus, such as what dairy companies need from a model and what producers need to trust automated recommendations. Along with this, the cohort structure and the program’s Washington, D.C. sessions on science policy are also opportunities I would not have had otherwise, and both matter for the kind of career I want to build.
What are your hobbies or interests outside of your research or scholarship?
Outside of research, I enjoy being in nature, trying new sports, following whatever catches my curiosity, and learning music at my own pace. Whether it’s playing football or ping pong, discussing world affairs, or picking up a new tune, I like to keep life active, creative, and open to new experiences.
Why did you choose Cornell to pursue your degree?
I chose Cornell because of its strong reputation in animal science and its collaborative approach to real-world agricultural challenges. I was especially drawn to the opportunity to work at the intersection of animal health, data science, and technology while learning from leaders in the field. My advisor, Dr. Miel Hostens, leads one of the few groups focused on digital dairy management and data-driven decision support, which closely matches my interests. Beyond that, Cornell’s depth across animal science, computational science, and agricultural systems allows me to draw on expertise from multiple directions. As someone who has worked as a veterinarian and is interested in developing tools that directly benefit producers, I felt that Cornell offered the ideal place to pursue that goal while expanding my research skills and perspective.