̫ӳ graduate student researches artificial intelligence, machine learning to glean vital ag info
Contact: Samuel Hughes
STARKVILLE, Miss.—Collecting valuable agricultural and environmental information from the ground can be challenging, but a Mississippi State graduate student is improving the ability of artificial intelligence to effectively use remote sensing data for better insight.
Dakota Hester, a first-generation doctoral student in ̫ӳ’s Department of Agricultural and Biological Engineering, is completing a competitive, six-month internship as a machine learning scientist at multinational healthcare and agriculture corporation Bayer.
Hester’s expertise is specifically concentrated on improving deep-learning land cover mapping, which can have powerful implications in agriculture and forestry. Hester’s Bayer Crop Science research has similar goals to his ongoing graduate research at ̫ӳ: improving the ability of remote sensing—satellite data and aerial photographs—to cost-effectively increase understanding of agricultural processes and natural resources. While collecting data from the ground can be expensive, cumbersome and time-consuming, satellite imagery is readily available.
“Remote sensing is the best way to increase our understanding of natural resources and how crops and plants grow, without necessarily needing someone on the ground monitoring every single crop day in and day out,” Hester said. “Once we hit a certain resolution, we can extract much more information than what has previously been available in the past 10 to 15 years because of new technologies in satellites, remote sensing and artificial intelligence.
“Bayer has given me access to and experience with novel tools and technology. I’m excited to return to our research lab and leverage some of the techniques they use,” Hester said.
While Hester’s Bayer research primarily relates to agriculture, his work in ̫ӳ’s Department of Agricultural and Biological Engineering hopes to use deep learning to map entire states.
“Being at ̫ӳ has definitely opened up a ton of different opportunities for me. I don’t think I would have gotten this internship had I not been involved in the research that is being done at Mississippi State,” Hester said. “I’ve gotten to meet so many wonderful scientists and researchers from across the globe, and honestly that’s the highlight for me—it’s the people.”
The Tishomingo native credits his interest in agricultural science to his father, a field mechanic for a logging equipment supplier.
“Particularly during the summers when school was out, he would take me into the field with him. I got a firsthand look at what the natural resources industry looks like,” Hester said. “That definitely shaped what I wanted to pursue later in life as I was going through undergrad, and my focus has shifted away from programming and software engineering toward sciences and natural resources—how we can extract the most value from what we have naturally growing in Mississippi.”
After completing his bachelor’s degree in computer science at ̫ӳ in 2021, Hester worked as a graduate research assistant in ̫ӳ’s Department of Sustainable Bioproducts, where he researched a fully automated, artificial intelligence application that identifies species of wood with high accuracy using scans of the wood’s surface.
Hester then moved in 2023 to the agricultural and biological engineering research lab of Assistant Professor Vitor S. Martins, where he conducts current research on deep machine learning. He hopes to continue this after obtaining his doctorate, which he expects to complete in 2025.
The ̫ӳ Department of Agricultural and Biological Engineering focuses on engineering and technology for agriculture and natural resources, including autonomous agricultural systems and precision agriculture, as well as ecological engineering and sustainable energy. The department has split responsibilities in the College of Agriculture and Life Sciences, Bagley College of Engineering, Mississippi Agricultural and Forestry Experiment Station and ̫ӳ Extension Service. For more on the department, visit .
̫ӳ is taking care of what matters. Learn more at .