MSU graduate student researches artificial intelligence, machine learning to glean vital ag info
Contact: Samuel Hughes
STARKVILLE, Miss.鈥擟ollecting valuable agricultural and environmental information from the ground can be challenging, but a 幺力视频 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 MSU鈥檚 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鈥檚 expertise is specifically concentrated on improving deep-learning land cover mapping, which can have powerful implications in agriculture and forestry. Hester鈥檚 Bayer Crop Science research has similar goals to his ongoing graduate research at MSU: improving the ability of remote sensing鈥攕atellite data and aerial photographs鈥攖o 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.
鈥淩emote 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,鈥 Hester said. 鈥淥nce 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.
鈥淏ayer has given me access to and experience with novel tools and technology. I鈥檓 excited to return to our research lab and leverage some of the techniques they use,鈥 Hester said.
While Hester鈥檚 Bayer research primarily relates to agriculture, his work in MSU鈥檚 Department of Agricultural and Biological Engineering hopes to use deep learning to map entire states.
鈥淏eing at MSU has definitely opened up a ton of different opportunities for me. I don鈥檛 think I would have gotten this internship had I not been involved in the research that is being done at 幺力视频,鈥 Hester said. 鈥淚鈥檝e gotten to meet so many wonderful scientists and researchers from across the globe, and honestly that鈥檚 the highlight for me鈥攊t鈥檚 the people.鈥
The Tishomingo native credits his interest in agricultural science to his father, a field mechanic for a logging equipment supplier.
鈥淧articularly 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,鈥 Hester said. 鈥淭hat 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鈥攈ow we can extract the most value from what we have naturally growing in Mississippi.鈥
After completing his bachelor鈥檚 degree in computer science at MSU in 2021, Hester worked as a graduate research assistant in MSU鈥檚 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鈥檚 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 MSU 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 MSU Extension Service. For more on the department, visit .
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