Jensina Davis
PhD Student
Jensina Davis is a graduate student in the Complex Biosystems program at UNL specializing in Integrated Plant Biology. She received her B.S. in Agronomy and Seed Science with a minor in Statistics from Iowa State University in May 2022. Originally from Brookings, SD, she has completed several internships with companies in the agriculture industry and is passionate about advancing sustainability in agriculture using computational and statistical research methods.
In the News
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UNL graduate fellowship honors for lab students
Three students in our lab were honored as UNL graduate fellowship recipients. Congratulations to Jensina Davis (Hardin Fellow), Nikee Shrestha, and Sofiya Arora (Widaman Fellows). -
Hackathon wins at Bayer Agriculture Data
Ryleigh Kirby, Harshita Mangal, Sofiya Arora, Jensina Davis, Hadiya Kounsar, Ozgur Altundas, Amany Gomaa, and Karla Cuéllar joined the Bayer Agriculture Data Hackathon, where Sofiya’s team won first place, Hadiya and Ryleigh’s team took second, Jensina’s team placed third, and Ozgur’s team earned the social engagement award. -
Trio presents at Nebraska Plant Science Symposium
Jensina Davis, Harshita Mangal, and Sofiya Arora each presented research at the University of Nebraska Plant Science Symposium. -
Hardin fellowship for Jensina Davis
Jensina Davis received the Hardin Distinguished Graduate Fellowship Award from UNL’s Agricultural Research Division. -
Heuermann Award for Jensina Davis
Jensina Davis earned a Heuermann Award from the Center for Plant Science Innovation. -
Jensina Davis advances to candidacy
Congratulations to Jensina Davis on advancing to PhD candidacy.
Recent Publications
- (2025) 3D reconstruction enables high-throughput phenotyping and quantitative genetic analysis of phyllotaxy. Plant Phenomics doi: 10.1016/j.plaphe.2025.100023 bioRxiv doi: 10.1101/2024.10.03.616344
- (2025) Assessing the impact of yield plasticity on hybrid performance in maize. Physiologia Plantarum doi: 10.1111/ppl.70278 bioRxiv doi: 10.1101/2025.01.21.634104
- (2024) Sorghum segmentation and leaf counting using an in silico trained deep neural model. The Plant Phenome Journal doi: 10.1002/ppj2.70002
