Michael Tross

Michael Tross

PhD Student

  • Cohort PhD Students
  • Tenure 2024
  • Now AI Developer, Corteva Agriscience

Michael Tross is graduate student on the Integrated Plant Biology track of the Complex Biosystems graduate program at UNL. He joined the lab in the summer of 2020 after rotating in the lab in his first year. He received his Bachelors from Doane University in 2019, where he worked with Tessa Durham Brooks phenotyping maize plants. He hails from the town of Sandy Point, located on the small island of St. Kitts in the Caribbean. He has previously worked as both a lab technician and a high school teacher.

Google Scholar Profile

TA: Laboratory Section of LIFE 120 – Fundamentals of Biology

In the News

  • Plants People Planet cover feature

    Michael Tross and a paper led by Nikee Shrestha are featured on the cover of Plants, People, Planet. Read the cover write-up, which links to the paper.

  • Corteva genotyping tour and lab visit

    Michael Tross, who earned his PhD in Plant Science in our lab and now works as an AI data scientist at Corteva, arranged for nearly the entire lab to drive from Lincoln to Johnston to talk science with Corteva researchers and tour their impressive high-throughput genotyping facilities.

  • Michael Tross featured in Midwest Messenger

    Dr. Michael Tross, a recent PhD graduate from our lab, featured in a Midwest Messenger article on AI for agriculture!

  • Michael Tross defends PhD

    Michael Tross successfully defended his PhD thesis. Congratulations Dr. Tross! Michael will be leaving us for a job as an AI Data Scientist at Corteva Agrisciences.

  • Maize Genome Conference presentations

    The Schnable Lab presented at the Maize Genome Conference hosted in Raleigh, NC. Two of our grad students presented lightning talks about their posters: Nikee Shrestha and Michael Tross. In addition, Harshita Mangal, Hongyu Jin, Vladimir Torres, Jensina Davis, Waqar Ali, and Ramesh Kanna presented posters.

Recent Publications

  • Tross MC, Duggan G, Shrestha N, Schnable JC (2024) Models trained to predict differential expression across plant organs identify distal and proximal regulatory regions. doi: 10.1101/2024.06.04.597477 Preprint
  • Powadi A, Jubery T, Tross M, Shrestha N, Coffey L, Schnable JC, Schnable PS, Ganapathysubramanian B (2025) Enhancing yield prediction from plot-level satellite imagery through genotype and environment feature disentanglement. Frontiers in Plant Science doi: 10.3389/fpls.2025.1617831
  • Davis JM, Gaillard M, Tross MC, Shrestha N, Ostermann I, Grove RJ, Li B, Benes B, Schnable JC (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
  • Shrestha N, Powadi A, Davis J, Ayanlade TT, Liu H, Tross MC, Mathivanan RK, Bares J, Lopez-Corona L, Turkus J, Coffey L, Tubery TZ, Ge Y, Sarkar S, Schnable JC, Ganapathysubramanian B, Schnable PS (2025) Plot-level satellite imagery can substitute for UAVs in assessing maize phenotypes across multistate field trials. Plants Planet People doi: 10.1002/ppp3.10613 agriRxiv doi: 10.31220/agriRxiv.2024.00251
  • Istipliler D, Tross MC, Bouwens B, Jin H, Yufeng Ge, Yang J, Mural RV, Schnable JC (2025) Heritability, heterosis, and hybrid/inbred classification ability of maize leaf hyperspectral signals under changing soil nitrogen. Crop Science doi: 10.1002/csc2.70073
  • Shrestha N, Mangal H, Torres-Rodriguez JV, Tross MC, Lopez-Corona L, Linders K, Sun G, Mural RV, Schnable JC (2025) Off-the-shelf image analysis models outperform human visual assessment in identifying genes controlling seed color variation in sorghum. The Plant Phenome Journal doi: 10.1002/ppj2.70013 bioRxiv doi: 10.1101/2024.07.22.604683
  • Powadi A, Jubery TZ, Tross M, Schnable JC, Ganapathysubramanian B (2024) Disentangling genotype and environment specific latent features for improved trait prediction using a compositional autoencoder. Frontiers in Plant Science doi: 10.3389/fpls.2024.1476070
  • Ostermann I, Benes B, Gaillard M, Li B, Davis J, Grove RJ, Shrestha N, Tross MC, Schnable JC (2024) Sorghum segmentation and leaf counting using an in silico trained deep neural model. The Plant Phenome Journal doi: 10.1002/ppj2.70002
  • Jin H, Tross MC, Tan R, Newton L, Mural RV, Yang J, Thompson AM, Schnable JC (2024) Imitating the "breeder’s eye": predicting grain yield from measurements of non-yield traits. The Plant Phenome Journal doi: 10.1002/ppj2.20102 bioRxiv doi: 10.1101/2023.11.29.568906
  • Korth N, Yang Q, Van Haute MJ, Tross MC, Peng B, Shrestha N, Zwiener M, Mural RV, Schnable JC, Benson AK (2024) Genomic co-localization of variation affecting agronomic and human gut microbiome traits in a meta-analysis of diverse sorghum. doi: 10.1093/g3journal/jkae145 bioRxiv doi: 10.1101/2023.09.20.558616
  • Tross MC, Grzybowski M, Jubery TZ, Grove RJ, Nishimwe AV, Torres-Rodriguez JV, Sun G, Ganapathysubramanian B, Ge Y, Schnable JC (2024) Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel. The Plant Phenome Journal doi: 10.1002/ppj2.20106 bioRxiv doi: 10.1101/2023.12.15.571950
  • Gaillard M, Benes B, Tross MC, Schnable JC (2023) Multi-view triangulation without correspondences. Computers and Electronics in Agriculture doi: 10.1016/j.compag.2023.107688
  • Mural RV, Sun G, Grzybowski M, Tross MC, Jin H, Smith C, Newton L, Andorf CM, Woodhouse MR, Thompson AM, Sigmon B, Schnable JC (2022) Association mapping across a multitude of traits collected in diverse environments identifies pleiotropic loci in maize. Gigascience doi: 10.1093/gigascience/giac080 bioRxiv doi: 10.1101/2022.02.25.480753
  • Tross MC, Gaillard M, Zweiner M, Miao C, Grove RJ, Li B, Benes B, Schnable JC (2021) 3D reconstruction identifies loci linked to variation in angle of individual sorghum leaves. PeerJ doi: 10.7717/peerj.12628 bioRxiv doi: 10.1101/2021.06.15.448566