Priv.-Doz. Dr. Joerg Leukel

Contact

Emailjoerg.leukel[at]uni-hohenheim.de
Phone+49 (711) 459 23968
AddressUniversity of Hohenheim
Information Systems and Digital Technologies (580e)
Schwerzstr. 35, 70599 Stuttgart, Germany

Teaching

  • Digital Transformation of the Healthcare Industry [5304-460, Master, English]
  • E-Health [5304-290, Bachelor, German]
  • Kooperative Intelligente Informationsysteme [5304-450, Master, German]
  • Projects in Bioeconomic Research - Group Project [1505-410, Master, English]
  • Profilseminar Projekt Information Systems [5801-360, Bachelor, German]
  • Wissensverarbeitung [24160, Bachelor, German]

Third-party Funded Research Projects

Project titleFunded by
Digital value chains for sustainable small-scale agriculture; sub-project 10: Machine learning in grassland management (DiWenkLa)Federal Ministry of Food and Agriculture (BMEL)
Artificial intelligence for digital & sustainable road construction (KInaStra)Ministry of Economic Affairs, Labor and Tourism Baden-Württemberg
Artificial intelligence for efficient and resilient agricultural technology (KINERA)Federal Ministry of Food and Agriculture (BMEL)
Platform ecosystem for innovative maintenance management through predictive maintenance (PlatonaM)Federal Ministry for Economic Affairs and Climate Action (BMWi)

Recent Publications

  • Leukel, J., Scheurer, L., & Zimpel, T. (2025). Overinterpretation of evaluation results in machine learning studies for maize yield prediction: A systematic review. Computers and Electronics in Agriculture, 230, Article 109892, https://doi.org/10.1016/j.compag.2024.109892

  • Müller, M., Gohl, S., Groll, K., & Leukel, J. (2025). Wie GreenAI-Bauprozesssteuerung und automatisierte CO2-Bilanzierung die CO2-Emissionen senken. In Schäfer, F. (Ed.), 4. Kolloquium Straßenbau in der Praxis: Fachtagung zum Planen, Bauen, Erhalten, Betreiben unter den Aspekten von Nachhaltigkeit und Digitalisierung. Tagungshandbuch 2025 (pp. 381-387). expert.

  • Scheurer, L., Leukel, J., Zimpel, T., Werner, J., Perdana-Decker, S., & Dickhoefer, U. (2024). Predicting herbage biomass on small-scale farms by combining sward height with different aggregations of weather data. Agronomy Journal, 116(6), 3205-3221. https://doi.org/10.1002/agj2.21705

  • Leukel, J., Scheurer, L., & Sugumaran, V. (2024). Machine learning models for predicting physical properties in asphalt road construction: A systematic review. Construction and Building Materials, 440, Article 137397. https://doi.org/10.1016/j.conbuildmat.2024.137397

  • Leukel, J., Özbek, G., & Sugumaran, V. (2024). Application of logistic regression to explain internet use among older adults: A review of the empirical literature. Universal Access in the Information Society, 23, 621-635. https://doi.org/10.1007/s10209-022-00960-1

  • Stumpe, C., Leukel, J., & Zimpel, T. (2024). Prediction of pasture yield using machine learning-based optical sensing: A systematic review. Precision Agriculture, 25(1), 430-459. https://doi.org/10.1007/s11119-023-10079-9

  • Zimpel, T., Perdana-Decker, S., Leukel, J., Scheurer, L., Dickhoefer, U., & Werner, J. (2023). P42 Estimating pasture yield using machine learning and weather data: Effect of small and large prediction horizons. Animal-science proceedings, 14(4), 628-629. https://doi.org/10.1016/j.anscip.2023.04.137

  • Leukel, J., González, J., & Riekert, M. (2023). Machine learning-based failure prediction in industrial maintenance: Improving performance by sliding window selection. International Journal of Quality & Reliability Management, 40(6), 1449-1462. https://doi.org/10.1108/IJQRM-12-2021-0439

  • Leukel, J., Zimpel, T., & Stumpe, C. (2023). Machine learning technology for early prediction of grain yield at the field scale: A systematic review. Computers and Electronics in Agriculture, 207, Article 107721. https://doi.org/10.1016/j.compag.2023.107721

  • Leukel, J., Schehl, B., & Sugumaran, V. (2023). Digital inequality among older adults: Explaining differences in the breadth of internet use. Information, Communication & Society, 26(1), 139-154. https://doi.org/10.1080/1369118X.2021.1942951

  • Leukel, J., & Sugumaran, V. (2022). How novice analysts understand supply chain process models: An experimental study of using diagrams and text. Journal of Enterprise Information Management, 35(3), 757-773. https://doi.org/10.1108/JEIM-11-2020-047

  • Kösebay, M., Kirn, S., Wallrafen, S., Leukel, J., & Gierl, F. (Eds.) (2021). Stadt der Zukunft – Smartes Stadtmobiliar für mehr Teilhabe im Alter. medhochzwei.

  • Leukel, J., González, J., & Riekert, M. (2021). Adoption of machine learning technology for failure prediction in industrial maintenance: A systematic review. Journal of Manufacturing Systems, 61, 87-96. https://doi.org/10.1016/j.jmsy.2021.08