Dr. Christian Post

Wissenschaftlicher Mitarbeiter

• Entwicklung eines systemorientierten Serious Games zur virtuellen Simulation von Konzepten und Handlungsoptionen zur Verminderung von Stickstoffemissionen in der Schweinehaltung (PigNPlay)

• Datenkompetenzen in der Nutztierhaltung - Maschinelles Lernen zur automatischen, robusten Verhaltensklassifikation bei Schweinen (DaNuMa)

2023 Dr. agr. (Rheinische Friedrichs- Wilhelm-Universität Bonn)

Titel: "Challenges related to statistical methods and sensor systems for the daily prediction of health disorders in individual dairy cows"

2017 M.Sc. Agrar- und Lebensmittelwirtschaft, Controlling in der Nutztierhaltung (Hochschule Osnabrück)

2014 B.Sc. Landwirtschaft (Hochschule Osnabrück)

Post, C, Rietz, C, Buescher, W, Müller, U (2021). The Importance of Low Daily Risk for the Prediction of Treatment Events of Individual Dairy Cows with Sensor Systems. Sensors. 21(4). DOI: 10.3390/s21041389

Post, C, Rietz, C, Buescher, W, Müller, U (2020). Using Sensor Data to Detect Lameness and Mastitis Treatment Events in Dairy Cows: A Comparison of Classification Models. Sensors. 20(14). DOI: 10.3390/s20143863.

Ghaffari, M, Jahanbekam, A, Post, C, Sadri, H, Schuh, K, Koch, C, Sauerwein, H (2020). Discovery of different metabotypes in overconditioned dairy cows by means of machine learning. Journal of Dairy Science. 103(10). DOI: 10.3168/jds.2020-18661.

Ghaffari, M, Monneret, A, Hammon, H, Post, C, Müller, U, Frieten, D, Gerbert, C, Dusel, G, Koch, C (2022): Deep convolutional neural networks for the detection of respiratory disease and scours in preweaned dairy calves using data from automated milk feeders. Journal of Dairy Science. 105 (12). https://doi.org/10.3168/jds.2021-21547