PDE-STH: Plant Disease Epidemiology Sensor Technology Hub

PDE-STH: Plant Disease Epidemiology Sensor Technology Hub team uses advanced sensor-based technologies to better characterize plant disease epidemics.



The team is committed to transforming our understanding of plant diseases through state-of-the-art sensor technology. Driven by the need to enhance agricultural productivity and sustainability, PDE-STH will employ sophisticated sensor data to detect early signs and symptoms of disease in crops, facilitating timely interventions. The primary objective is to harness data gathered from sensor arrays across diverse agricultural settings, with the ultimate aim of creating sophisticated predictive models. By integrating a variety of sensing platforms with advanced measurement science techniques, PDE-STH seeks to deliver accurate, real-time insights into plant health and disease dynamics. Specific projects include the development of precise algorithms for the real-time monitoring of fungal pathogens in field crops and the creation of intuitive interfaces for accessing disease forecasts.



  • Computer vision
  • Machine learning
  • Deep learning
  • Agricultural engineering


  • General understanding of agriculture.
  • Computer Skills: Java, Python, LangChain, Jupyter Notebook, Unity, C#, R, JavaScript, HTML, CSS, C.
  • Experience with team projects.
  • Experience designing and developing intuitive interfaces (e.g., dashboards, visualization tools, etc.).