Thanks for visiting!
- From Nepal
- Graduate of Budhanilkantha School
- BS, MS from Stanford
- Researcher at Wageningen University and Research
The title of my PhD was: Machine learning for large-scale crop yield forecasting.
I am currently coordinating an effort to create a benchmark for subnational crop yield forecasting. Many researchers from around the world are contributing to this effort. We are all part of the Machine Learning for Agricultural modeling (AgML) team of Agricultural Model Intercomparison and improvement Project (AgMIP).
- Machine learning for large-scale crop yield forecasting
- Machine learning for regional crop yield forecasting in Europe
- Interpretability of deep learning models for crop yield forecasting
- A weakly supervised framework for high-resolution crop yield forecasts (ICLR workshop paper)
- A weakly supervised framework for high-resolution crop yield forecasts (Journal paper)
- Beyond assimilation of leaf area index: Leveraging additional spectral information using machine learning for site-specific soybean yield prediction
- Big data in agriculture: Between opportunity and solution