met.no thesis

Author: RobertoNeglia

_theses/met-no_dataset.md

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+---
+layout: base
+title: "⛈️ Spatiotemporal weather forecasting"
+keywords: "Spatio-temporal models, weather forecasting"
+contact_person: "Filippo Maria Bianchi, Roberto Neglia"
+---
+
+
+## 📝 Description
+The project focuses on applying advanced deep learning techniques to forecast spatiotemporal weather patterns and events.
+The student will work with the data from the [MET Norway](https://www.met.no/en) weather API, which provides high-resolution weather forecasts and historical observations. Once the data is prepared and pre-processed by building a spatiotemporal graph representation, the student will implement and fine-tune Spatiotemporal Graph Neural Networks (STGNNs) models using PyTorch and [Torch Spatiotemporal](https://torch-spatiotemporal.readthedocs.io/en/latest/), experimenting with different architectures and hyperparameters. By the end of the project, the student will have developed a strong understanding of meteorological data pre-processing, graph-based modeling, spatiotemporal deep learning, and its application to real-world weather forecasting tasks, which can be further explored in future research, as well as potential experience in deploying these models in production environments.
+
+**Data:** The student will use raw high-resolution weather data from the MET Norway API, which includes various meteorological variables such as temperature, precipitation, and wind speed.
+
+## 📨 Contact:
+Filippo Maria Bianchi <[email protected]>
+Roberto Neglia <[email protected]>