Skip to content
View tom-andersson's full-sized avatar
62 followers · 24 following

Achievements

Achievement: Pair ExtraordinaireAchievement: StarstruckAchievement: Pull Shark

Achievements

Achievement: Pair ExtraordinaireAchievement: StarstruckAchievement: Pull Shark

Highlights

  • Pro

Block or report tom-andersson

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
tom-andersson/README.md

Hi, I'm Tom 👋

I'm a researcher and engineer building AI prediction tools for climate change mitigation and adaptation.

I believe both engineering and theory are vital for scaling AI applications into real-world impact. (I'm still trying to work out if I'm a scientist who's secretly an engineer or an engineer who's secretly a scientist!)

While you're here, you might like to check out some of my projects:

  • 💻 DeepSensor, a Python package for modelling xarray and pandas data with neural processes to tackle diverse environmental prediction tasks.
  • ❄️ IceNet, a codebase for reproducing our Nature Communications paper on seasonal Arctic sea ice forecasting with deep learning. IceNet is being operationalised over at icenet-ai!

Feel free to reach out through my contact details on the left.

Pinned Loading

  1. alan-turing-institute/deepsensor alan-turing-institute/deepsensor Public

    A Python package for tackling diverse environmental prediction tasks with NPs.

    Python 89 16

  2. deepsensor_gallery deepsensor_gallery Public

    A gallery of DeepSensor research applications

    Jupyter Notebook 5 2

  3. icenet-paper icenet-paper Public

    Code associated with the paper 'Seasonal Arctic sea ice forecasting with probabilistic deep learning'

    Python 90 19