ECO-AI Hackathon: AI-Driven Solutions for Carbon Capture and Storage

Join forces with your fellow researchers (PhD students & PDRAs) from across the UK to innovate and collaborate exploring AI for NetZero approaches. Over the course of a three days, you’ll be challenged to work on unique problems related to carbon capture and storage (CCS), and its economics and policy implications. You will be provided with the tools, support, and data needed to write new codes and study current challenges in material discovery using AI, subsurface flow modelling using AI, and uncovering progress by abstract clustering of CCS patents using AI.

Participating researchers will receive informative workshops and mentorship from Heriot-Watt University (HWU) and Imperial College London (ICL) experts working within the ECO-AI project.

Event Details

Dates: Wednesday 13 March – Friday 15 March 2024
Location: Heriot-Watt University, Edinburgh, UK
Venue: Scott Suite, Edinburgh Business School

Application details

Applications have now closed. If you have submitted an application, you can expect to receive notification of your application status shortly. Should you have any questions regarding your application in the meantime, please feel free to reach out to ECO-AI project manager at

What to expect

This is a two-part event. You will be invited to attend an AI workshop in CCS and the ECO-AI project on 11 & 12 March. This will lead into the Hackathon (13- 15 March) where you will have the option to compete in one of three tracks:

  • Machine learning for encoding and decoding of molecules with the aim of designing a powerful decoder that produces valid structures.
  • Machine learning for prediction of dissolution in porous media flow.
  • Machine learning for clustering of CCS patents.

Event Flow

  1. Attend 2-day AI workshop on CCS.
  2. Form teams and select challenge track.
  3. Collaborate on solutions over 3-day hackathon.
  4. Demo solutions to experts from industry and academia.

As a participant, you will have access to the required platforms and software to perform the deep learning experiments during the Hackathon.

This Hackathon will allow you to collaborate with your peers from outside your own institution and to network with the workshop participants. At the end of the Hackathon your team will have the chance to demonstrate your work to data scientists within the ECO-AI project and industry experts attending the workshop.

Food and beverages (brain fuel) will be provided during the event.

Who Should Attend

The workshop is ideal for PhD students and early career researchers interested in AI applications in environmental sciences, particularly those focusing on CCS technologies. It’s an excellent opportunity for anyone eager to contribute to the global effort in reducing carbon emissions through innovative AI-driven solutions.

Background & pre-reading

We expect all participants to possess basic knowledge of Python and some ML tools (e.g., Scikit-learn, PyTorch). For those who are not familiar with these tools, please do some pre-reading on how to use basic Python, NumPy, Pandas, Scikit-learn, and PyTorch using the following resources.

  1. Enthought Numpy Tutorial - SciPyConf 2023
  2. University of Washington Machine Learning with Python Course
  3. PyTorch Tutorials

Contact Us

If you have any questions about the application process or the event itself, please contact ECO-AI project manager

Tentative Hackathon Agenda:

Date Time Session
Wednesday 13th 09:00 - 12:00
  • Welcome Speech and Introduction (1 hour)
  • Expert Talks (2 hours)
12:00 - 13:00 Lunch & coffee
13:00 - 17:00
  • Team Formation (1 hour)
  • Project Planning for each team (3-4 teams) with mentor (3 hours)
Thursday 14th 09:00 - 12:00
  • Coding Begins (3 hours)
12:00 - 13:00 Lunch & coffee
13:00 - 17:00
  • Progress Check and Feedback (1 hour)
  • Continued Coding (3 hours)
Friday 15th 09:00 - 12:00
  • Final Stretch (3 hours)
12:00 - 13:00 Lunch & coffee
13:00 - 16:00
  • Project Presentations (2 hours)
  • Closing Ceremony (1 hour)