Parallel sessions (workshop) - Data-driven discovery (e.g. materials, drugs)

Data-driven discovery leverages the power of big data and computational methods to make processes more efficient, cost-effective and targeted. Industries that have traditionally relied on complex and labour-intensive techniques can deploy machine learning methods to rapidly analyse and interpret complex data to identify and predict properties without extensive physical experimentation. This session explores how to leverage these capabilities in areas such as drug development and material innovation, pushing the boundaries of what can be discovered and achieved in these fields.

The workshop consists of a few short thought-provocations from our experts, followed by facilitated breakout discussions with participants.

Moderator: Charlotta Cederqvist

Contributors & title of talk(More details to be announced):

• Prof. Adrian Jackson

• Dr. Eleonora Ricci - Accelerated discovery of materials in support of the green energy transition

• Prof. Julien Michel - Computer-Aided Drug Discovery by Blending of Physics and Data Driven Approaches

With the workshop, we aim to:

• showcase University of Edinburgh's expertise in data, digital and AI

• surface cross-sector challenges and approaches to leverage new technologies for data-driven discovery

• co-create opportunities for collaboration around new solutions or questions

We invite attendees to share their experiences, insights, and ideas to the workshops, bringing something to add or to ask to contribute to the breakout discussions.