Epistemic Overview
Cross-disciplinary AI for scientific discovery initiatives and labs.
Founded
2022
Director / President
Atılım Güneş Baydin (Lead, Oxford AI for Science Lab)
Category
Research Group
Research Domains
Timeline
c. 2019
The 'AI for Science' (AI4Science) initiative begins to form as a cross-disciplinary theme at Oxford, particularly in MPLS.
2021
The 'Oxford AI for Science Lab' (part of this initiative), led by Atılım Güneş Baydin, is established.
2022
AI4Science researchers publish key work on 'differentiable simulators' and 'physics-informed neural networks' (PINNs).
2023
The initiative hosts the 'AI for Science' summer school and various workshops.
2024
The groups expand research in applying AI to climate modeling, drug discovery, and materials science.
Influential Papers / Notable Research
Cross-disciplinary research applying AI to foundational sciences (physics, biology, climate).
Development of 'differentiable simulators' and 'physics-informed neural networks' (PINNs).
Using AI for accelerated discovery in areas like drug development, materials science, and climate modeling.