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Harding Distinguished Postgraduate Scholars Programme


  Ilyes Batatia


  Engineering, Hughes Hall

  PhD thesis: TBC



Research interests:

  1. Geometric deep learning for physics and chemistry
  2. Machine learning force fields
  3. Generative models for atomistic structures
  4. Long-range modelling in deep learning

Chemistry has a fundamental role in the challenges facing my generation and to which I aspire to seek solutions, particularly the storage of energy and the creation of a more sustainable society. I want to contribute to the theoretical study of these challenges using quantum chemistry and machine learning tools. In particular, I wish to develop physically inspired geometric deep-learning methods for chemistry and physics. These methods will enhance our understanding of physics by creating fast and robust algorithms to tackle the most pressing challenges of my generation.

Who or what inspired you to pursue your research interests?

Research has been a vocation since childhood and resonates with my eternal desire for learning. Therefore, the researcher’s job is a natural choice to deepen the areas that fascinate me while contributing to answering critical questions of my generation, in particular, related to climate change.