The 2025 cohort brings together outstanding early-career researchers from departments across the MPLS Division, who will use AI to advance fields ranging from cosmology to conservation, and from solar cell design to storm surge prediction.
The new Fellows and their projects are:
- Alycia Leonard, Department of Engineering Science – Predicting empowerment: AI-driven targeting of best-fit energy services for efficient sustainable development
- Taniya Kapoor, Department of Engineering Science – Engineering-informed foundation models for sustainable bridges
- Thomas Monahan, Department of Engineering Science – Global operational storm surge prediction using scientific machine learning and satelite altimetry
- Jiahe Cui , Department of Engineering Science - AI-enabled understanding of oculomotor control through high resolution imaging of the living human retina.
- Daniel Schofield, Department of Engineering Science – Scaling AI for ethology and wildlife conservation: towards automated monitoring of primates in the wild
- Augustin Marignier, Department of Earth Sciences – Illuminating the Earth’s inner core with Bayesian machine learning
- Deaglan Bartlett, Department of Physics – Trustworthy machine learning for cosmological discovery
- Hattie Stewart, Department of Physics – Galaxy modelling in next generation radio surveys with machine learning
- Jonathan Pattrick, Department of Biology – Characterising pollinator energetics and foraging stratergies using machine learning
- Yuxing Zhou, Department of Chemistry – Understanding amorphous oxides for solar cell applications using gererative machine learning.
Through a combination of research, training, and collaboration, the Schmidt AI in Science Fellows are developing cutting-edge AI tools and applying them to pressing scientific challenges.