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 social policy interventions
- Taniya Kapoor, Department of Engineering Science – Engineering-informed foundation models for sustainable materials discovery
- Thomas Monahan, Department of Engineering Science – Global operational storm surge prediction using neural differential equations
- Daniel Schofield, Department of Engineering Science – Scaling AI for ethology and wildlife conservation
- Augustin Marignier, Department of Earth Sciences – Illuminating the Earth’s inner core with Bayesian AI
- Deaglan Bartlett, Department of Physics – Trustworthy machine learning for cosmological discovery
- Hattie Stewart, Department of Physics – Galaxy modelling in next generation radio surveys with AI
- Jonathan Pattrick, Department of Biology – Characterising pollinator energetics and foraging dynamics using computer vision and AI
- Yuxing Zhou, Department of Chemistry – Understanding amorphous oxides for solar cell design using AI-driven modelling
- Siyi Yang, Department of Materials – Automated crystal growth parameter exploration using autonomous agents
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.