About

Work Experience

• Schmidt AI in Science Fellow, University of Oxford

  Jun, 2024 - Present

  Developing data-driven and explainable AI methods to model bird flight as a dynamic morphing system. Focused on shape analysis, rough path signatures, and interpretable decompositions of motion.

  • Applying decomposition methods to bird wing motion

  • Collaborating across mathematics, zoology, and computer science

  • Developing open-source analysis tools for natural motion

• Research Data Scientist, The Alan Turing Institute

  Jul, 2021 - Present

  Collaborative scientific software engineering and AI research across academic and public sector projects. Worked in domains from digital humanities, trusted digital signatures, and urban analytics. Most recently, research with GNNs for AI weather forecasting in partnership with the UK Met Office.

  • Developing GNN-based models for spatiotemporal forecasting

  • Scalable workflows using HPC and Azure

  • Co-led training and reproducibility initiatives for research software

• Biological Sciences Lecturer, University of Oxford - Magdalen College

  Oct, 2020 - Present

  Tutorial and course-based teaching across zoology, behaviour, statistics, and programming for undergraduates. Ongoing contributor to interdisciplinary methods teaching across DTC programmes.

  • Course creation in Python, R, MATLAB, version control, and data science

  • Student support and supervision in quantitative biosciences

• Postdoctoral Research Assistant, University of Oxford - Department of Zoology

  Aug, 2019 - Jul, 20211 year 11 months

  Studied flight control, obstacle avoidance, and vision-guided behaviour in birds. Recorded over 4 million data points using a custom motion capture system.

  • ERC-funded research into visually guided flight

  • Fieldwork and experimental design with Harris hawks and zebra finches

Projects Experience

• Morphing Shape Space of Hawk Flight

  Feb, 2021 - Present

  Principal component analysis of 3D wing and tail kinematics in Harris' hawk, enabling generalisable shape modes across morphologies.

• Comparative Study of Morphing Flight

  Apr, 2025 - Present

  Cross-species comparison of morphing strategies in birds using projected shape modes, with data from kestrels, pigeons, and hawks.

• Morphing Flight in Gust Manoeuvres

  Jun, 2025 - Present

  Analysis of pigeon and kestrel responses to wind gusts using shape-based methods to quantify adaptive morphing during unsteady flight.

• Dynamic Decomposition of Wings During Flapping

  May, 2024 - Present

  Application of Dynamic Mode Decomposition (DMD) to isolate temporal patterns in wing and tail movement during flight.

• Shape Analysis of Flight Trajectories

  Feb, 2022 - Present

  Elastic shape analysis of 3D flight paths grouped by individual and context (e.g., perch distance) using SRVF and Karcher means.

• Data Signatures in Animal Motion

  Jul, 2025 - Present

  Exploring the use of rough paths and time-series signatures to characterise differences in flapping and locomotion control.

• High-Dimensional Spider Biomechanics Decomposition

  Jul, 2024 - Present

  Morphing and dynamics analyses of leg and body markers in spiders during walking.

• Geometric Machine Learning of Wing Shapes in Flight

  Jul, 2025 - Present

  Developing ML techniques for representing and comparing wing shapes from motion capture data.

• FastNet: AI for Weather Forecasting

  Feb, 2024 - Present

  GNN-based predictive models using HPC and cloud infrastructure, in collaboration with the Met Office.

• Open Research Software Teaching

  Oct, 2020 - Present

  Course design and delivery across institutions on reproducible programming, research data science, and scientific computing.

Skills

Education

Publications

Interests