CV

Education

MPhys Computational Physics, 1st class, University of Edinburgh 2016-2021
Ph.D applied mathematics, University of Edinburgh, 2021 - ongoing

Technical Skills

Programming Experience:
- Machine learning and differentiable programming
- Numerical methods and simulation techniques (Agent based models, monte-carlo methods)
- Graph optimisation
- Image processing
- GPU and MPI parallelisation
Software and Tools:
- Python (JAX, PyTorch, numpy, scipy, matplotlib, tensorflow, pandas)
- Bash
- Kubernetes
- ImageJ
- C, C++, MATLAB, Cuda
Mathematics:
- Partial differential equations and dynamical systems
- Statistical mechanics and probability theory
- Mathematical modelling

Academic Experience

Research:
- Modelling spatio-temporal pattern formation with Neural Cellular Automata (see Projects page).
- Predicting hospital ICU stay times with patient demographics and disease co-occurrences via graph clustering algorithms.
- Validating the performance of wind turbines after modifications, given noisy/unreliable direct measurement.
- Ongoing work exploring how to fit reaction-diffusion-advection equations to biological data.
Other experience:
- I run a weekly reading group for scientific applications of machine learning, which involves organising/giving talks, and discussing papers as a group.
- Attended a wide range of conferences (see Conferences page), sometimes presenting my work, which has led to ongoing collaborations.
- Experience presenting technical work in a clear and understandable manner.
- Experience working in a team and independently, balancing the time commitments of several concurrent projects.
- Cosupervised 2 Masters dissertations on the evolution of intelligence in biologically inspired systems.

Work experience

Summer 2019 - Research assistant
- Assisted a PhD student with research in frustrated anti-ferromagnets
- Developed C++ code to simulate the classical heisenberg model
2017 - 2020 - Maths and Physics tutor
- Part time tutoring of high school level maths and physics
2021 - ongoing - Teaching assistant
- Teaching assistant for undergraduate scientific programming courses, giving me experience in debugging other people’s code and explaining technical concepts to those who don’t understand them.

Publications

Learning spatio-temporal patterns with Neural Cellular Automata

Alex D. Richardson, Richard A Blythe, Tibor Antal, Linus J. Schumacher. "Learning spatio-temporal patterns with Neural Cellular Automata." PLOS Computational Biology.