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Adam Smith

I am a second year PhD student at the Mathematics for Real-World Systems Centre for Doctoral Training (MathSys II CDT). My interests are predominantly in applied mathematics which mainly include solving ODE/PDE models for biological systems, but have additional experience in machine learning.

My research is in mathematical neuroscience with a specific interest in cortical spreading depression. Cortical spreading depression (CSD) is a slow propagating wave (mm/min) of neuronal depolarisation followed by electrical silencing. The wave causes loss of ion homeostasis, increased blood flow and can have negative consequences to effected neural tissue if already damaged. The phenomenon presents itself in a number of neurological diseases with varying consequences, but my focus is its role in migraine and the relationship with its seizure activity. The relationship CSD has with seizure activity has been described as complex, with some studies describe it to have an anti-seizure role whereas other believe it facilitates increased excitability and seizure susceptibility.

Understanding the relationship between seizures and CSD will undoubtedly help with identification of new therapeutic targets for both epilepsy and migraine. I aim to conduct a number of mathematical studies to begin understanding this relationship and explain experimental data. The project is supervised by Professor Yulia Timofeeva (Computer Science, University of Warwick) and Professor Kirill Volynski (UCL Queen Square Institute of Neurology) and in collaboration with clinical colleagues at National Hospital for Neurology and Neurosurgery (Professor Dimitri Kullmann).

Research Projects

MSc Individual Project (2020) - Kinetochore Tracking with Machine Learning

  • Developed an automated algorithm for the detection of kinetochore in 3D time-lapse data using machine learning that improved on existing software.
  • Supervised by Dr Jonathan Harrison and Professor Nigel Burroughs with data from the McAinsh lab.

MSc Research Group Project (2020) - Using Generative Adversarial Networks to create multi-channel images of cells undergoing macropinocytosis

  • Evaluated various generative architectures to learn the mapping between a reference protein marker and several secondary proteins within a cell, enabling us to map the spatio-temporal order of actin recruitment within it.
  • Other group members were Nayef Shkeir and Dan Catchpole.
  • Supervised by Dr Till Bretschneider with data from 3i.

Education

2020- : PhD in Mathematics for Real-World Systems, University of Warwick

2019-20: MSc in Mathematics for Real-World Systems, University of Warwick (Distinction)

2015-19: MMath in Applied Mathematics, University of Nottingham (First Class Honours)

Contact

adam.smith.1@warwick.ac.uk

Office D1.13, Zeeman Building

Extra-Curricular

  • Outdoor Bowls, trialled for England Junior team and play for the Warwickshire senior team
  • Darts, Ex-President and Ex-Captain for University of Notts Darts Team, also currently play for University of Warwick.