CV

Education

• PhD, Engineering (Computational Neuroscience & Machine Learning), University of Cambridge, 2024-
  • Thesis: “Contextual inference for continual reinforcement learning”
  • Advisors: Prof. Máté Lengyel, Prof. Guillaume Hennequin
• MSc, Scientific and Data Intensive Computing, UCL, 2023-2024
  • Thesis: “Machine learning methods for causal discovery in observational time series data”
  • Advisors: Dr Nikos Nikolaou, Prof. Ricardo Silva
• MSci, Biological Sciences (Computational Biology), UCL, 2018-2022
  • Thesis: “Species delimitation from genomic data under the multispecies coalescent model with migration”
  • Advisors: Prof. Ziheng Yang, Dr Tomas Flouris

Research experience

• Academic Visitor, Systems & Signals Group, Department of Mathematics, Imperial College London, 01/2023-10/2023
  • Researching ODE and SDE models of clonally expanding mtDNA mutations in neurodegenerative disease. Investigating analytical solutions, and implementing numerical simulations in C++
• Research Associate, Ziheng Yang Lab, UCL Centre for Life’s Origins and Evolution, 06/2022-06/2023
  • Conceptualizing an innovative method for heuristic species delimitation under the multispecies coalescent model with gene flow, and implementing it as a Python package
• Research Intern, Secrier Lab, UCL Genetics Institute, 06/2021-12/2021
  • Identification a reduced genetic signature of tumour quiescence from single cell RNA-seq data using machine learning. Developing an R package for the identification and diagnosis of tumour quiescence from patient samples.