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School of Mathematical Sciences

Mr Filip Bonja


Postgraduate Research Student

Room Number: Mathematical Sciences Building, Room: MB-402


Filip is a second year PhD student under the supervision of Dr. Adrian Baule. He is a member of the Dynamical Systems and Statistical Physics group at Queen Mary. His current research is on analysing Langevin equations driven by non-Markovian and non-Gaussian noise.

Before joining Queen Mary, Filip obtained his Bachelor of Science degree from McGill University, where he graduated with a double major in Biology and Mathematics. His concentrations were respectively human cancer genetics and dynamical systems.

Filip later pursued his Master's degree in Applied Mathematics at Royal Holloway, University of London. His research area was on stochastic analysis and financial mathematics. He was awarded the Master of Science Dissertation for outstanding performance on his dissertation, entitled "Lévy Processes with Applications to Option Pricing Models: Theory, Simulation and Calibration".

Besides pursuing his PhD, Filip is also actively involved in the private sector. He provides business consultancy services to law firms in London and actively publishes articles on LinkedIn considering recent trends in the consultancy and legal services industry.



Spring 2019

  • MTH5120 - Statistical Modelling I (Marker)
  • MTH5125 - Actuarial Mathematics II (Demonstrator)
  • MTH5127 - Actuarial Professional Development II (Demonstrator)
  • MTH6155 - Financial Mathematics II (Marker)


Fall 2018

  • MTH4107 - Introduction to Probability (Marker)
  • MTH5124 - Actuarial Mathematics I (Marker) 


Spring 2018

  • MTH6155 - Financial Mathematics II (Teaching Associate)
  • MTH6156 - Financial Mathematics III (Demonstrator, replacement TA)


Fall 2017

  • MTH5121 - Probability Models (Demonstrator)


Research Interests:

  • Langevin equations
  • Lévy processes
  • Non-Markovian processes
  • Measure theoretic probability
  • Higher-order Fokker-Planck Equations
  • Path integral representations
  • Functional analysis
  • Lie symmetry analysis of nonlinear PDEs


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