Mohammad Fadil Sumun

PhD Candidate at London School of Economics

Speaker

Mohammad Fadil Sumun is a PhD candidate in the Department of Statistics at the London School of Economics (LSE). His thesis on 'Applications of Physics-Informed Machine Learning in Financial Mathematics' develops neural methods for option pricing, volatility surface modelling and stochastic control: error analysis of physics-informed neural networks for high-dimensional option pricing under jumps, early exercise and path dependence; cross-asset neural operators that construct arbitrage-consistent implied volatility surfaces from sparse quotes; and neural solvers for Hamilton-Jacobi-Bellman equations. He presented his work on exotic option pricing at the International Conference on Scientific Computing and Machine Learning (SCML 2026) in Bath. He holds an MSc in Mathematical and Computational Finance from the University of Oxford, and an MSc in Quantitative Methods for Risk Management and a BSc in Actuarial Science from LSE.