Abdul-Lateef Haji-Ali

Abdul-Lateef Haji-Ali serves as Associate Professor in the Actuarial Mathematics & Statistics department at Heriot-Watt University's School of Mathematical and Computer Sciences, Edinburgh. His research focuses on computational methods for stochastic systems with applications in finance and engineering, maintaining active supervision of PhD students.

His primary expertise spans Monte Carlo methodologies, particularly multilevel techniques and importance sampling for rare events in stochastic differential equations. Current work integrates machine learning with traditional Monte Carlo approaches, emphasizing McKean-Vlasov systems and partial differential equations under uncertainty.

Recent publications (2024-2025) reveal concentrated advancement in rare-event simulation for complex stochastic models, with growing interdisciplinary connections to generative AI through diffusion models. Key innovations include antithetic schemes for non-commutative noise systems and double-loop importance sampling frameworks.

His scientific recognition includes:

• Leslie Fox Prize (2nd place, June 2019)

Dr. Haji-Ali actively recruits PhD candidates for projects on Adaptive Monte Carlo Methods for Stochastic Differential Equations. His collaborative network spans international institutions, with recent co-authorship including Tempone, Pereyra, and Zygalakis, indicating robust research funding through sustained high-impact publication output.