Mame Diarra Toure

I am a PhD student at McGill University. In my research, I work on the application of deep learning and reinforcement learning. I aim to apply those methods to industry problems particularly within the realm of the curse of dimensionality. My work is funded by a Dean fellowship and MILA fellowship. I was also recently awarded the Women In AI Excellence scholarship from MILA.

Prior to joining McGill I worked as a quantitative analyst at Société Général. I did my undergraduate and part of my graduate training in France where I attended Lycée Sainte-Croix Sainte-Euverte and ENSIIE-France's Grandes Ecoles system. I hold an engineering degree in applied mathematics and computer science from ENSIIE and spent the third year of ENSIIE's curriculum at Paris Saclay University where I earned a Master in quantitative finance with first class honors. My outstanding academic performance was recognized with the award of the Sophie Germain Excellence Scholarship for my Master's in Quantitative Finance.

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I'm interested in machine learning, deep learning, reinforcement learning, stochastic control problems, stochastic differential equations and partial differential equations. I am currently working on finding a suitable mathematical model that could be use for deep reinforcement learning in order to solve problems for which the state space is continuous or infinite,

Previous Work and School projects

During my undergraduate and graduate studies degree I had the chance to work on some research projects alone or with my classmates

> Combining Neural Networks Algorithms and Model Diffusion for CVA Pricing
Mame Diarra Toure , Ghada Ben Said, Gabriel Moran, Ouassim Sebbar,Houssem Fendi,Issame Sarroukhe

Using deep neural networks to compute CVA

Option pricing using artificial neural networks
Mame Diarra Toure , Imane Alla

ANN for option pricing

Rough volatility modelling,Kernel Estimation of Volterra processes
Mame Diarra Toure

Estimating the kernel of a rough volatility model

Rough volatility modelling, Lifted heston model
Mame Diarra Toure

Study of lifted heston model