Who I am
I am a PhD Researcher in AI & Machine Learning at Imperial College London's AI4Health programme, focusing on the development of novel statistical and AI methods for healthcare applications.
My main research interests are in probabilistic deep learning, Bayesian methods, simulation-based inference, neural architecture search, numerical methods, and optimization. In particular, I enjoy leveraging methods from these areas for solving problems in the natural sciences.
What I do
As a member of Systems and Signals Group research group led by Professor Nick Jones, my focus is modelling somatic mitochondrial mutations through the lens of mammalian aging, using a combination of classical statistical techniques with multi-modal deep learning methods.
Of specific interest are the dynamics and effects of mutations unique within a given cell, coined recently by the group as "cryptic" mutations, which are essentially invisible under bulk tissue sampling methods.
With strong evidence of a relationship between the accumulation of cryptic mutations and chronological age, and implicated causal links between mitochondrial dysfunction and ageing in skeletal muscle tissue, further discoveries could be pivotal in age-related disease treatments and interventions.
What I do
As a member of Systems and Signals Group research group led by Professor Nick Jones, my focus is on mathematical modelling of somatic mitochondrial mutations as through the lens of mammalian aging.
Of specific interest are the dynamics and effects of mutations unique within a given cell, coined recently by the group as "cryptic" mutations, which are essentially invisible under bulk tissue sampling methods.
With strong evidence of a relationship between the accumulation of cryptic mutations and chronological age, and implicated causal links between mitochondrial dysfunction and ageing in skeletal muscle tissue, further discoveries could be pivotal in age-related disease treatments and interventions.
Who I am
I am a PhD Researcher in AI & Machine Learning at Imperial College London's AI4Health programme, focusing on the development of novel statistical and AI methods for healthcare applications.
My main research interests are in probabilistic deep learning, Bayesian methods, simulation-based inference, neural architecture search, numerical methods, and optimization. In particular, I enjoy leveraging methods from these areas for solving problems in the natural sciences.
What I do
As a member of Systems and Signals Group research group led by Professor Nick Jones, my focus is on mathematical modelling of somatic mitochondrial mutations as through the lens of mammalian aging.
Of specific interest are the dynamics and effects of mutations unique within a given cell, coined recently by the group as "cryptic" mutations, which are essentially invisible under bulk tissue sampling methods.
With strong evidence of a relationship between the accumulation of cryptic mutations and chronological age, and implicated causal links between mitochondrial dysfunction and ageing in skeletal muscle tissue, further discoveries could be pivotal in age-related disease treatments and interventions.