I joined the Mathematical NeuroOncology Lab at Mayo Clinic in Phoenix in November 2018 as a Bioinformatician.
I am an advocate for mathematical models that can be applied to gain clinical insight, with the long-term goal of guiding clinical trials, and in turn improving patient care. I have worked on a partial differential equation model – the Proliferation Invasion Hypoxia Necrosis Angiogenesis (PIHNA) model, to suggest mechanistic explanations to clinically observed phenomena.
My data-driven work is focused on finding meaningful signals in retrospective data, and using mathematical techniques to find meaningful genetic/transcriptomic signals. I have published work on survival implications of cystic glioblastoma, as well as the shape of pretreatment MRI abnormalities. As of July 2020, I have taken a role in the intra-operative collection of image-localized biopsies, which we are using alongside data analysis/machine learning to gain insight into brain tumor heterogeneity.
I graduated with a Masters of Mathematics from the University of York, UK in 2014, and completed my Ph.D. in Mathematical Medicine and Biology at the University of Nottingham, UK in 2019. My PhD thesis, Mathematical Modelling of Brain Tumour Growth and Therapy, was focused on using partial differential equation models to simulate tumor growth dynamics and drug diffusion through proposed polymers for local chemotherapy delivery.
I am also involved in education and outreach. I have arranged multiple external speakers to come to the lab, advertised to the wider research community at Mayo Clinic. I am an active member of our Education Committee, ensuring success for our summer interns and rotating graduate students. I also enjoy mentoring, having directly mentored 6 lab members to date.