Dr Elena Issoglio


I studied mathematics in Turin (Italy) from 2003 unitl 2008 (bachelor and master degree).
During my master I specialised in Analysis and Probability Theory and this led m to my PhD in Jena (Germany) on a project on a stochastic partial differential equation that described the random transport of a substance in a porus medium. This area of mathematics - and more generally stochastic analysis - is in between probability and analysis and it finds applications in numerous fields like physics, finance, biology and neuroscience, just to name a few.
After I completed my PhD in 2012 I moved to King's College London where I spent 2 years as a fixed-term lecturer teaching financial mathematics and probability modules.
This experience opened the door to my involvement in financial mathematics, which I teach in Leeds since when I joined as a lecturer in 2014.

My research after 5 years of completing my PhD still includes stochastc partial differential equations and applications to physics. Nevertheless I meanwhile widened my horizons to other areas of stochastic analysis, like backward stochastic differential equations (which find applications in finance), numerical analysis for singular (random) partial differential equations, and more theoretical questions regarding existence of solutions to singular stochastic differential equations. I am also interested in applications to neuroscience (e.g. modelling the activity of the brain as a stochastic equation on a network) and in big data applied to weather forecasting.

On a wider societal level, during the years I spent in the UK I became interested in gender issues related to STEM disciplines. Since then I have been promoting the role of women in Science and in particularly Mathematics, see for example the Women in Maths event that I organised in September 2017 in Leeds.

Research interests

1) Systems of forward-backward SDEs with irregular coefficients
2) n-dimensional SDEs with singular drift: in particular distributional drifts
3) SPDES driven by fractional Brownian motion: pathwise techinques to solve transport equations driven by fractional noises
4) Numerics for Stochastic PDEs: I recently started to look at numerical schemes to approximate stochastic PDEs, in particular PDEs with distributional coefficients
5) SPDEs on metric measure spaces: Main techniques used are fractional Sobolev spaces generalized to measure spaces and fractional integrals and derivatives
6) SDEs in Banach spaces: cylindrical fractional Brownian motion in infinite dimensional spaces, and related stochastic calculus in Banach spaces.


  • Fellow of the Higher Education Academy

Student education

I pass my knowledge to the next generation of mathematician by delivering lectures and tutorials in various module linked to Financial Mathematics for our BSc and MSc programmes. I also supervise BSc and MSc students in their final year dissertation.

Research groups and institutes

  • Statistics

Postgraduate research opportunities

We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our research opportunities allow you to search for projects and scholarships.