Dr Georgios Aivaliotis
- Position: Lecturer
- Areas of expertise: financial and actuarial mathematics; stochastic control; risk and dependence modelling; data analytics; temporal pattern mining.
- Email: G.Aivaliotis@leeds.ac.uk
- Phone: +44(0)113 343 5162
- Location: 9.311 Physics Research Deck
My research interests evolve around probability, statistics, stochastic processes and machine learning. Applications of my research can be found in the broad area of financial and actuarial mathematics, data analytics, survival analysis as well as financial technologies.
I have worked in the area of stochastic control for mean-variance type problems and applications in portfolio selection and agent remuneration. Currently, I am applying ideas from probability and statistics into the field of Data Analytics, in particular I am working on robust temporal pattern mining from data that are time stamped. This is part of the EPSRC funded project QuantiCode in which I am a Co-Investigator.
I am an Alan Turing Fellow and co-Investigator on the Alan Turing Project "Modelling the joint effects of temporal, heterogeneous datasets".
Throughout my career, I have kept close links with several industrial partners and government organisations that I have had projects with (CallCredit, Leeds City Council, Jet2, Sainsburys and others). I am an associate member of the Leeds Institute for Data Analytics (LIDA).
- PhD in Statistics, University of Leeds
- MSc in Financial Mathematics, Herriot-Watt University and The University of Edinburgh
- BSc in Statistics, Athens University of Economics and Business
I led the development of the BSc Actuarial Mathematics (and the exemption recognition process) for a number of years and assisted in running the MSc Financial Mathematics. I am currently contributing to the development of the new MSc in Financial Technologies.
I have taught a variety of Financial and Actuarial modules both in UG and PG level.
Research groups and institutes
- Probability and Financial Mathematics
- Temporal models for heterogeneous datasets
- Dynamic Dependence modelling
- Survival Analysis using temporal patterns