Reader in Statistics
I am Reader in Statistics at the School of Mathematics, Statistics and Actuarial Science (SMSAS) of the University of Kent and a member of the Statistical Ecology @ Kent (SE@K) group and of the Durrell Institute of Conservation and Ecology (DICE).
My research expertise is in the area of Statistical Ecology, and in particular developing new statistical models and associated software for monitoring migration and phenological patterns of populations, for citizen science and related data, and for monitoring biodiversity using DNA-based survey data. I am also interested in the applications of Bayesian methods, and more specifically of Bayesian nonparametric methods, in ecology.
During 2011-2014 I was working at the University of Oxford as a Departmental Lecturer at the Department of Statistics and as a Stipendiary Lecturer at St Peters College.
My first post-doctoral job, during 2010-2011, was at Victoria University of Wellington, New Zealand where I was employed as a Research and Teaching Fellow.
My PhD, completed in 2010, was a joint project between the Max Planck Institute for Demographic Research, Rostock, Germany and the University of Kent.
I hold an MSc in Statistics with Applications in Medicine from the University of Southampton and a BSc in Statistics from Athens University of Economics and Business.
My PhD project was jointly funded by the University of Kent and the Max Planck Institute for Demographic Research (MPIDR), in Germany. Whilst at MPIDR, I met several demographers, one of whom was Eleonora Mussino, who several years later approached me with a project looking at using capture-recapture models for estimating the number of immigrants in Sweden using incomplete registers. We were awarded funding from the Swedish Research Council in 2021, and started developing new models, first based on Multiple Systems Estimation (MSE), and then using capture-recapture-recovery models, together with Bruno Santos, Lecturer at the University of Kent. In 2022, we run a workshop, funded by Kent's Migration and Movement Signature Research Theme (M&M SRT), bringing together researchers from different fields interented in M&M, while in the same year, we were awarded an SRT studentship to extend the work in a number of directions.
Shortly after joining the University of Kent in 2014, I was awarded a Vice-Chancellor's studentship to celebrate the university's 50th birthday. It was a competitive process, but our project, proposing the development of Bayesian nonparametric models, in collaboration with Professor Jim Griffin, was succesful at gaining funding, and also at attracting a fantastic student, Alex Diana, who started his PhD in 2016. Alex went on to publish a number of excellent papers from his PhD, and then stayed on to do his postdoc with us on our NERC-funded project in 2020, during which he developed eDNAPlus for metabarcoding data and all the corresponding workshop material for our various workshops at Kent and elsewhere. He then went on to work as our KTP associate with NatureMetrics in 2022/23, duing which he worked very closely with Prof Doug Yu and developed a number of models for metabarcoding data and study design approaches for corresponding studies. In 2023, he was offered a lectureship at the University of Essex, which ended his time at the University after 7 very productive years (but not our collaboration of course!).
In 2016/17, shortly before going on maternity leave, I was part of the working group for designing a new programme, called Year in Data Analytics (YiDA). The programme was rather ground-breaking in that it was run jointly with QStep, from SSPSSR, and it was to be offered to eligible students who wanted to learn more statistics and data analytics tools from around the university. The programme started running in 2017 whilst I was on maternity leave, led by Rachel McCrea, and soon grew to be a hugely successful programme that gave students valuable skills for their future. In 2021, YiDA was Winner of CEMS Divisional award of the University Teaching prizes. "The Year in Data Analytics is the result of an enormous amount of effort from the colleagues involved and represents a fantastic and innovative 'year in' programme for all Kent students. The non-traditional design of the programme reflects the challenges of teaching quantitative methods to non-specialists and such innovation is to be highly commended. The programme is a huge asset to the university and its students in a wide range of ways. There is clear impact on the student experience in the programme and on graduate outcomes. The innovation lies in the integration of this programme across subjects/ Divisions with opportunities for students to develop wider disciplinary perspectives and graduate outcomes.