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BSc Mathematics (Bucharest)
MSc Stochastic Processes and Theoretical Statistics (Bucharest)
PhD Statistics (Bristol)
Postdoctoral research positions sponsored by GCHQ (Bristol, 2006-2008) and on the EPSRC funded project Locally Stationary Energy Time series (Bristol, 2011-2013). [Academic career break to fit with my very young family. I worked part-time as a medical statistician for NHS Blood and Transplant, Bristol, 2008-2011.]
In September 2013 I joined the Department of Mathematics at the University of York as a Lecturer in Statistics.
Head of Statistics Section
Member of the University Impact Leads for Science Departments Group
My central research theme focuses on developing multiscale methodology to solve various real-life problems and broadly pertains to (replicate) nonstationary time series analysis in the time- and spectral- domains, forecasting and long-memory estimation; regression, dimension reduction and associated tasks such as clustering; data adaptive techniques constructed for irregular and complex sampling structures, such as networks. My research found applications in a range of fields from neuroscience and biology to environmental science.
Work on locally stationary time series introduced new methodology for modelling replicate nonstationary time series, including clustering and spectral domain testing for eg, local field potentials and circadian rhythms. Work on modelling network time series and in the real- or complex-valued second generation wavelet area led to improved estimator precision in a variety of challenging settings and tasks, and the interested reader can use the associated R packages ‘GNAR’, ‘liftLRD’, ‘CLiftLRD’, ‘CNLTreg’, ‘adlift’ and ‘nlt’, all on CRAN.
Recent co-authors: Prof Seth Davis (Biology, York), Prof Jon Pitchford (Mathematics and Biology, York), Dr Jess Hargreaves (Mathematics, York); Dr Matt Nunes (Bath); Dr Rebecca Killick, Prof Idris Eckley (Lancaster); Prof Guy Nason (Imperial College); Prof Hernando Ombao (KAUST).
PhD applications are invited for competitive funding on projects that span the fields of multiscale methods, nonstationary time series analysis and forecasting, in particular for data collected on irregular and spatial structures such as networks. Particular application fields of interest include energy, biology and neuroscience.