Dr Adam M Sykulski

Position Research Fellow
Email(*) a.sykulski
Personal webpage  
Themes Multivariate and High Dimensional Data, Stochastic Modelling and Time Series

* @ucl.ac.uk

Biographical Details

Dr Adam-Sykulski

I am a statistician specialising in time series analysis, stochastic processes and spatiotemporal data. I research practical problems that can not be analysed using the methods from a typical "Time Series 101" class. That means the data could be nonstationary, anisotropic, fractional in memory, and/or multivariate/high-dimensional.

I have an application focus in modelling large-scale global oceanographic data. I also investigate time series obtained from neuroscience and seismology, amongst others.

Please do get in touch if you have overlapping research interests.

I am an EU-funded Marie Curie Research Fellow. I am currently based at NorthWest Research Associates in Seattle, USA - but am collaborating closely with the UCL Department of Statistical Science, where I return in April 2016.

My current research focuses primarily on developing semi-parametric modelling and estimation techniques for large-scale multivariate time series and spatiotemporal data. I have a particular interest in frequency-domain modelling, and estimation of parameters via the Whittle Likelihood (see recent papers below).

I have applied my research to oceanographic data. In particular, I am implementing our methods on data from the Global Drifter Program: a large global database of satellite-tracked freely-drifting instruments known as 'drifters'. Our techniques allow us to make insightful new findings which improves global climate modelling and our ability to respond to environmental threats such as oil spills.

I also have an active research interest (from my PhD) in decision theory problems related to the multi-armed bandit problem, which is the simplest abstraction of the exploration-exploitation tradeoff. I have developed algorithms for how this tradeoff can be tuned on-line in practical problems. I have extended these ideas to multi-player problems, which then brings in ideas from game theory.

Teaching Material

Here are slides available to download for a short course I give on "visualising" spectral analysis methods:

Click here for Keynote (Mac)

Click here for PDF

Research Interests

Time Series Analysis, Spatiotemporal Processes, Nonstationarity and Anisotropy, Applications in Oceanography, Decision Theory, Game Theory, Tennis.

Recent publications and preprints

  • Sykulski, AM, Olhede, SC, Lilly, JM and Danioux, E (2016) Lagrangian Time Series Models for Ocean Surface Drifter Trajectories. Journal of the Royal Statistical Society Series C, 65(1), pp. 29-50.¬†Link to paper Link to ArXiv version
  • Sykulski, AM,¬†Olhede, SC, Lilly, JM and Early, JJ (2015) On Parametric Modelling and Inference for Complex-Valued Time Series. Link to ArXiv version