Signal Processing and Communications Laboratory

Department of Engineering

Marina Riabiz

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Background - Research - Publications - Teaching

Position: PhD Student

E-mail: mr622 [at] cam.ac.uk

Office Location: BN3-02

Thesis Title: 'Bayesian Inference for non-Gaussian LÚvy Processes'

Supervisor: Prof. Simon Godsill

Background

I completed my undergraduate Bachelor and Master degrees in Mathematical Engineering at Politecnico di Milano (Italy), specialising in the Applied Statistics Curriculum. My master thesis involved supervised classification of functional data, regarding geometrical features of fibres.

Research Interests

Bayesian inference for the alpha-stable distribution:

The Matlab code for conditional and marginal MCMC schemes for stable parameters inference can be downloaded here: stable_paremeters_inference.zip

Publications

  • Riabiz, M., Ardeshiri, T., and Godsill, S., 'Convergence results for tractable inference in alpha-stable stochastic processes'. Proceedings of the 22nd International Conference on Digital Signal Processing, 2017 (DSP 2017), London.
  • Riabiz, M. , and Godsill, S., 'Approximate simulation of linear continuous time models driven by asymmetric stable LÚvy processes'. Proceedings of the 42nd Conference on Acoustics, Speech, and Signal Processing, 2017 (ICASSP '17), New Orleans.
  • Riabiz, M., Ardeshiri, T., and Godsill, S., 'A central limit theorem with application to inference in alpha-stable regression models'. Journal of Machine Learning and Research, Workshop and Conference Proceedings, Volume 55, assigned to the NIPS 2016 Time Series Workshop
  • Lemke, T., Riabiz, M., and Godsill, S., 'Fully Bayesian Inference for alpha-Stable Distributions Using a Poisson Series Representation'. Digital Signal Processing, 2015
  • Riabiz, M., Lindsten F., and Godsill, S., 'Pseudo-Marginal MCMC for Parameter Estimation in alpha-Stable Distributions'. In Proceedings of the 17th IFAC Symposium on System Identification (SYSID), Beijing, 2015

Teaching

  • Supervisions for 3F3 (Signal and Pattern Processing), 3F8 (Inference)
  • Lab demonstrations for the I1 Lab (Spectrum Analysis), 1B Lab Computing (C++), 3F4 Lab (Data Transmission), 3F3 (Signal and Pattern Processing), SF1 (Data Analysis 3rd Year Project)
  • Teaching Assistant for 4F13 (Machine Learning)