Dr Patricio Maturana Russel

Lecturer

Phone: 09 921 9999 ext 8985

Email: p.maturana.russel@aut.ac.nz

Physical Address:

School of Engineering, Computer and Mathematical Sciences
AUT Tower, Level 1
2-14 Wakefield St
Auckland 1010

Links to relevant web pages:

https://www.gravity.ac.nz/

Qualifications:

  • PhD in Statistics. The University of Auckland, New Zealand, 2017.
  • MSc in Statistics. Universidad de Valparaíso, Chile, 2011.
  • BSc in Statistics. Universidad de Valparaíso, Chile, 2007.

Memberships and Affiliations:

New Zealand Astrostatistics and General Relativity

Biography:

Patricio has a BSc degree (2007) and a MSc in Statistic (2011) from the Universidad de Valparaíso, Chile. In that time, he worked in estimation and local influence in factor analysis under heavy-tailed distributions, supervised by Dr Felipe Osorio. He did his PhD in Statistics at the University of Auckland (2017), supervised by Dr Steffen Klaere and Dr Brendon Brewer.  The title of his thesis is "Bayesian inference in phylogenetics using Nested Sampling".  Then, he did a post doc for 2 years at the same department, working with Profesor Renate Meyer. His work consisted in the development of Bayesian Statistical techniques with application in Gravitational Wave data. Patricio joined AUT in 2020.

Teaching Areas:

  • STAT700 Applied Stochastic Models
  • STAT802 Advanced Topics in Analytics

Research Areas:

  • Bayesian Inference
  • Data analysis
  • MCMC methods
  • Nested Sampling
  • Marginal likelihood or Evidence calculation
  • Bayesian spectral density estimation
  • Phylogenetic inference
  • Graviational wave data analysis

Research Summary:

Patricio works in the development and implementation of Bayesian statistical methods applied mainly to phylogenetics and gravitational wave data analysis.  He is also interested in developing and implementing locally stationary methods for power spectral density estimation for time series that shows slowly-varying dependencies over time.

Publications:

Maturana-Russel, P., Meyer, R., Veitch, J. and Christensen, N. (2019).  Stepping-stone sampling algorithm for calculating the evidence of gravitational wave models. Physical Review D. DOI: 10.1103/PhysRevD.99.084006 Paper

Maturana Russel, P., Brewer, B. J., Klaere, S. and Bouckaert, R. R. (2019).  Model selection and parameter inference in phylogenetics using nested sampling. Systematic Biology. DOI: 10.1093/sysbio/syy050 Paper

Meyer, R. and Maturana Russel, P. (2018).  Bayesian Analysis of Gravitational Wave Data. Wiley StatsRef: Statistics Reference Online. DOI: 10.1002/9781118445112.stat08009 Paper

Maturana Russel, P. (2018).  Bayesian support for Evolution: detecting phylogenetic signal in a subset of the primate family. In: Polpo A., Stern J., Louzada F., Izbicki R., Takada H. (eds) Bayesian Inference and Maximum Entropy Methods in Science and Engineering. Maxent 2017. Springer Proceedings in Mathematics & Statistics, vol 239. Springer, Cham. DOI: 10.1007/978-3-319-91143-4 20 Paper

Maturana Russel, P. (2017).  Bayesian Inference in Phylogenetics using Nested Sampling. The University of Auckland. ResearchSpace@Auckland. Thesis