THE GOOD, THE BAD, AND THE UGLY: AT THE OTHER END OF THE DATA SCALE - - PowerPoint PPT Presentation

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THE GOOD, THE BAD, AND THE UGLY: AT THE OTHER END OF THE DATA SCALE - - PowerPoint PPT Presentation

THE GOOD, THE BAD, AND THE UGLY: AT THE OTHER END OF THE DATA SCALE Natalia Petrovskaya School of Mathematics,University of Birmingham, UK Natalia Petrovskaya Dagstuhl seminar 17901 27.02 03.03 2017 Personal background Applied


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‘THE GOOD, THE BAD, AND THE UGLY’: AT THE OTHER END OF THE DATA SCALE

Natalia Petrovskaya

School of Mathematics,University of Birmingham, UK

Natalia Petrovskaya Dagstuhl seminar 17901 27.02 – 03.03 2017

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Personal background

  • Applied mathematician: MSci – National Research Nuclear

University (MEPhI), Russia, PhD - Keldysh Institute for Applied Mathematics (KIAM), Russia.

  • researcher in KIAM – computational aerodynamics

(contractor for Boeing) and computational plasma physics (contractor for National Research Center ‘Kurchatov Institute’).

  • from 2004: lecturer, senior lecturer at University of

Birmingham, UK – mathematical ecology.

Natalia Petrovskaya Dagstuhl seminar 17901 27.02 – 03.03 2017

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Research Areas/Interests

  • Efficient computational methods for pest monitoring and

control:

– the problem of uncertainty and accuracy control for strongly heterogeneous spatial ecological data – evaluation of the population density functionals (the total population size, synchronization between habitats) from sparse ecological data – evaluation of the total population size from noisy ecological data

Natalia Petrovskaya Dagstuhl seminar 17901 27.02 – 03.03 2017

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Research Areas/Interests

  • Mathematical models for biological invasion

– various regimes of biological invasion: short-distance dispersal vs. long-distance dispersal – patchy invasion scenario: pattern formation

  • Spatio-temporal dynamics of slug population (applied

project with ecologists at Harper Adams University, UK)

– predictive modelling (individual based modelling, partial differential equations) – processing field data

Natalia Petrovskaya Dagstuhl seminar 17901 27.02 – 03.03 2017

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Links to ‘Computer Science meets Ecology’

  • What happens at the other end of the data scale (big data
  • vs. sparse data)

– Does ‘big data’ always mean ‘reliable data’? – How to measure the quality of information (sparse = noisy)? – Transition from sparse to big datasets - threshold quantities?

Natalia Petrovskaya Dagstuhl seminar 17901 27.02 – 03.03 2017

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Links to ‘Computer Science meets Ecology’

  • Pattern recognition problem (spatial clusters,

heterogeneous spatial density distributions...)

– Resolution of spatial pattern features? – Automated recognition of spatial clusters, evaluation of the cluster size? – Automated recognition of invasive fronts/patches?

Natalia Petrovskaya Dagstuhl seminar 17901 27.02 – 03.03 2017