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Janis Klaise

I am currently a PhD student in the Complexity Science Doctoral Training Centre. I am working with Dr. Samuel Johnson in the field of Complex Networks.

PhD Work


My PhD project is focused on investigating the emergence of topological properties of natural and artificial systems which can be described in the framework of complex network theory. Simply put, a complex network is an abstraction of a system with interactive agents, represented by a collection of nodes (agents) and links between them (interactions). Examples include friendship networks, neural networks (biological or artificial), food-webs, electrical grids and many more.

Research interests:

  • Models of complex networks
  • Statistical mechanics of complex networks
  • Spreading processes on networks

Publications


  1. J. Klaise and S. Johnson, Relaxation dynamics of maximally clustered networks (2017) [arXiv]
  2. J. Klaise and S. Johnson, The origin of motif families in food webs (2016) [in press]
  3. J. Klaise and S. Johnson, From neurons to epidemics: How trophic coherence affects spreading processes, Chaos 26, 065310 (2016) [arXiv]

Events


Teaching


  • Lab tutor for 'Maths by Computer' (MATLAB) for 1st year students on the BSc/MMath in Mathematics, 2016
  • Seminar tutor for 'Quantitative Analysis for Management 1' for 1st year students on the BSc in Management/International Management course, Warwick Business School, 2015
  • Supervisor of mathematics for 1st year students on the BSc/MMath in Mathematics, 2011, 2012, 2014, 2015.

Background


My undergraduate degree was an MMath in Mathematics at the University of Warwick from 2008-2012. My final year project was in the area of algebraic number theory: Orders in quadratic imaginary fields of small class number, supervised by Prof. John Cremona.

In 2013-2014 I completed an MSc in Complexity Science which involved two 3-month long research projects:

  • Mini-project 1: Modelling the transition to turbulence in pipe flow
    Supervised by Prof. Dwight Barkley.
    Liquid flow in a pipe exhibits a rich behaviour ranging from laminar, to intermittent to fully turbulent flow that depends on the Reynold's number. Here we model pipe flow with a simple discrete model that exhibits a phase transition into an absorbing state and attempt to characterize it by measuring a set of critical exponents.

Poster: (PDF Document) 

  • Mini-project 2: The effect of clustering in epidemic spreading on scale-free networks

Supervised by Dr. Thomas House and Dr. Charo I. Del Genio.
The spreading of infectious disease is often modelled a a stochastic process on a network. Human interaction networks are often highly complex, exhibiting a scale-free degree distribution and high clutering or transitivity. Here we study how an epidemic final size is influenced by the level of clustering in a network.

Janis Klaise

E-mail: J.Klaise[at]warwick.ac.uk

Office: D2.10

View Janis Klaise's LinkedIn profile LinkedIn

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