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Personal profile

Research interests

Enrico is a PhD student in mathematical biology with a background in stochastic modeling and complex networks. His main research is into the development of mathematical models for cell migration and collective behaviour.
 
He earned a BSc in mathematics at the University of Padua in Italy, where he studied probability theory and voter models. He then obtained a MSc degree in mathematics working on branching processes and complex networks as an Erasmus student based between Padua and Bristol. He moved to study  mathematical biology at the University of Bath where he joined the Yates Group.
 
His main field of research deals with colonisation of  the embryos by melanoblasts using agent-based stochastic models. In particular, he is interested in incorporating biological realism into individual-based stochastic models and the derivation of representative deterministic models.
 
In addition, he has always cultivated a passionate interest for decision making and collective movements in large groups of individuals, specifically in social or swarming insects as ants and locusts, which also forms part of the work he undertakes during his PhD.

Education/Academic qualification

Mathematics, Master in Science, Università di Padova

3 Oct 201423 Sep 2016

Mathematics, Bachelor of Science, Università di Padova

2 Oct 201126 Sep 2014

Keywords

  • QC Physics
  • Collective Behaviour
  • Cell biology
  • Cell migration
  • QA76 Computer software
  • Agent-based models
  • Multi-scale analysis

Fingerprint Dive into the research topics where Enrico Gavagnin is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 6 Similar Profiles
Cell Migration Mathematics
Agent-based Model Mathematics
Stochastic Model Mathematics
Mathematical Biology Mathematics
Pair Correlation Function Mathematics
Jump Process Mathematics
Invasion Mathematics
Cell Cycle Mathematics

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Research Output 2018 2018

2 Citations (Scopus)
Open Access
File
Jump Process
Persistence
Agent-based Model
Motion
Modeling
1 Citation (Scopus)

Pair correlation functions for identifying spatial correlation in discrete domains

Gavagnin, E., Owen, J. & Yates, C., 4 Jun 2018, In : Physical Review E. 97, 6, 062104.

Research output: Contribution to journalArticle

Open Access
File
Pair Correlation Function
Spatial Correlation
Intuitive
Regular tessellation
Metric
1 Citation (Scopus)

Stochastic and Deterministic Modelling of Cell Migration

Gavagnin, E. & Yates, C., 19 Jul 2018, Integrated Population Biology and Modeling. Rao, A. S. R. & Srinivasa, R. C. R. (eds.). Elsevier, p. 37-91 55 p. (Handbook of Statistics ; vol. 39).

Research output: Chapter in Book/Report/Conference proceedingChapter

Cell Migration
Cell
Modeling
Agent-based Model
Continuum
Cell Migration
Invasion
Cell Cycle
cell movement
Cell Movement