Tractable frameworks for complex network modelling
Lead Research Organisation:
University of Bristol
Department Name: Mathematics
Abstract
Many modern applications generate large-scale data with a network structure which often includes a temporal component, different modes of connection, and information at edge, node and subgraph levels. Finding tractable statistical frameworks for exploiting such data could have important societal benefits, for example, in cyber-security applications (e.g. intrusion detection, 'fake news'), medicine (e.g. biological networks, genetics), 'artificial intelligence' applications (e.g. recommender systems, sentiment analysis, natural language processing) and more. This PhD will seek to develop such solutions, initially focussing on the approach of embedding, whereby a complex discrete data structure is first transformed into a point cloud, allowing subsequent analysis by more standard statistical and machine-learning techniques such as clustering.
Organisations
People |
ORCID iD |
Patrick Rubin-Delanchy (Primary Supervisor) | |
Ian Gallagher (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/N509619/1 | 01/10/2016 | 30/09/2021 | |||
2120306 | Studentship | EP/N509619/1 | 01/10/2018 | 31/03/2022 | Ian Gallagher |
EP/R513179/1 | 01/10/2018 | 30/09/2023 | |||
2120306 | Studentship | EP/R513179/1 | 01/10/2018 | 31/03/2022 | Ian Gallagher |