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Highly comparative time-series analysis

This research involves developing new methods for time-series analysis based on a new analytic framework for understanding structure in time series. more...

Supervisor(s): Fulcher, Ben (Dr)

Inferring the dimensionality of dynamical systems automatically using machine learning

This research will develop methods to infer the dimensionality of a dynamical system automatically, by adapting dimensionality reduction methods to high-dimensional time-series feat more...

Supervisor(s): Fulcher, Ben (Dr)

Multivariate brain activity patterns underlying consciousness

Clinical assessment of consciousness is one of the most significant issues in brain injury and general anaesthesia, yet it remains challenging for medical practitioners. Terrifyingl more...

Supervisor(s): Fulcher, Ben (Dr)

Modelling the mechanisms of brain stimulation

Brain-stimulation techniques that modulate brain activity in a targeted way are growing in their clinical relevance, for example, with transcranial magnetic stimulation (TMS) being more...

Supervisor(s): Fulcher, Ben (Dr)

Analysis of telematics data using machine learning techniques

Usuage-based auto insurance (UBI) represents a significant evolution in automobile insurance pricing over traditional pricing as it can provide more personalised premiums based on i more...

Supervisor(s): Chan, Jennifer (Associate Professor)

Fighting the spread of misinformation

The development of a quantitative measure of the spread of misinformation, for the purposes of developing a strategy to counter science denial. more...

Supervisor(s): Alexander , Tristram (Dr), Fulcher, Ben (Dr), Sharma, Manjula (Professor)

UNVEILING DRIVERS AND FUTURE SCENARIOS OF THE CARBON FOOTPRINT OF GLOBAL TOURISM

This project will employ multi-region input-output analysis (Isard 1951; Leontief 1953), structural decomposition analysis and a comprehensive global database (Lenzen et al. 2012; more...

Supervisor(s): Malik, Arunima (Dr), Lenzen, Manfred (Professor)

Retaining Military Personal Model: Adequacy, Robustness and Simplicity

The project will focus on implementing Partial Least Squares Path Modelling techniques to determine the military turnover drivers and their contribution to turnover.  An econom more...

Supervisor(s): Jajo, Nethal (Dr), Peiris, Shelton (Associate Professor)

Understanding disease progression and comorbidities using multi-omics and clinical information

This research project aims at exploring clinical and multi-omics data to improve our present understanding of disease progression, transition and comorbidities. To achieve this aim, more...

Supervisor(s): Uddin, Shahadat (Dr)

Health burden of chronic diseases

This research project aims to model the health burden of chronic diseases and their comorbid conditions using Markov models, Bayesian statistics and Complex network. more...

Supervisor(s): Uddin, Shahadat (Dr)