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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)

ASSESSING THE SUSTAINABILITY OF GLOBAL TOURISM FROM SOCIAL, ENVIRONMENTAL AND ECONOMIC PERSPECTIVES

This project will employ multi-region input-output analysis (Isard 1951; Leontief 1953) and a comprehensive global database (Lenzen et al. 2012a; Lenzen et al. 2013; Lenzen et al. 2 more...

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

Physical models of whole-brain gene coexpression patterns

This research will develop simple physical models to explain patterns of whole-brain gene expression observed across mouse neurodevelopment. more...

Supervisor(s): Fulcher, Ben (Dr)

REBOUND EFFECTS AND ADDITIONALITY IN CARBON FOOTPRINTS OF GLOBAL TOURISM

This project will employ multi-region input-output analysis (Isard 1951; Leontief 1953) and a comprehensive global database (Lenzen et al. 2012; Lenzen et al. 2013; Lenzen et al. 20 more...

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

Formation of road corrugation and ruts

The project aims at identifying the traffic conditions leading to the formation of road washboard and ruts. more...

Supervisor(s): Rognon, Pierre (Dr)

Tree root anchoring: a biomimetic approach to foundation design

The project aims at finding new foundation designs inspired by tree roots. more...

Supervisor(s): Rognon, Pierre (Dr)

Time-series biomarkers of neurological disorders

This research will develop a new machine learning framework for finding and quantifying patterns of brain dynamics that distinguish patients with brain disorders from healthy contro more...

Supervisor(s): Fulcher, Ben (Dr)

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)

Real-time Low-power Neural Accelerator

This project aims at developing an Application-Specific Integrated Circuit (ASIC) for a low-power learning system processing real-time time-series data. more...

Supervisor(s): Kavehei, Omid (Dr)