Principled uncertainty quantification for electrical generation data [TAKEN]

ELIGIBILITY: This project is for a student taking the MSc in Statistics and Sustainability or the MSC in Statistics and Data Science. This project will investigate methods to predict electricity generation in Ireland. Importantly, we will make predictions with uncertainty intervals that accurately quantify variability in electricity production. We will compare prediction intervals generated by … Read more

Compositional Data Analysis for Energy Mix Projections [TAKEN]

ELIGIBILITY: This project is for a student taking the MSc in Statistics and Sustainability or the MSC in Statistics and Data Science. Compositional data comprise observations that sum to a fixed value and require special attention for statistical modelling and analysis. Energy mix, the proportion of energy use by fuel type, is an example of … Read more

Bayesian Forecasting of Electric Vehicle Adoption [TAKEN]

ELIGIBILITY: This project is for a student taking the MSc in Statistics and Sustainability or the MSC in Statistics and Data Science. This project will focus on comparing Bayesian time-series forecasting methods, motivated by the problem of projecting electric vehicle adoption. Depending on interest, this may involve using probabilistic programming through the Stan programming language. … Read more

Extreme Value Theory and the Climate [TAKEN]

ELIGIBILITY: This project is for a student taking the MSc in Statistics and Sustainability or the MSC in Statistics and Data Science. Met Éireann monitors weather at 25 stations, with daily historical data available for multiple climate measures including precipitation, temperature, and wind speed. This project will analyze these data using methods from Extreme Value … Read more

Deep learning clustering methods applied to outbreak classification

ELIGIBILITY: This project is for a student enrolled in MSc in Statistics and Data Science. Interested students should contact Gabriel Palma at GPALMA@tcd.ie Deep Learning (DL)-based clustering methods, such as Variational Deep Embeddings (VaDE) [1], combine model‑based clustering (Gaussian Mixture Models, GMMs) with variational autoencoders and have shown promising results on clustering benchmarks. Building on … Read more

Bayesian Hierarchical Models applied to insect outbreak forecasting

ELIGIBILITY: This project is for a student enrolled in MSc in Statistics and Data Science. Interested students should contact Gabriel Palma at GPALMA@tcd.ie Insect outbreaks have frequently been documented in insect pest populations in various agroecosystems presenting serious economic damage. To address this problem, Integrated Pest Management (IPM) present various techniques to reduce the insect … Read more

Design and Analysis of Clinical Trials

Eligibility: Students taking the online MSc in Statistics and Data Science. Interested students should email  Caitríona Ryan  at ryanc86@tcd.ie. Supervisor: Caitríona Ryan, Associate Professor in Statistics and Trial Design in the School of Medicine at Trinity College Dublin and  the Wellcome-HRB Clinical Research Facility in St. James’s hospital. https://www.tcd.ie/medicine/public-health-and-primary-care/staff/caitriona-ryan/   I would be happy to … Read more

Energy–performance trade-offs in compressed overparameterised neural networks

Eligibility: this project is only available to students on the online MSc Statistics and Data Science programme. If interested please contact Cangxiong Chen at Cangxiong.Chen@tcd.ie (personal webpage https://cangxiongchen.github.io/). Modern neural networks are usually overparameterised, i.e. they contain more parameters than necessary to fit the training data. The additional capacity from overparameterisation can improve optimisation and … Read more

Regression with uncontrolled changes in predictors

Eligibility: This project is only available to students on the online MSc Statistics and Data Science programme. If you are interested, please contact Dr. Rishabh Vishwakarma at rishabh.vishwakarma@tcd.ie Biodiversity and ecosystem function (BEF) studies investigate how diversity, including the number of species and their relative proportions affect the outputs (functions) of an ecosystem. Commonly, BEF experiments establish communities with different species and varying sown proportions at a timepoint t … Read more

TNR and colony population dynamics

This is a project for the M.Sc. in Statistics and Data Science This will look at a longitudinal case study of a Dublin feral/community-cat colony before and after a Trap-Neuter-Return (TNR) intervention, using CDPA data to investigate changes in population size and other factors that may influence the colony’s trajectory. The data for this project … Read more