Mark Roantree

Professor of Computing

Dublin City University

Ireland

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About

Mark Roantree is a Professor of Computing at Dublin City University in Ireland. His research interests encompass machine learning applications in sports analytics, environmental modeling, and health informatics. Recent publications include works on time series prediction, evaluating the impact of climatic factors on cardiovascular mortality, and developing machine learning models for analyzing player movements in sports.

Articles (14)

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2025

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2025

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2025

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2025

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2025

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2024

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2024

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2024

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2024

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2024

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2023

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2023

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IRELAND

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Toon de Beukelaar

Assistant Professor

KU Leuven

BELGIUM

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Kyriaki (Korina) Psistaki

Democritus University of Thrace

GREECE

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Johann Issartel

Dublin City University

IRELAND

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Elke Eichelmann

Assistant Professor/Lecturer

Dublin City University

IRELAND

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Mark Roantree

Research Interests

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About

Articles (14)

Intercomparison of Machine Learning Models to Determine the Planetary Boundary Layer Height Over Central Amazonia

Assessing the Impact of Climatic Factors and Air Pollutants on Cardiovascular Mortality in the Eastern Mediterranean Using Machine Learning Models

Estimating oxygen uptake in simulated team sports using machine learning models and wearable sensor data: A pilot study

A Meta-learner approach to multistep-ahead time series prediction

Exploring the trie of rules: a fast data structure for the representation of association rules

Test–Retest Reliability of Running Economy and Metabolic and Cardiorespiratory Parameters During a Multistage Incremental Treadmill Test in Male Middle- and Long-Distance Runners

Temporal Changes and Between-Competition Differences in the Activity Profile of Elite Hurling Referees

Adapting physics-informed neural networks to improve ODE optimization in mosquito population dynamics

A multidimensional database of in-game player movements (Actions and events) in gaelic football

Engineering Features from Raw Sensor Data to Analyse Player Movements during Competition

Moving well‐being well: Using machine learning to explore the relationship between physical literacy and well‐being in children

Air Temperature and Relative Humidity Datasets from an Urban Meteorological Network in the City Area of Novi Sad (Serbia)

Physical literacy in children: Exploring the construct validity of a multidimensional physical literacy construct

A methodology for classification and validation of customer datasets

Collaborators (11)

Sarahjane Belton

Andrew McCarren

Niall Moyna

Hannah Goss

Brendan Egan

Michael Scriney

Dongyun Nie

Toon de Beukelaar

Kyriaki (Korina) Psistaki

Johann Issartel

Elke Eichelmann

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