Daniel Vergara

Doctoral Student at Marine Technology

New researcher in the area of applied Machine Learning for improving Energy Efficiency in ships. My research aims to improve the operation and control of internal combustion engines using data-driven models and first principles modelling and to analyse their performance under new modes of operation.
His research would reduce the use of fuel in said ships and hence to increase operations revenue whilst reducing emissions.
Daniel's work also involves applied statistics, modelling, simulation, and control.

Source: chalmers.se
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Showing 2 publications

2023

A machine learning based Bayesian decision support system for efficient navigation of double-ended ferries

Daniel Vergara, Martin Alexandersson, Xiao Lang et al
Journal of Ocean Engineering and Science. Vol. In Press
Journal article
2023

Power allocation influence on energy consumption of a double-ended ferry

Daniel Vergara, Martin Alexandersson, Xiao Lang et al
Proceedings of the International Offshore and Polar Engineering Conference
Paper in proceeding

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Showing 1 research projects

2021–2024

AI-enhanced energy efficiency measures for optimal ship operations to reduce GHG emissions

Wengang Mao Marine Technology
Xiao Lang Marine Technology
Daniel Vergara Marine Technology
VINNOVA

6 publications exist
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