Meadhbh O'Neill

Meadhbh O'Neill


Confirm Centre, UL

Highly motivated individual studying statistical data science within the Confirm Smart Manufacturing Centre and the Mathematics Application Consortium for Science and Industry (MACSI) in the University of Limerick. My research involves creating state-of-the-art methodology using modern statistical techniques for optimizing manufacturing processes. My work includes the development of novel variable selection methods, which can be used to gain meaningful insights into the key drivers of a process. I have had a leading role in several high-impact interdisciplinary projects, where I have strengthened my communication, teamwork and problem-solving skills while working closely with industry experts.




Confirm Centre, University of Limerick
PhD in Statistics
Confirm Centre, University of Limerick
September 2018 - June 2023
University of Limerick
BSc in Financial Mathematics (1.1 - First Class Honours)
University of Limerick
September 2014 - June 2018

Industry Projects

Multinational Pharmaceutical Company
May 2021 - April 2022
  • Implement statistical models to extract meaningful information from large-scale high-throughput data measured via state-of-the-art metrology throughout the manufacturing process.
  • Development of new, robust and flexible statistical models for multivariate sensor data using functional data analysis.
  • Establishment of novel models for temporal derivatives (i.e., velocity and acceleration) with uncertainty estimates.
  • Construction of innovative prediction models, which capture between- and within-production line uncertainty.
Multinational Medical Device Company
December 2020 - March 2021
  • Investigate potential insights from manufacturing execution system (MES) data.
  • Statistical analysis of performance metrics including workload, scrap and idle time.
  • Construction of control limits to assess variability in different workstations, shifts, days of the week.
Multinational Electronics Company
August 2019 - June 2019
  • Gain a deeper understanding of the behaviour of a device through its voltage response curve.
  • Creation of a clustering algorithm to identify different shapes of voltage curves statistically.
  • Mapping of the curves to a physical failure mechanism using a mathematical model.
  • Obtain new insights into device failure modes and device-level variability.
  • Creation of an interactive dashboard that provides visual exploration of the failure location and automated clustering.


Global Young Scientists Summit
Based on my achievements to date and my contribution to several industrial projects, I was nominated and chosen to attend the 10th anniversary edition of the GYSS after a highly competitive selection process. The theme of GYSS 2022 was ‘Advancing Science, Creating Technologies for a Better World’. It was an exciting opportunity to interact and be mentored by Nobel laureates and eminent scientists, while also exchanging ideas with other young researchers.


The 15th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics)
Robust Distributional Regression Models with Automatic Variable Selection
December 2022 King's College, London
The 36th International Workshop on Statistical Modelling (IWSM)
Automatic Variable Selection in Distributional Regression Models
July 2022 University of Trieste, Italy
The 42nd Conference on Applied Statistics in Ireland (CASI)
Robust Distributional Regression with Automatic Variable Selection
May 2022 University College Cork, Ireland
The 4th International Conference on Econometrics and Statistics (EcoSta)
Smooth BIC Variable Selection Procedure for Heteroscedastic Data
June 2021 HKUST, Hong Kong
Invited Seminar at The Division of Mathematics for Vehicle Engineering
Industrial Feature Selection using a Smooth Information Criterion
June 2021 Fraunhofer ITWM, Germany
The 21st ECMI Conference on Industrial and Applied Mathematics
Industrial Feature Selection Using a Smooth Information Criterion
April 2021 University of Wuppertal, Germany
The 39th Conference on Applied Statistics in Ireland (CASI)
Differentiable Penalized Regression
May 2019 Trinity College Dublin, Ireland