Highlights

• Senior Lecturer in Statistics, School of Mathematical Sciences
• Funded Investigator, Insight Research Ireland Centre for Data Analytics
• 60+ peer-reviewed journal and conference papers
• Supervising/Supervised 5 PhD students and 40+ MSc projects
• Coordinated/delivered 30+ modules

Short Bio

Dr Eric Wolsztynski obtained his PhD in Statistical Signal and Image Processing at the University of Nice (France) in 2006, working on theoretical aspects of robust estimation methods and their application to image processing. In 2007 he joined the Signal Processing Group at Technische Universität Darmstadt (Germany), where he worked on developing robust methods for tracking wireless terminals in realistic environments. Dr Wolsztynski joined the Statistics Department at UCC as a postdoc in 2008, where he is now Senior Lecturer in Statistics. Dr Wolsztynski is a Funded Investigator with the Insight Research Ireland Centre for Data Analytics.

Research Support

2020-ongoing: Funded Investigator, Insight Research Ireland (12/RC/2289-P2, support as per SFI model)
2019-20: co-PI, Insight industrial project (ca. €90k)
2014: UCC Strategic Research Fund (€3,960)
2011-17: collaborator, SFI (PI 11/1027, €1.2m, PI Finbarr O'Sullivan)

Dr Wolsztynski's research interests combine theoretic and applicative aspects of statistical learning, computational statistics, and data-driven estimation methods. His work primarily focuses on predictive modelling techniques, with specific focus on modelling for diagnostic imaging analysis and multi-omics for healthcare, and more generally methodologies for the analysis of wide data. Recent contributions include the development of a 3D-coherent model of volumetric tumour activity derived from PET imaging data, and the definition of molecular uptake gradients, which are statistical summaries extracted from this model to create novel biomarkers for non-invasive assessment. This research aims at creating opportunities to improve tumour characterization and patient prognosis, and stems from clinical collaborations in Ireland and the USA. Other past and current research projects include the development of machine learning methodologies for non-life insurance modelling, and forecasting models for granular fintech data. Dr Wolsztynski also enjoy collaborations in the field of renewable energies.

Software:
R package 'mia' (Statistical Modelling and Radiomics Tools for Medical Imaging Analysis)
R package 'volumetrics' (3D uptake model for PET imaging data)
To install a package, run these instructions within R (e.g. for package mia): library(devtools)
install_github("ericwol/mia")
library(mia)