I am a data scientist and a statistician, who tries to combine the best of two worlds. I have over years of experience and my area of expertise lies in the construction and validation of predictive models. I also have experience in other research areas, such as clustering and assessing the agreement or reliability of repeated measurements. Further, I am proficient in and have a passion for programming (especially in R). I love to immerse myself in new research projects, which require me to solve complex problems and to analyze the data thoroughly. Tackling new, unfamiliar challenges is something I look forward to as it allows me to grow and develop new knowledge and new skills.

I did my PhD in Actuarial Science at the KU Leuven, under the supervision of professor dr Katrien Antonio. My research focused on the development and evaluation of predictive modeling techniques within actuarial science. In my research, I assessed the performance of both statistical and machine learning methods. Another part of my research focused on the development of fraud detection models using social network features. Here, I examined both the methodological and practical part. If you want to read my PhD thesis, you can do so by clicking on this link.

Before my PhD, I worked as a biostatistian in the International Ovarian Tumor Analysis (IOTA) group and I stayed connected to biomedical research throughout my whole career. In the IOTA group, I was part of an interdisciplinary team of researchers connected to UZ Leuven and KU Leuven. I worked on numerous projects, which provided me with a firm and solid basis in biostatistics. Furthermore, my main research projects focused on the development and validation of clinical prediction models.

Work experience

A detailed overview of my work experience and skills is given in my CV, which you can access via this link. If you are interested in my publications, click on this link.

July 2024 - Present	Honorary Research Associate
	Department of Metabolism, Digestion and Reproduction Faculty of Medicine Imperial College London
	Projects (click to open): I am in charge of all aspects of the analysis, including data management, designing and performing the analysis, compiling and interpreting the results, and ultimately preparing a report and a publishable article.
Oct 2023 - Present	Risk Officer
	Valuation Non-Life Risk Ageas
	Projects (click to open): I contribute to the ongoing success of the organization by optimizing risk assessment frameworks, enhancing operational efficiency, and driving strategic decision-making. Drawing on my methodological expertise, I continuously refine, improve, and challenge existing processes. My responsibilities include: automating internal model processes: managing the automation of internal model processes and runs, streamlining operations for enhanced efficiency; methodology evaluation and enhancement: thoroughly examining and challenging existing methodologies, whilst developing and implementing alternative methods to drive continuous improvement; guiding tool development: comprehensive testing and guiding the development of internal model tools, ensuring robustness and reliability; tool deployment and testing: leading the development and deployment of tools for testing the models, facilitating thorough evaluation and validation of model outcomes; implementation of external reinsurance model: implementing the external reinsurance model, optimizing risk management strategies for the organization; documentation management: ensuring comprehensive documentation of processes and procedures as well as of the implementations, fostering transparency and accountability across all operations.
Oct 2019 - Sep 2023	Doctoral researcher
	Department of Accountancy, Finance and Insurance Faculty of Economics and Business KU Leuven
	Projects (click to open): My PhD was part of a collaboration between the KU Leuven and a Belgian insurance company. I took responsibility for translating the insurance company's research question into an analysis plan as well as for planning, organizing, programming, executing and analyzing the research. Further, I communicated the research findings in a clear and concise way to the company at regular intervals. The main projects that I worked on are: workers' compensation insurance: constructed an algorithm to reduce hierarchically structured categorical variables to their essence; developed a workflow for the construction and validation of prediction models when both subject-specific and hierarchically structured categorical variables are available. fraud detection: development of a simulation engine to develop and to evaluate insurance fraud detection strategies.
Feb 2015 - Sep 2018	Statistical researcher
	Department of Development and regeneration Faculty of Medicine KU Leuven
	Projects (click to open): I was part of the statistical unit of the IOTA group. I conducted the statistical analyses, documented, presented and discussed the results with the multidisciplinary team. Additionally, I took responsibility for managing and encrypting the databases as well as for developing (statistical) software to facilitate our research. I worked on numerous projects, which can best be summarized as follows: clinical research: examining relation patient characteristics and tumour type; agreement and reliability of ultrasound measures, of clinical blood and urine tests; evaluation and (external) validation of clinical prediction models. methodological research: evaluation of performance measures assessing discrimination and calibration; examining the effect of shrinkage methods on predictive performance. database management: detection and cleaning of inconsistencies; data wrangling; merging data from different hospitals to create the main database; development of statistical software: to manage the database; assessing agreement and reliability; to assess the model's predictive performance; to encrypt the database and software-specific data files.
Mar 2016 - Apr 2019	Voluntary research associate
	Department of Managerial Economics, Strategy and Innovation Faculty of Economics and Business KU Leuven
	Projects (click to open): I worked as a consulting statistical researcher on (confidential) projects for the private sector. My main tasks were to perform the statistical analysis and to report the research findings to the company.

July 2024 - Present	Honorary Research Associate
	Department of Metabolism, Digestion and Reproduction Faculty of Medicine Imperial College London
Projects (click to open): I am in charge of all aspects of the analysis, including data management, designing and performing the analysis, compiling and interpreting the results, and ultimately preparing a report and a publishable article.
Oct 2023 - Present	Risk Officer
	Valuation Non-Life Risk Ageas
Projects (click to open): I contribute to the ongoing success of the organization by optimizing risk assessment frameworks, enhancing operational efficiency, and driving strategic decision-making. Drawing on my methodological expertise, I continuously refine, improve, and challenge existing processes. My responsibilities include: automating internal model processes: managing the automation of internal model processes and runs, streamlining operations for enhanced efficiency; methodology evaluation and enhancement: thoroughly examining and challenging existing methodologies, whilst developing and implementing alternative methods to drive continuous improvement; guiding tool development: comprehensive testing and guiding the development of internal model tools, ensuring robustness and reliability; tool deployment and testing: leading the development and deployment of tools for testing the models, facilitating thorough evaluation and validation of model outcomes; implementation of external reinsurance model: implementing the external reinsurance model, optimizing risk management strategies for the organization; documentation management: ensuring comprehensive documentation of processes and procedures as well as of the implementations, fostering transparency and accountability across all operations.
Oct 2019 - Sep 2023	Doctoral researcher
	Dpt. of Accountancy, Finance and Insurance Faculty of Economics and Business KU Leuven
Projects (click to open): My PhD was part of a collaboration between the KU Leuven and a Belgian insurance company. I took responsibility for translating the insurance company's research question into an analysis plan as well as for planning, organizing, programming, executing and analyzing the research. Further, I communicated the research findings in a clear and concise way to the company at regular intervals. The main projects that I worked on are: workers' compensation insurance: constructed an algorithm to reduce hierarchically structured categorical variables to their essence; developed a workflow for the construction and validation of prediction models when both subject-specific and hierarchically structured categorical variables are available. fraud detection: development of a simulation engine to develop and to evaluate insurance fraud detection strategies.
Feb 2015 - Sep 2018	Statistical researcher
	Dpt. of Development and regeneration Faculty of Medicine KU Leuven
Projects (click to open): I was part of the statistical unit of the IOTA group. I conducted the statistical analyses, documented, presented and discussed the results with the multidisciplinary team. Additionally, I took responsibility for managing and encrypting the databases as well as for developing (statistical) software to facilitate our research. I worked on numerous projects, which can best be summarized as follows: clinical research: examining relation patient characteristics and tumour type; agreement and reliability of ultrasound measures, of clinical blood and urine tests; evaluation and (external) validation of clinical prediction models. methodological research: evaluation of performance measures assessing discrimination and calibration; examining the effect of shrinkage methods on predictive performance. database management: detection and cleaning of inconsistencies; data wrangling; merging data from different hospitals to create the main database; development of statistical software: to manage the database; assessing agreement and reliability; to assess the model's predictive performance; to encrypt the database and software-specific data files.
Mar 2016 - Apr 2019	Voluntary research associate
	Dpt. of Managerial Economics, Strategy and Innovation Faculty of Economics and Business KU Leuven
Projects (click to open): I worked as a consulting statistical researcher on (confidential) projects for the private sector. My main tasks were to perform the statistical analysis and to report the research findings to the company.

Education

PhD in Actuarial Science, 2023
      KU Leuven, Belgium

MSc in Statistics, 2019
      KU Leuven, Belgium
      Combined with full-time job as a researcher at KU Leuven

MSc in Psychology, 2014
      KU Leuven, Belgium

BSc in Psychology, 2012
      KU Leuven, Belgium

Software

You can find a selected set of my software projects on my Github page. Of these, two are published on CRAN. If you have any questions or suggestions, please feel free to contact me! I look forward to hearing from you.

CRAN packages

CalibrationCurves

With the CalibrationCurves package, you can generate (generalized) calibration curves, which are essential for evaluating the calibration performance of predictive models. In addition, it also computes a comprehensive range of statistics to assess the predictive performance of your model. As such, this package provides the necessary tools to evaluate the performance of your predictive model.

Detailed information as well as a tutorial can be found on the package’s website.

Key Features:

• Generate calibration plots easily (both with base R and ggplot).
• Assess model performance with various calibration and discrimination metrics.
• Supports both binary and continuous outcomes.

actuaRE

Using this package, you can fit a random effects model using either the hierarchical credibility model, a combination of the hierarchical credibility model with a generalized linear model or a Tweedie generalized linear mixed model.

As the CalibrationCurves package, this package also has its own dedicated website with a tutorial and comprehensive overview of the package’s functionality.

Key Features:

• Fit a random effects model with nested random effect using three different estimation methods.
• Obtain a comprehensive overview of the properties of the fitted model.
• Verify whether a fitted model has the balance property (i.e., the sum of the predicted values equals the sum of actual observations).
• Regain the balance property by adjusting the intercept term.
• Analyze and visualize the random effect predictions.

I am committed to continuously improving these packages and adding new features based on user feedback and the latest research developments. Your input is invaluable, and I welcome any questions, suggestions, or collaboration ideas.