Nora Amama-BenHassun
PhD candidate in Statistics and Operations Research at UPC. Her research focuses on the statistical validation of synthetic tabular data, with special interest in resemblance, utility and privacy.
Nora Amama-BenHassun
PhD candidate
Statistics and Operations Research (Universitat Politècnica de Catalunya-BarcelonaTECH)
Biosketch
Nora Amama-BenHassun graduated in Statistics from the University of Barcelona and Polytechnic University of Catalonia (UB-UPC) in 2022. She completed the Master’s degree in Statistics and Operations Research (MESIO UPC-UB) in 2023, with a specialization in Data Science.
She has worked in different applied fields, including consulting projects for the pharmaceutical sector at Datancia, where she developed interactive R Shiny tools aligned with CLSI procedures, applied statistical methodologies to support regulatory accuracy and compliance, automated LaTeX report generation, and collaborated on data visualization and user-interface design. She also completed an internship at YouGov, where she designed statistically robust surveys, worked on sampling and quota adjustments, and analysed public opinion and market research data for clients such as Sony, Orange Bank, and Tendam. In addition, she worked at Cofidis España in the Risk Department, where she contributed to fraud detection and risk assessment process automation using SAS and Excel, identified high-risk establishments and contracts, monitored customer acceptance systems, and developed dashboards and reports for risk management.
Alongside her professional activity, she has also contributed to academic and institutional initiatives, including service as a board member of the School of Mathematics and Statistics (FME) at UPC and teaching support in introductory courses in statistics, computer science, and calculus.
She has worked in different applied fields, including consulting projects for the pharmaceutical sector at Datancia, where she developed interactive R Shiny tools aligned with CLSI procedures, applied statistical methodologies to support regulatory accuracy and compliance, automated LaTeX report generation, and collaborated on data visualization and user-interface design. She also completed an internship at YouGov, where she designed statistically robust surveys, worked on sampling and quota adjustments, and analysed public opinion and market research data for clients such as Sony, Orange Bank, and Tendam. In addition, she worked at Cofidis España in the Risk Department, where she contributed to fraud detection and risk assessment process automation using SAS and Excel, identified high-risk establishments and contracts, monitored customer acceptance systems, and developed dashboards and reports for risk management.
Alongside her professional activity, she has also contributed to academic and institutional initiatives, including service as a board member of the School of Mathematics and Statistics (FME) at UPC and teaching support in introductory courses in statistics, computer science, and calculus.
Since April 2024, she has been a PhD candidate in the Statistics and Operations Research Programme at the Universitat Politècnica de Catalunya (UPC), under the supervision of Daniel Fernández and Jordi Cortés. She is a member of the GRBIO research group and collaborates in research developed within the IDEAI-UPC center in connection with the Siemens Energy AI Chair. Her research focuses on the statistical validation of synthetic tabular data, with particular interest in evaluating resemblance, utility, privacy, and the trade-offs between these dimensions, as well as in developing rigorous validation frameworks for the safe and transparent use of synthetic data.
Main Research Lines:
Synthetic data generation and validation
Statistical validation of synthetic tabular data
Applied statistics
Machine learning and applied AI
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