University of Amsterdam Visit by PhD Student Bahrul Nasution
Earlier this year, our PhD student from the Department of Social Statistics, Bahrul Nasution, spent three months (February to May 2025) at the Amsterdam Machine Learning Lab (AMLab) at the University of Amsterdam as part of the Turing Scheme program.
During the research visit, Bahrul worked on flow matching applied to tabular data synthesis鈥攁 critical challenge in producing high-quality synthetic data while preserving privacy. Bahrul collaborated with Dr. Christian A. Naesseth and Floor Eijkelboom whose expertise in flow matching contributed significantly to this research direction.
Flow matching is a generative modelling technique that learns to transform random noise into meaningful data by following smooth trajectories. Think of it as a more flexible and efficient cousin of diffusion models. This approach has become a backbone for many modern generative models across different domains - from image generation to, in this case, synthetic tabular data.
The collaborative environment at AMLab fostered innovative discussions that refined the methodological framework and strengthened the international research network between the Department of Social Statistics and the University of Amsterdam. Working at one of Europe's leading machine learning research labs provided a unique environment to engage with cutting-edge computational and quantitative research, especially in synthetic data generation.
The findings from this work are now available as a preprint on , representing a significant milestone in advancing generative models for tabular data, especially to provide privacy-preserving and high-quality synthetic data. This collaboration exemplifies the Department's commitment to fostering global academic partnerships and contributing methodological advancements to the broader machine learning and statistical community.