András Hubai is a biologist specializing in computer modeling and the statistical analysis of large databases. His doctoral research focuses on the problem of information persistence in the origin of life. At the Rényi Institute, he contributes to the work of two groups: he performs health data analysis in collaboration with the Health Services Management Training Centre of Semmelweis University, and he develops epidemic forecasting software for the National Laboratory for Health Security. He works closely with mathematicians, healthcare professionals, and artificial intelligence experts.

As a data steward, his task is to help identify the intersection between data that can be shared freely and data that is worth sharing. This poses a particular challenge at the Rényi Institute, where theoretical mathematics is largely data-independent, and applied mathematicians typically work with data provided by others.

“Championing data sharing is a noble principle. But as we institutionalize it, we must ensure that we always provide more value to researchers than the burden we place on them.”