Uploaded March 2026 | Updated September 2026, 1 week ago
Tamás Budavári, a professor in the Department of Applied Mathematics and Statistics, is recognized for his research at the intersection of data science and statistics, with emphasis on observational astronomy, urban planning, and, more recently, neurocritical care. He maintains joint appointments in the departments of Neurology and Physics and Astronomy, as well as a secondary appointment in the Department of Computer Science.
Budavári’s research focuses on computational and statistical challenges associated with real-world big data. Over the years, he has made significant contributions to areas such as photometric redshift estimation, probabilistic catalog matching, optimal image reconstruction, and the strategic intervention for vacant housing in Baltimore. He has developed innovative techniques for efficient querying of extensive astronomical catalogs and simulations, including those from the Sloan Digital Sky Survey and the Hubble Space Telescope.
Tamás Budavári, a professor in the Department of Applied Mathematics and Statistics, is recognized for his research at the intersection of data science and statistics, with emphasis on observational astronomy, urban planning, and, more recently, neurocritical care. He maintains joint appointments in the departments of Neurology and Physics and Astronomy, as well as a secondary appointment in the Department of Computer Science.
Budavári’s research focuses on computational and statistical challenges associated with real-world big data. Over the years, he has made significant contributions to areas such as photometric redshift estimation, probabilistic catalog matching, optimal image reconstruction, and the strategic intervention for vacant housing in Baltimore. He has developed innovative techniques for efficient querying of extensive astronomical catalogs and simulations, including those from the Sloan Digital Sky Survey and the Hubble Space Telescope.
