Thomas Sager

Professor innovating in the area of applied and theoretical statistics, Thomas Sager holds a distinguished position at the University of Texas at Austin, where he contributes significantly to the fields of statistics and data sciences. With a deep-seated interest in the intersection of air pollution, financial statistics, and law, Professor Sager's work extends into the realms of auditing and quality assurance, particularly within insurance companies. His research is characterized by a robust econometric analysis of insurance companies, offering insights that bridge the gap between theoretical frameworks and practical applications. Professor Sager's academic journey began at the University of Iowa, where he earned his B.A., M.S., and Ph.D., laying a strong foundation for his future endeavors in statistics. His interdisciplinary affiliations at the University of Texas include the Department of Statistics and Data Science and the Information, Risk, and Operations Management department, reflecting his broad expertise and collaborative spirit. Throughout his career, Professor Sager has been recognized for his exceptional teaching abilities, particularly within the Master's curriculum at the McCombs School of Business. His dedication to education is evident in his commitment to fostering a deep understanding of statistical principles among his students, preparing them for successful careers in diverse fields. In addition to his teaching accolades, Professor Sager's research contributions have been instrumental in advancing the understanding of statistical applications in insurance and financial sectors. His work not only enhances academic discourse but also provides valuable insights for industry practitioners seeking to navigate the complexities of risk management and financial analysis. Professor Sager continues to innovate and inspire in the field of statistics, leveraging his extensive knowledge to address contemporary challenges in air pollution, insurance, and financial statistics. His contributions to the academic community and beyond underscore his role as a leading figure in the advancement of statistical science.