2024 Department Dissertation Awards

With sincere appreciation for all those involved in the nomination and review process, the Department of Statistics proudly announces the winners of the full group of doctoral dissertation awards this year. Each hard-won distinction is accompanied by a prize of $1,000, and recipients will be presented with their certificates during the department's diploma ceremony on June 16th. Congratulations to these outstanding students!

Theodore W. Anderson Theory of Statistics Dissertation Award

Isaac Gibbs – for his groundbreaking work on adaptive conformal inference, maintaining prediction coverage over time despite substantial changes in the data distribution, and his amazing contribution to conformal prediction, quantifying the uncertainty of modern black box algorithms without distributional assumptions.

Jerome H. Friedman Applied Statistics Dissertation Award

Sifan Liu – for her work on high dimensional integration, machine learning optimization strategies and pre-integration in randomized quasi-Monte Carlo, and its novel application in data science.

Ingram Olkin Interdisciplinary Research Dissertation Award

Ying Jin – for pioneering model-free selective inference methods for multi-stage decision pipelines such as job hiring and drug discovery, and for providing new methods for diagnosing replication failure.

Probability Dissertation Award

Kangjie Zhou – for discovering precise high-dimensional asymptotics for projection pursuit with random data, using techniques from spin glasses and empirical process theory.