Florentina Bunea

Florentina Bunea is a professor of statistics and data science and a member of the graduate fields of statistics, applied mathematics, and computer science. Her research is broadly centered on statistical machine learning theory and high-dimensional statistical inference. She is interested in developing new methodology accompanied by sharp theory for solving a variety of problems in data science and in the growing area of AI output evaluation. She continues to be interested in the general areas of mixture modeling, latent space estimation, sparsity and dimension reduction in high dimensions, and statistical optimal transport, as well as their applications, most recently to large language models and immunology, among others. Specific research foci include:

• Latent space modeling: discovery and inference;

• Structure adaptive estimation in high dimensional models, with finite sample guarantees;

• Mixture ensembles: computationally efficient parameter estimation with theoretical guarantees;

• Estimation and inference in discrete statistical optimal transport;

• Statistical machine learning theory;

• LLM evaluation.
   

Bunea is a fellow of the Institute of Mathematical Statistics (IMS) and an IMS Medallion Award recipient. She has served or is currently serving as an associate editor for a number of journals, including the Annals of Statistics, Bernoulli, JASA, JRSS-B, EJS, and the Annals of Applied Statistics. She is a co-editor for the Chapman and Hall Statistics and Applied Probability Monograph Series. She is also a member of Cornell Bowers’ Diversity, Equity, Inclusion, and Belonging (DEIB) council, working to promote the diversity of the workforce in data science disciplines.