Anne van Delft

Anne van Delft is an Assistant Professor of Statistics at Columbia University's Department of Statistics. She joined Columbia in Fall 2020 after completing a postdoctoral fellowship in mathematical statistics at Ruhr University Bochum, Germany, following her PhD in Statistics from Maastricht University (2016). Her research focuses on stochastic processes in function spaces, particularly nonstationary function-valued time series, with applications in fields like genomics, climatology, and econometrics. She emphasizes mathematically rigorous methodologies that balance theoretical depth with computational efficiency.

Her work addresses challenges in analyzing complex data structures such as curves, surfaces, and manifolds, with applications to (neuro-)imaging and cell biology. Anne is an Associate Editor for *Statistical Inference for Stochastic Processes* and the *Journal of the American Statistical Association Reviews*. She received the prestigious Itô Prize in 2021 for outstanding contributions to stochastic analysis.

Her research interests span statistical methodology for functional data, nonstationary processes, and interdisciplinary applications. She advocates for methodological advancements that bridge theory and practice, ensuring applicability in real-world scenarios.