معرفی
Natalia Stepanova is a Professor in the School of Mathematics and Statistics at Carleton University. Her research focuses on high-dimensional statistical inference, nonparametric estimation, and hypothesis testing. She holds an office in Herzberg Laboratories (5229HP) and can be reached via email at nstep@math.carleton.ca.
Her research interests emphasize modern challenges in statistical theory, particularly in developing adaptive methods for sparse data analysis, nonparametric models, and signal recovery. Recent work includes advancements in sup-functional analysis for empirical processes and efficient kernel-based density estimation.
Stepanova’s publications (2010–2025) consistently address themes in nonparametric methods, high-dimensional data, and statistical efficiency. Key contributions include variable selection techniques, goodness-of-fit testing, and adaptive algorithms for sparse additive models. No scientific awards are explicitly listed in the provided materials.
Her academic contributions span graduate advising and collaborative research within the Ottawa-Carleton Institute for Mathematics and Statistics (OCIMS). No specific grants or lab affiliations are detailed in the text.
