Hanne Kekkonen

Hanne Kekkonen currently serves as an Assistant Professor at the Delft Institute of Applied Mathematics, Faculty of Electrical Engineering, Mathematics and Computer Science at TU Delft. After earning her Ph.D. in applied mathematics from the University of Helsinki in 2016, she expanded her expertise through research positions at the University of Warwick and University of Cambridge before joining TU Delft in 2020. Her academic focus centers on statistical inverse problems, uncertainty quantification, and Bayesian non-parametric models. As an applied mathematician, she has made significant contributions to the field of Bayesian statistics and inverse problems, with particular emphasis on edge-preserving random tree Besov methods and efficient Bayesian calibration of mechanical properties. Her teaching portfolio includes involvement in AI Skills programs, where she contributes to courses on machine learning techniques and statistical analysis. Dr. Kekkonen is actively engaged in mathematics outreach and continues to advance research in integration of active learning and MCMC sampling for efficient Bayesian calibration.