I’m a statistics postdoc at SAMSI and UNC Chapel Hill. I develop statistical methods for analyzing large and complex data sets in the physical sciences. My recent work has had two focal points: 1) developing spatio-temporal interpolation methods for analyzing oceanographic data from Argo profiling floats and 2) uncertainty quantification in ill-posed inverse problems with applications to the unfolding problem at the Large Hadron Collider at CERN. I’m currently participating in the SAMSI program on Mathematical and Statistical Methods for Climate and the Earth System and I also serve as a Statistics Consultant for the CMS experiment at CERN. I’ll be joining the Department of Statistics and Data Science at Carnegie Mellon University as an Assistant Professor in autumn 2018.
I obtained my PhD from EPFL in Lausanne, Switzerland in summer 2016 under the supervision of Prof. Victor M. Panaretos. I then spent a year as a postdoc at the University of Chicago, Department of Statistics, mentored by Prof. Michael L. Stein, before coming to SAMSI in September 2017. My BSc and MSc degrees are in Engineering Physics and Mathematics from Aalto University in Helsinki, Finland. I have also worked on variational Bayesian inference at Aalto University and on classification and anomaly detection problems at CERN and Fermilab. In autumn 2014, I was a visitor at the University of California, Berkeley, Department of Statistics, working on shape-constrained unfolding with Prof. Philip B. Stark.
Postal: Statistical and Applied Mathematical Sciences Institute (SAMSI), 4501 Research Commons, Suite 300, 79 T.W. Alexander Drive, Durham, NC 27709, USA