## Research

My general area of research is **uncertainty quantification**, at the intersection of applied mathematics, probability, statistics, and computational science.
A common theme underlying many of my current research interests is to add ‘the right amount of uncertainty’ to an otherwise certain or near-certain prediction, in order to correctly compensate for over-confidence in the modelling process.
In the words of Julian Baggini:

The mark of a mature, psychologically healthy mind is indeed the ability to live with uncertainty and ambiguity, but only as much as there really is.

- Outlines of some research topics
- List of academic publications
- List of conferences, talks, and other academic gatherings

My research is funded by the Free University of Berlin within the Excellence Initiative of the German Research Foundation (DFG). I am also a co-PI on the ECMath project CH15 “Analysis of Empirical Shape Trajectories”.

I have also received support from

- the DFG-funded project A06 “Enabling Bayesian uncertainty quantification for multiscale systems and network models via mutual likelihood-informed dimension reduction”, part of the Collaborative Research Centre SFB 1114 “Scaling Cascades in Complex Systems”, as PI;
- the US National Science Foundation (NSF) under grant DMS-1127914 to the Statistical and Applied Mathematical Sciences Institute (SAMSI) and SAMSI's 2017–2018 Quasi-Monte Carlo Working Group II “Probabilistic Numerics”;
- the King's College London – Freie Universität Berlin Funding Programme for Joint Research Workshops;
- the University of Warwick International Partnership Fund;
- the US Department of Energy NNSA (award DE-FC52-08NA28613), through the California Institute of Technologyâ€™s ASC/PSAAP Center for the Predictive Modeling and Simulation of High Energy Density Dynamic Response of Materials;
- the US Junior Oberwolfach Fellows project (NSF Grant 0540019);
- the Oberwolfach Leibniz Graduate Students programme;
- the University of Warwick Research Development Fund.