I am Associate Senior Lecturer at the Department of Mathematical Sciences of Chalmers University of Technology and University of Gothenburg and working on statistical theory and methodology for dynamical stochastic models. In general, dynamical stochastic models describe the evolution of processes and systems which have dynamics with temporal or spatial interactions and show stochastic behaviour. Applications of such models are found in all areas, be it to model the change in the extension of the West Antarctic ice shelf, the interaction of neurons in the brain or the deformation of tissue during tumour growth.

- Github: https://github.com/mschauer
- Academic website: http://www.math.chalmers.se/~smoritz/index.htm
- Twitter: @MoritzSchauer

20:00 UTC

ZigZagBoomerang.jl provides piecewise deterministic Monte Carlo methods. They have the same goal as classical Markov chain Monte Carlo methods: to sample for example from the posterior distribution in a Bayesian model. Only that the distribution is explored through the continuous movement of a particle and not one point at a time. This provides new angles of attack: I showcase a multithreaded sampler and high-dimensional variable selection sampler.