Research

My research focuses on using statistical methodology to understand complex for complex real-life problems, with an emphasis on Bayesian inference. While most of my work is in climate, I am also interested in working on any interesting problems where my statistical expertise can be useful.

Research themes

Below are some of the main research directions I work in:

• Long-range dependence

  Efficient Bayesian analysis of long-memory processes, with applications to climate data.

• Bayesian age-depth modeling

  Dating uncertainty and synchronization of layer-counted paleoclimate proxy records.

• Early warning signals

  A Bayesian model-based approach for identifying early warning signals preceding tipping points.

I have also worked on other topics, including deep learning methods as well as data integration. This page will be updated as more papers get published.

If you are interested in a collaboration, please feel free to contact me.

Other pages

• Selected publications → Publications
• Full CV → CV