You are all cordially invited to the AMLab seminar on Tuesday **March 6** at 16:00 in C3.163, where **Thijs van Ommen** will give a talk titled “**Accurate and efficient causal discovery**”. Afterwards there are the usual drinks and snacks!

**Abstract**: Will administering a certain chemical cause a cancer cell to stop multiplying? To answer this and other scientific “what-if” questions, we need causal models, which describe the cause-effect relations within a system of interest. Because even domain experts may not know the right causal model, we want to learn it automatically from large-scale data. This problem is called causal discovery, and is very difficult: the signals in the data that allow us to distinguish different causal models are often weak, so we need to be careful when interpreting them. Also, the number of candidate models that must be considered makes this problem computationally challenging. I will present some of my recent results which are an important step towards developing a statistically accurate and computationally efficient algorithm for causal discovery.