Causal Inference Interest Group (CIIG)

The CIIG hosts monthly seminars which discuss recent advances in the field of causal inference, from both empirical and formal perspectives. Everyone with an interest in discussing causal inference is very welcome to come along and I particularly encourage PhD students and research associates.

Presenters are drawn from both academia and industry. If you would like to present your research (or related causal inference material) at the CIIG, please contact yours truly.

For more information see the main ATI website.

Sign up

Subscribe to the mailing list to stay tuned about upcoming talks. There is also an internal Slack channel at the Turing where you can find out about upcoming talks and events.

Calendar of events

Below you will find the upcoming talks (click on the ‘Agenda’ tab to get a list of all scheduled talks).


  • 45 minutes of presentation
  • ~10 minutes of discussion, led by the host, usually myself
  • Q & A

If you have questions during the talk, please submit the questions using the Zoom Q & A feature. Time permitting, and depending on the volume of questions, the host will either ask your question for you or confirm with you to ask the question yourself and unmute you at a suitable time.

Practical details

  • Where? Always online but sometimes also in-person at the Alan Turing Institute, London, UK (but will then be streamed as well).
  • When? Mostly every month. Times and dates may vary. The most up-to-date schedule can be found below.
  • Do you have a calendar which I can subscribe to? You bet! Scroll to the bottom of this page.
  • Will the talks be recorded? No, but the slides will be made available on this website.

Other causal inference seminar series

As causal inference is gaining in popularity, there are now many other seminar series which discuss causal inference. Here are some of them:

Past program

12/12/22Matej ZečevićTU DarmstadtCausal explanations of structural causal models [Slides]Online
28/11/22Max LittleMIT / BirminghamGRAPL: A computational library for nonparametric structural causal modelling, analysis and inference [Slides]Online
18/10/21Ricardo SilvaUCLA New Class of Algorithms for Bounding Causal Effects [Slides]Online
25/10/21Jonathan RichensDeepMindCounterfactual harmOnline
08/11/21Johannes TextorNijmegenHow to test DAG models [Slides]Online
15/11/21Virginia AgliettiDeepMindDynamic Causal Bayesian Optimization [Slides]Online/ATI
29/11/21Silvia Chiappa & Alan MalekDeepMindSelecting the Asymptotically Best Causal Effect Estimator with Multi-Armed BanditsOnline
06/12/21Nicola BranchiniEdinburghCausal Entropy OptimizationOnline
13/12/21Lewis HammondOxfordReasoning About Causality in Games [Slides]Online
17/01/22Hana ChocklerCausaLens/KingsActual causality, responsibility, explanations, and fairness – a bird’s eye view [Slides]Online
31/01/22Ciarán Gilligan-LeeSpotify/UCLLearning problems from The Causal Hierarchy [Slides]Online
14/02/22Qingyuan ZhaoCambridgeMendelian randomization: Old and new insights [Slides]Online
28/02/22Kellyn ArnoldLeedsThe effects of lockdown timing on COVID-19 cases across Europe: A counterfactual modelling study [Slides]Online