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).
Format
- 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
Date | Speaker | Org | Title | Location |
---|---|---|---|---|
Matej Zečević | TU Darmstadt | Causal explanations of structural causal models [Slides] | Online | |
Max Little | MIT / Birmingham | GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference [Slides] | Online | |
Ricardo Silva | UCL | A New Class of Algorithms for Bounding Causal Effects [Slides] | Online | |
Jonathan Richens | DeepMind | Counterfactual harm | Online | |
Johannes Textor | Nijmegen | How to test DAG models [Slides] | Online | |
Virginia Aglietti | DeepMind | Dynamic Causal Bayesian Optimization [Slides] | Online/ATI | |
Silvia Chiappa & Alan Malek | DeepMind | Selecting the Asymptotically Best Causal Effect Estimator with Multi-Armed Bandits | Online | |
Nicola Branchini | Edinburgh | Causal Entropy Optimization | Online | |
Lewis Hammond | Oxford | Reasoning About Causality in Games [Slides] | Online | |
Hana Chockler | CausaLens/Kings | Actual causality, responsibility, explanations, and fairness – a bird’s eye view [Slides] | Online | |
Ciarán Gilligan-Lee | Spotify/UCL | Learning problems from The Causal Hierarchy [Slides] | Online | |
Qingyuan Zhao | Cambridge | Mendelian randomization: Old and new insights [Slides] | Online | |
Kellyn Arnold | Leeds | The effects of lockdown timing on COVID-19 cases across Europe: A counterfactual modelling study [Slides] | Online |