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SUMMARY:Gentle introduction to causal inference and estimation of causal e
 ffects in the wild - Dr Yordan Raykov\, School of Mathematical Sciences\, 
 University of Nottingham\, UK
DTSTART:20250721T113000Z
DTEND:20250721T123000Z
UID:TALK234430@talks.cam.ac.uk
CONTACT:Dace Apšvalka
DESCRIPTION:*Speaker*: Dr Yordan Raykov\, School of Mathematical Sciences\
 , University of Nottingham\, UK (*Visiting in person*)\n\n*Title*: Gentle 
 introduction to causal inference and estimation of causal effects in the w
 ild\n\n*Abstract*: This hands on tutorial walks participants from first pr
 inciples to state of the art practice in causal inference. We begin by sho
 wing how the back door and front door criteria\; the causal direction of a
 n association and how we can determine whether an effect is identifiable. 
 We then contrast classic parametric estimators with modern non parametric\
 , machine learning based approaches\, explaining when prediction accuracy 
 matters\, when it does not\, and why. Next\, we tackle unmeasured confound
 ing by presenting instrumental variable and negative control strategies\, 
 as well as how classical latent variable models can be used in many situat
 ions. A rapid tour of constraint based\, score based\, and functional caus
 al model algorithms\, together with the Python packages that implement the
 m\, illustrates how to move from data to a working causal graph. Finally\,
  we survey front line challenges such as longitudinal data with time varyi
 ng confounding\, irregular sampling schedules\, and high dimensional outco
 mes like feature vectors\, brain connectome matrices\, or wearable device 
 curves. By the end of the session hopefully you will know when a causal qu
 estion is answerable\, how to estimate its effect using the right tool\, a
 nd where to find some of the software that lets you put these ideas into p
 ractice. \n\n*Bio*:\nDr Yordan Raykov is an Assistant Professor in Data Sc
 ience at the University of Nottingham. His research develops novel statist
 ical machine learning algorithms for clustering\, dimensionality reduction
 \, feature sharing\, and sequence modeling\, with applications in digital 
 sensor monitoring and precision medicine. Before joining Nottingham\, he w
 orked in both academia and industry\, including with ARM Cambridge\, Radbo
 udumc\, UCB Pharma\, Johns Hopkins\, and the Michael J. Fox Foundation.\n\
 n*Venue*: MRC CBU West Wing Seminar Room and Zoom https://us02web.zoom.us/
 j/82385113580?pwd=RmxIUmphQW9Ud1JBby9nTDQzR0NRdz09 (Meeting ID: 823 8511 3
 580\; Passcode: 299077)
LOCATION: MRC-CBU\, 15 Chaucer Road\, Cambridge
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