Thank you for your kind words @oacarah! Thanks Kazuki Yoshida for bringing this to my attention. Jake Westfall, I enjoyed reading your article and look forward to more. :)

I'm excited to be speaking tomorrow at University of Southern California's AI Rising Stars Symposium. Thank you for extending an invitation Bistra Dilkina and Sean Ren 🔆.

Happy New year! Posting a few intentions for the upcoming year. In particular, "Be who you needed when you were going through hard times".

Deadline extension for our #ICML workshop on missing values to June 8! Keynotes by M. van der Schaar, R. Caruana Karthika Mohan, Mauricio Sadinle, Madeleine Udell Panel discussants will include A. Gelman I. Shpitser artemiss-workshop.github.io w/ @JulieJosseStat Jes Frellsen Gael Varoquaux 🦋

Here is a wonderful blog post about missingness graphs that allows one to answer quite a lot of questions about missingness. Great job, Jake Westfall! Judea Pearl

Good news for all victims of missing-data. We are informed that our paper "Graphical Models for Processing Missing Data" (with Karthika Mohan) has pacified all reviewers' objections and will be published in JASA, see ucla.in/2LdEjZW So, if you are confused, as most people 1/n

I am excited to announce that I will be joining the School of #EECS Oregon State University as a tenure-track assistant professor in the Fall. Ever grateful to my mentors, friends & family for their advice, support & encouragement through the years!

I welcome PhD applications from students interested in working with me on topics at the intersection of Artificial Intelligence and Causal Inference. Application deadline: 15th Dec 2021. Link: gradschool.oregonstate.edu/programs/3075/…

Ah! the long-awaited book is here!🥳🥳 For a gentle introduction to missing data from a causal perspective, see my chapter, dl.acm.org/doi/10.1145/35…

Hear Hear 📢📢📢 Excited to announce the First EPFL Causality Workshop, sponsored by the EPFL School of Engineering #epflSTI. First Speaker is Prof. Aapo Hyvärinen, on 'Causal discovery based on latent variable models'. More Info & (free) Registration👉causality2022.epfl.ch

Is it safe to assume IID when you know that data are not IID? What conditions contribute to bias when estimating causal effects? How can we remove bias due to interference? Answers to these and more are discussed in our paper!

Congratulations to Dr. Chi Zhang (Chi Zhang) on defending her PhD thesis! Her work on interference pushes research boundaries and highlights the perils of blindly assuming IID. Well done, Dr. Zhang! It's been a delightful journey collaborating with you. 🥳🎉🍾 Judea Pearl @oacarah

Remember PO's slogan "causal inference is a missing-data problem"? Well, here Karthika Mohan shows the opposite: "missing-data is a causal problem": ucla.in/3sxeqOW. Her gentle introduction through simple and meaningful examples should convince everyone, including the

Enjoying every page of this book! Delighted by the dedicated chapter on causality, thrilled with the missing data section, and grateful for the shoutout to my work with Judea Pearl . A must-read for AI students. linkedin.com/posts/alan-mac…

I discussed the application of Operations Research methods to the challenge of Causal Discovery with Imperfect Data at the Computing Community Consortium (CCC) AI/OR Workshop in Washington DC. Grateful for the opportunity and huge thanks to the fantastic organizers!

We invite submissions of extended abstracts, up to 2 pages in length, to the UAI Causal Inference Workshop.

New preprint: Do Finetti w/Chi Zhang, Karthika Mohan, Ferenc Huszár, Bernhard Schölkopf and me. arxiv.org/abs/2405.18836 Do Finetti provides a do-calculus foundation for exchangeable data following the independent causal mechanism (ICM) principle + a causal Pólya urn model to show how

Challenging the IID assumption is key to advancing AI/ML, as real-world data often violates IID. We are excited to present our paper that explores this frontier.

Honored to speak on causality at #IBC2024 in Atlanta! 🎉 Humbled to hear my work on missing data has helped improve outcomes for children. 🙏✨ Huge shout-out to the researchers at Murdoch Children's Research Institute! 👏🌟 Judea Pearl Margarita Moreno-Betancur Jiaxin Zhang @ghazalehdashti

🚀 Excited to be at AAAI! 🚀 Join me on Tuesday, 25th Feb to explore the fascinating ways causality brings clarity to messy datasets. See you in Philadelphia! 👋#AAAI2025 #CausalDataScience #MissingData #noniidData