Nice piece Yao. It’s great seeing folks write about Jamie Robins’ work. I took a course with Jamie just on G-methods in grad school. Really brilliant and unique guy. Admittedly, Miguel Hernan had to “translate” a lot of what Jamie was talking about most of the semester.

For some reason, I have found Jamie often gets left out of the conversation when folks discuss the juggernauts in the Causal Inference space. A lot of things that were independently rediscovered in the late 80’s and early 90’s by other folks (like Pearl) were actually already in Jamie 1986 paper. A running joke at school was that most everything published in the late 80s, 90s, and even early 2000’s on Causal Inference was already in Jamie’s 1986 paper, but few knew because few had read the whole thing due to the length and difficulty. His paper is ~120 pages long!

Chief Data Scientist & Head of AI @ AIMatters | Harvard trained Statistician and Machine Learning Scientist | Interests in Statistical ML & Causal Inference

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