Assistant Professor of Social Science at Hong Kong University of Science and Technology. Causal inference methodologist.
Joined January 2015
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Ang Yu retweeted
1/ How well can ML predict people's futures?
Our new paper examines the predictability of 484 outcomes. To our knowledge, the first high-throughput study of the predictability of life outcomes.
I worked on this during my time at Princeton @PrincetonCITP. A thread 🧵
Math is solved, so what? Running was “solved” by domesticating horses or whatever thousands of years ago, but today plenty of athletes and coaches still make a living from running. Spherical earth was also “solved” a long time ago, and there are still flat-earthers among us now..
It's that time of year again, and I got curious about how much economics Nobel laureates have dabbled in sociology. Turns out a lot of them used to publish a lot in sociology journals, but for some reason, they stopped....
ang-yu.github.io/posts/2026/…
Ang Yu retweeted
I refuse to believe that the most egregious case yet of academic AI-slop involves a guy whose last name is "No slop" spelled backwards. Simply cannot be true.
I think the classic Blade Runner monologue captures how a lot of people feel these days. All the moments we spent honing our technical skills have been lost in time, like tears in rain...
Craft, Curiosity, and Knowledge: Duncan Watts in Conversation with Philipp Brandt
sociologica.unibo.it/article…
I just realized I’ve always had an advantage: my anglicized (lol, no pun intended) name is both simple and distinctive, a rare combination for Chinese names 😂
Social Networks has a special issue on causal network analysis sciencedirect.com/special-is…
Ang Yu retweeted
A few months ago, a high profile paper in Science claimed to find that researchers' ideology produced biased results in favour of immigration.
A reanalysis of the data finds that result came from a coding error, which once corrected, shows no effect.
Will people who shared that original finding update their views?
osf.io/preprints/metaarxiv/4…
Later this week, I'm presenting "Explaining with Odds Ratios: Nonparametric Estimands and Estimators" at the Sociological Science Conference at Stanford University. Very excited to share this research for the first time!
I just found out that my paper with Felix Elwert, “Nonparametric Causal Decomposition of Group Disparities,” has received the Outstanding Publication Award from @AsaMethodology! It means so much to receive recognition from a community I identify with so strongly.
This paper is very cool for figuring out the nonparametric estimand behind the KHB estimator. journals.sagepub.com/doi/ful…
People often say that the linear probability model is bad, because it produces impossible fitted values, and logit is good because it doesn't. In this blog post, I explain why I think otherwise: ang-yu.github.io/posts/2026/…