assistant prof at USC Data Sciences and Operations and Computer Science; phd Cornell ORIE.
data-driven decision-making, operations research/management, causal inference, algorithmic fairness/equity
bureaucratic justice warrior
angelamzhou.github.io
angela zhou
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has anyone written about the inherent optimism in scaling up pilots to larger-scale implementations? DM's policy is not risk-averse for beneficial social interventions that aren't expected to cause harm (but may be noisy zeroes), but risk-seeking/optimistic
I'm giving some talks in June! Please hit me up if we overlap :)
June 12 - SIGMETRICS causal workshop sites.google.com/view/causal-...
June 19 - INI Causality & Machine Learning workshop
almost last :') but not least :') Around 6/15-25
June 26 - FAccT Tutorial programs.sigchi.org/facct/2026/p...
Best thing about Mamdani is that he's one of the only Democrats who understands you can just do things
obviously i don't have any good way to implement this, but
i don't think we should waste real expert reviewer's time reviewing mediocre AI-written papers and having real expert reviewer provide valuable feedback that, presumably, will just get sent to LLMs to complete. at that point the reviewers might as well be authoring along with the authors
I regret to inform you that Claude Fable is very good at writing technical tutorials.
Here are 10 notebooks in both Python and R using @bsky.app @atproto.com to run common social data science tasks: search, SNA, replies, time series, NLP, images, LLMs, feeds, streams, and bots.
