🧠⚙️ Interested in decision theory+cogsci meets AI? Want to create methods for rigorously designing & evaluating human-AI workflows? I'm recruiting PhDs to work on: 🎯 Stat foundations of multi-agent collaboration 🌫️ Model uncertainty & meta-cognition 🔎 Interpretability 💬 LLMs in behavioral science

I’m recruiting students this upcoming cycle at UIUC! I’m excited about Qs on societal impact of AI, especially human-AI collaboration, multi-agent interactions, incentives in data sharing, and AI policy/regulation (all from both a theoretical and applied lens). Apply through CS & select my name!

if you think about AI, healthcare, women's health, or all of the above, i highly recommend this article on the role of fetal heart rate monitors in the rise of C-sections: www.nytimes.com/2025/11/06/h...

Super cool, and something I wish existed within machine learning for healthcare too! I'm often wondering what people are actually doing in practice and assembling evidence for my guesses.

Cornell (NYC and Ithaca) is recruiting AI postdocs, apply by Nov 20, 2025! If you're interested in working with me on technical approaches to responsible AI (e.g., personalization, fairness), please email me. academicjobsonline.org/ajo/jobs/30971

@michelleding.bsky.social has been doing amazing work laying out the complex landscape of "deepfake porn" and distilling the unique challenges in governing it. We hope this work informs future AI governance efforts to address the severe harms of this content - reach out to us to chat more!

New #NeurIPS2025 paper: how should we evaluate machine learning models without a large, labeled dataset? We introduce Semi-Supervised Model Evaluation (SSME), which uses labeled and unlabeled data to estimate performance! We find SSME is far more accurate than standard methods.

I am on the job market this year! My research advances methods for reliable machine learning from real-world data, with a focus on healthcare. Happy to chat if this is of interest to you or your department/team.

Are you a researcher using computational methods to understand cities? @mfranchi.bsky.social @jennahgosciak.bsky.social and I organize an EAAMO Bridges working group on Urban Data Science and we are looking for new members! Fill the interest form on our page: urban-data-science-eaamo.github.io

can't recommend highly enough!

Excited to be at #ICML2025 to present our paper on 'pragmatic misalignment' in (deployed!) RAG systems: narrowly "accurate" responses that can be profoundly misinterpreted by readers. It's especially dangerous for consequential domains like medicine! arxiv.org/pdf/2502.14898

I'll be presenting a position paper about consumer protection and AI in the US at ICML. I have a surprisingly optimistic take: our legal structures are stronger than I anticipated when I went to work on this issue in Congress. Is everything broken rn? Yes. Will it stay broken? That's on us.

🎉Excited to present our paper tomorrow at @facct.bsky.social, “Characterizing Bias: Benchmarking Large Language Models in Simplified versus Traditional Chinese”, with @brucelyu17.bsky.social, Jiebo Luo and Jian Kang, revealing 🤖 LLM performance disparities. 📄 Link: arxiv.org/abs/2505.22645

🖋️ Curious how writing differs across (research) cultures? 🚩 Tired of “cultural” evals that don't consult people? We engaged with interdisciplinary researchers to identify & measure ✨cultural norms✨in scientific writing, and show that❗LLMs flatten them❗ 📜 arxiv.org/abs/2506.00784 [1/11]

and... here is the actual GIF 🙈

New work 🎉: conformal classifiers return sets of classes for each example, with a probabilistic guarantee the true class is included. But these sets can be too large to be useful. In our #CVPR2025 paper, we propose a method to make them more compact without sacrificing coverage.

I’m in Nashville this week for #CVPR2025! DM me to chat about conformal prediction, test-time adaptation, or model reliability. Excited to see new work and to catch up with friends old and new!!

Please help us spread the word! 📣 FATE is hiring a pre-doc research assistant! We're looking for candidates who will have completed their bachelor's degree (or equivalent) by summer 2025 and want to advance their research skills before applying to PhD programs.

I really enjoyed (and learned a LOT from) working on this project with these wonderful co-authors: @dmshanmugam.bsky.social Ashley Beecy Gabriel Sayer @destrin.bsky.social @nkgarg.bsky.social @emmapierson.bsky.social 7/7

Erica’s new paper on a method to both measure *and* correct for three types of disparities associated with disease progression is now out! Check out the thread for more detail + findings from a case study on heart failure. Congratulations!!!

my friend jonah made a fun game that i now play everyday: guessten.com! please enjoy and send me your scores

just used this to source citations with great success - a very nice tool!!

kenny had the great idea to spend a whole day analyzing dogs — so so fun! i like health data but turns out i love dog data

Migration data lets us study responses to environmental disasters, social change patterns, policy impacts, etc. But public data is too coarse, obscuring these important phenomena! We build MIGRATE: a dataset of yearly flows between 47 billion pairs of US Census Block Groups. 1/5

💡New preprint & Python package: We use sparse autoencoders to generate hypotheses from large text datasets. Our method, HypotheSAEs, produces interpretable text features that predict a target variable, e.g. features in news headlines that predict engagement. 🧵1/

(1/n) New paper/code! Sparse Autoencoders for Hypothesis Generation HypotheSAEs generates interpretable features of text data that predict a target variable: What features predict clicks from headlines / party from congressional speech / rating from Yelp review? arxiv.org/abs/2502.04382

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Our article on using LLMs to promote health equity is out in New England Journal of Medicine AI! 85% of equity-related LLM papers focus on *harms*. But also vital are the equity-related *opportunities* LLMs create: detecting bias, extracting structured data, and improving access to health info.

We have a new review on generative AI in medicine, to appear in the Annual Review of Biomedical Data Science! We cover over 250 papers in the recent literature to provide an updated overview of use cases and challenges for generative AI in medicine.