Drew Prinster

225 posts

Drew Prinster

Drew Prinster

@DrewPrinster

Trustworthy AI/ML in healthcare & high-stakes apps | My job is (mostly) error bars 🫡 (eg, conformal prediction) | CS PhD at Johns Hopkins. Prev at Yale. he/him

Bergabung Aralık 2019
378 Mengikuti344 Pengikut
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Neha Verma
Neha Verma@n_verma1·
Introducing "DOTResize: Reducing LLM Width via Discrete Optimal Transport-based Neuron Merging" ! We introduce an optimal transport framework for Transformer width compression that redistributes signal across neurons rather than eliminating them 🚚⚖️ 🧵 1/6
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Clara Fannjiang
Clara Fannjiang@clara_fannjiang·
we're hiring a Ph.D. intern! join us @genentech in South San Francisco for a summer advancing ML & statistical approaches for clinical trial design & analysis 📉💊DMs are open, feel free to reach out! 🔗tinyurl.com/yc3hfndp
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Shuvom Sadhuka
Shuvom Sadhuka@shuvom_s·
How can you evaluate agent trajectories with only black-box access to a verifier and the agent? Introducing E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testing ❌no finetuning ❌no additional GPU compute ⬛black-box access ✔️controllable error rates w/ guarantees Thread below:
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Ji Won Park
Ji Won Park@jiwoncpark·
Interested in uncertainties for LLMs? Come chat with me at poster #815 tomorrow (Thu) 11a-2p! Joint work with @kchonyc on tilting the sampling distribution toward semantic diversity for ARMs or DLMs, for efficient UQ. Also ask me about PhD internships! neurips.cc/virtual/2025/l…
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jenny huang
jenny huang@JennyHuang99·
super honored to receive the Amazon AI Fellowship to support my work at MIT ~ more great projects + collaborations ahead ☺!
Rohit Prasad@RohitPrasadAI

Excited to announce @amazon's new AI PhD Fellowship Program supporting 100+ students across 9 universities like Carnegie Mellon, MIT & Stanford. Fellows will be paired with senior scientists working in related fields, plus receive financial support and AWS credits for research. Learn more: amazon.science/news/amazon-la…

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Nathan C. Frey
Nathan C. Frey@nc_frey·
After three exciting years @PrescientDesign @genentech, last Friday was my last day. It has been an amazing journey, with an incredible team, and I know there is much more to come from this stellar group of researchers. I am immensely grateful to my team, our collaborators, and to @stephenrra & @GligorijevicV for their mentorship and support over the years. Onto the next adventure!
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Kuan-Hao Chao
Kuan-Hao Chao@KuanHaoChao·
I’m thrilled to share that I successfully defended my PhD in @JHUCompSci at @JohnsHopkins yesterday (Aug 25). This milestone isn’t mine alone—it belongs to everyone who believed in me, challenged me, and made the hard days lighter. Immense thanks to my advisors, @StevenSalzberg1 and @elapertea; my committee—Ben Langmead, @drklly and @anqi_liu33; and all labmates, collaborators, and mentors. It’s you who made me who I am today. What’s next: I’m joining the @illumina AI Lab as a Senior Deep Learning Scientist. Grateful and excited—let’s stay connected!
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Ji Won Park
Ji Won Park@jiwoncpark·
🚨 We’re hiring at Frontier Research @PrescientDesign @genentech! Work on statistical ML for drug discovery: - Bayesian inference & decision theory - Uncertainty quantification - Multi-objective optimization DMs open, feel free to reach out directly! 🔗 tinyurl.com/4bm5st9v
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Drew Prinster
Drew Prinster@DrewPrinster·
@xinghan0 @anqi_liu33 @suchisaria Would love to chat with people thinking about AI safety monitoring, reliability, sequential testing, regulation, conformal prediction, & more, feel free to reach out! :)
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Drew Prinster
Drew Prinster@DrewPrinster·
Where's Waldo? 🧐 Maybe you'll find him on our poster, but you can definitely find me at #ICML2025! - Invited Talk: Tue (7/15) Multi-Agent Systems in Ambient Settings Social (~7:45pm) - Poster: Thu (7/17) morning (11-1:30pm), East Exhibit Hall, E-1912 icml.cc/virtual/2025/p…
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Drew Prinster@DrewPrinster

AI monitoring is key to responsible deployment. Our #ICML2025 paper develops approaches for 3 main goals: 1) *Adapting* to mild data shifts 2) *Quickly Detecting* harmful shifts 3) *Diagnosing* cause of degradation 🧵w/ @xinghan0 @anqi_liu33 @suchisaria arxiv.org/abs/2505.04608

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Beepul Bharti
Beepul Bharti@BeepulBharti·
I’m at #ICML2025 this week presenting my work on multiaccuracy and multicalibration with proxy sensitive attributes. If you are interested, please come by poster E-1101 on Tuesday at 4:30 pm PST to learn more! @Jere_je_je @PaulYiMD icml.cc/virtual/2025/p…
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Anqi (Angie) Liu
Anqi (Angie) Liu@anqi_liu33·
I am not going to make this ICML but @DrewPrinster will be there! Check out our recent work on online AI monitoring under a non-stationary environment.
JHU Computer Science@JHUCompSci

& “WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales” by @DrewPrinster, @xinghan0, @anqi_liu33, & @suchisaria proposes a weighted generalization of conformal test martingales: arxiv.org/abs/2505.04608 (5/5)

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Murat Kocaoglu
Murat Kocaoglu@murat_kocaoglu_·
I am pleased to announce that I will be joining Johns Hopkins University's Computer Science Department @JHUCompSci as an Assistant Professor in Fall 2025. I am grateful to my mentors for their unwavering support and to my exceptional PhD students for advancing our lab's vision.
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Timothy Snyder
Timothy Snyder@TimothyDSnyder·
Best read as a reasoned call to action, not a question. And we will need vivid terms for where we are going — oligarchy and fascism — as well as what we are seeking — freedom and equality. nytimes.com/2025/05/08/opi…
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Drew Prinster
Drew Prinster@DrewPrinster·
@unsorsodicorda @xinghan0 @anqi_liu33 @suchisaria A bit of both (tho more focused on online learning)! Ie, we run 2 test martingales in parallel: one doesn't depend on labels & triggers adaptation to shifts; second uses labels & is the alarm criteria. 'Think there's lot of cool extensions possible in forecasting setting! :)
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Drew Prinster
Drew Prinster@DrewPrinster·
@xinghan0 @anqi_liu33 @suchisaria WATCH opens up many opportunities for future work in AI safety monitoring: Eg, adaptive monitoring algorithms for other data-generating settings, extensions to monitoring generative models, LLMs, AI agents, and more! Stay tuned for updates, & reach out if want to chat! 7/
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Jaemin Cho
Jaemin Cho@jmin__cho·
Sharing some personal updates 🥳: - I've completed my PhD at @unccs! 🎓 - Starting Fall 2026, I'll be joining the Computer Science dept. at Johns Hopkins University (@JHUCompSci) as an Assistant Professor 💙 - Currently exploring options + finalizing the plan for my gap year (Aug 2025 - Jul 2026), so feel free to reach out! 🔎 Endless thanks to my amazing advisor @mohitban47, the @uncnlp group, my partner @HeesooJang2, and my family. I couldn’t have done this without your constant support 🙏 Also, a heartfelt shoutout to all the collaborators I’ve worked with over the years—your ideas, encouragement, and hustle have meant the world. Excited for what’s ahead. Let’s keep building together! ❤️
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Drew Prinster
Drew Prinster@DrewPrinster·
@predict_addict Love it. As you know, conformal prediction's also very useful for *detecting* black swan events, eg with conformal test martingales! In case of interest, we try to build on those capabilities for goal of monitoring deployed AI systems: x.com/DrewPrinster/s…
Drew Prinster@DrewPrinster

AI monitoring is key to responsible deployment. Our #ICML2025 paper develops approaches for 3 main goals: 1) *Adapting* to mild data shifts 2) *Quickly Detecting* harmful shifts 3) *Diagnosing* cause of degradation 🧵w/ @xinghan0 @anqi_liu33 @suchisaria arxiv.org/abs/2505.04608

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Jelajahi

@genentech @kchonyc @JennyHuang99 @nc_frey @GligorijevicV @KuanHaoChao @JHUCompSci @JohnsHopkins