AI prof/Endowed Chair @JohnsHopkins, Foundr @BayesianHealth, investor 15+ AI startups, ex-Stanford AI, MIT TR35, Sloan, @wef YGL, @darpa AI safety & Health AI
Manhattan, NY
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- Followers 15,039
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So incredibly proud.
The opportunity for AI to improve health outcomes is massive. But what’s been missing is rigorous peer-reviewed studies showing AI used in practice. Today we published 3 studies in Nature Medicine that show for the first time ever how AI saves lives.
bayesianhealth.com/sepsis-re…
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Fun for @AndrewLBeam and me to get a chance to chat with @suchisaria today for @NEJM_AI Grand Rounds!
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In @HealthcareBrew: “Ultimately, we can only produce outcomes when clinicians trust the system and act on it,” says @bayesianhealth founder @suchisaria. “You can think of the @US_FDA as a very meaningful and critical level for building trust.” healthcare-brew.com/stories/…
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An #AI system developed by John C. Malone Associate Professor of Computer Science @suchisaria detects deadly infections faster than doctors, saving thousands from sepsis—a condition that claims more than 250,000 lives each year in the U.S. malonecenter.jhu.edu/fda-app…
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“Once a clinician already suspects sepsis, the clock has been running—often for hours or even days,” says lead researcher and John C. Malone Associate Professor of Computer Science @suchisaria. “No other cleared test or device monitors for sepsis prior to clinician suspicion.”
The @US_FDA has approved an AI-powered early warning system developed by Johns Hopkins researchers that can detect sepsis before clinicians may even suspect it. hub.jhu.edu/2026/05/12/fda-a… #ResearchSavesLives
ALT An image with white text on a dark blue background. The Research Saves Lives logo is at the top left.
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SPOT💡: In “Conformal Policy Control,” @DrewPrinster, @anqi_liu33, @suchisaria, @clara_fannjiang, @jiwoncpark, @kchonyc, & @samuel_stanton_ show how to use any safe reference policy as a probabilistic regulator 4 any optimized but untested policy: arxiv.org/abs/2603.02196 (14/25)
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WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales (arxiv.org/abs/2505.04608), w/ @xinghan0, @anqi_liu33, @suchisaria:
- Sat (7/11, Room 318) ICML Workshop on Hypothesis Testing
(3/6)
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“Improving Coverage in Combined Prediction Sets with Weighted p-values” by @DrewPrinster, @suchisaria, @ChellappaProf, @anqi_liu33, & more proposes a framework for the weighted aggregation of prediction sets w/ weights assigned based on contribution: arxiv.org/abs/2505.11785 (6/7)
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Can we ensure AI agents respect our safety constraints, even as they explore & improve?
- Medical LLMs that are helpful, & avoid false claims?
- Bioscience agents that generate effective molecule designs, & ensure they’re safe?
📄🧵w/ @samuel_stanton_ @clara_fannjiang @jiwoncpark @kchonyc @anqi_liu33 @suchisaria
Excited to share “Conformal Policy Control” ⬇️
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Running a company:
2020: can you survive a pandemic?
2021: still here? we’re going to give all of your competitors $100m series A rounds.
2022: wow, you made it? okay, all engineers cost $600,000/year now.
2023: nice job! okay, SVB failed and we’re going to take away your bank account.
2024: a survivor I see. but can you pivot from ai to crypto to defense tech back to ai-enabled defense tech in a 12 month period to stay relevant?
2025: unfortunately all of your competitors have raised $2b series B rounds. oh and only 500 engineers are relevant and they cost $100m/yr each.
2026: well, well, well. you’re still in business? let’s deploy the thunderclap of godlike LLMs from the heavens so all of your customers can rebuild your app in 2 hours. can you survive?
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As #AI transforms nearly every sector, @suchisaria outlines guiding principles in @NatureMedicine for AI’s use in medical care so that it can truly benefit physicians and patients.
Clinical AI doesn’t need better AUC. It needs better evaluation design.
Benchmarks ≠ bedside readiness. Better evaluation will build clinician trust.
New perspective in @NatureMedicine w/ @suchisaria & @hmkyale
Link: rdcu.be/e0IkI
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I’m in Chicago for work and realizing I have extra time open this evening! What should I do? Curious to hear ideas.
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Could #AI help predict #sepsis? At 2:30pm join @DrMarcSiegel as he speaks with @suchisaria (AI prof/Endowed Chair @JohnsHopkins & Founder @BayesianHealth) and @withyouDrWu (Professor, director of CHSOR @JohnsHopkinsSPH) about their research. Stream here: sxm.app.link/DoctorRadio
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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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🚨With an awesome group of collaborators from health system & federal agencies, @Jean_J_Feng and I are embarking on an ambitious multi-year project to develop tools for monitoring & updating clinical AI algorithms, with the aim of informing how we accelerate & scale responsible AI deployment. More details here jeanfeng.com/joining Looking postdocs, data scientists and senior research fellow applications. Apply!
Thanks for RT.
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Awesome highlights of the important research being done by @MathiasUnberath and @suchisaria! #ResearchSavesLives
From diagnosing infections with a smartphone to training surgical robots, Johns Hopkins researchers are using AI to create real-world impact. hub.jhu.edu/research-saves-l…
ALT A white background with blue text overlay. At the top is the "Research Saves Lives" banner and an image of a phone and healthcare provider.
ALT A white background with blue text overlay. At the top is the "Research Saves Lives" banner and an image of a robotic arm.
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ALT A white background with blue text overlay. At the top is the "Research Saves Lives" banner and an image of a blue car and crash dummies.
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Hopkins Engineering faculty Rama Chellappa, @suchisaria, and Axel Krieger talk AI healthcare with @ScienceNews!
AI could transform health care, but the stakes are high. sciencenews.org/article/ai-h…
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When do AI explanations actually help, & promote appropriate trust?
Spoiler, via prospective, multisite @radiology_rsna study of 220 doctors: *How* AI explains its advice has big impacts on doctors’ diagnostic performance and trust in AI--even if they *don’t realize it*!
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