Ehsan Adeli

Prof. at @Stanford @StanfordMed @StanfordPSY; @StanfordSVL; @StanfordAILab; @StanfordTAIL
AI, Computer Vision, Neuroscience, Healthcare, Medical Image Analysis.

[Ehsan Adeli @eadeli]

Patient activity in the hospital gets scattered across shifts, notes, and handoffs. Our recent work, TRACER, pulls it back together: a training-free harness that lets LLMs/VLMs track activity from bedside video + EHR. Harness and synthetic data are open. Led by @DuranteZane 👇

[Zane Durante @DuranteZane]

1/ Can AI help doctors make more informed decisions based on patient activity and behavior over the course of a hospital stay?

Today we introduce TRACER: a training-free multimodal harness that enables LLMs and VLMs to track patient activity using bedside video and health records.

Blogpost: https://t.co/f7Wy0tn3df

Paper: https://t.co/5qeoDjwM7y

[Ehsan Adeli @eadeli]

It feels like déjà vu to trade one homeland for another, only to end up in a kakistocracy!

[Ehsan Adeli @eadeli]

@karanps you are amazing!

[Ehsan Adeli @eadeli]

Do text-to-image models need language pretraining? We trained Halcyon from scratch on 100M image–text pairs with no LLM at all, and it beats LlamaGen & JiT-T2I using 18–275× less compute. Open weights, 0.1–4B, in recent work led by @keshigeyan; @__yuezhao__ @jcniebles @drfeifei.

[Keshigeyan Chandrasegaran @keshigeyan]

Excited to share Halcyon, our latest research on multimodal pretraining!

Building strong text-to-image generative models is simpler than we think!

Blog: https://t.co/HOrwIJIHTf
Models: https://t.co/xBPJkEAOPU
Paper: https://t.co/8kROIz1c7L

[Yaser Zhian @yaserzt]

Maybe I'm dense, but it only just occurred to me that this "AI revolution" is the only pure-software technology jump that I can think of.

Wheels, steam engine, cars, electricity, cinema and TV, computers, the internet, mobile phones, etc. were all enabled by new hardware.

[Ehsan Adeli @eadeli]

@malikatifsaleem Sure! As if no one can use them for malicious reasons!

[Ehsan Adeli @eadeli]

It is so funny how the tech industry spent 20 years building tests to prove you're not a bot. Now we're building AI agents to pass them for us to reserve a table online.

We're now engineering the exact thing we spent years engineering against. Same tech, opposite team.

[Karan Singh @karanps]

LLMs have tokens. Images have patches. What should the brain have? 🤔

HBAR, our hierarchical tokenizer for fMRI, was just accepted to NeurIPS 2026! 🎉

It compresses fMRI ~415× while preserving structure from voxels → parcels → functional networks.

[Puyin Li @PuyinLi]

💰 Announcing prizes for the QuantiPhy Challenge @ NeurIPS 2026!

🏆 $3,500 total cash prizes
Main Track
🥇 $1,000 · 🥈 $500 · 🥉 $250
Open-Weight Track
🥇 $1,000 · 🥈 $500 · 🥉 $250

⏰ Team registration: Oct 9, 23:59 AoE
⏰ Submission deadline: Oct 23, 23:59 AoE

[Tiange Xiang @xxtiange]

Today we announce 💰exciting prizes💰 for winners at the QuantiPhy Challenge @NeurIPSConf 2026.

Register your team before 9th Oct. and submit csv files before 23rd Oct. to join the NeurIPS competition and win the prize!!!

See more at: https://t.co/uoswGNz80n

[youngjoongkwon @youngjoongkwon]

Code for GenFusion: Feed-forward Human Performance Capture via Progressive Canonical Space Updates (ICLR 2026) is now public.

Like watching a dancer spin, it fuses each frame into a canonical space and renders novel views from what was actually seen.

https://t.co/YyaqX1HH54

[youngjoongkwon @youngjoongkwon]

Code, checkpoints, and full 4D-Dress test results are out for comparison.

Paper: https://t.co/2Sd7K6zgYB
Project: https://t.co/dFgWYYYWFL
Images: https://t.co/m5VaG89Yko
Videos: https://t.co/Amx8423ivU

w/ Yao He, Heejung Choi, @gengchen01 , Zhengmao Liu,@jiajunwu_cs , @eadeli

[Ehsan Adeli @eadeli]

@anshulkundaje Agreed 100%!

[Ehsan Adeli @eadeli]

@karanps That's similar to how humans learn; we don't just get bigger brains; we tackle progressively harder problems as our capabilities grow. A synchronized evolution between model architecture and training curriculum is likely to become a way for FM training or agent systems.
2/2

[Ehsan Adeli @eadeli]

One of the biggest shifts we're seeing in AI is moving beyond scaling data or scaling models in isolation toward co-evolving both together. @karanps's ICML2026 paper is a great example of that thinking: as a model matures, its learning environment should mature with it.
1/2

[Karan Singh @karanps]

Published at ICML 2026, with the final version and code now available!

Curriculum-Guided Layer Scaling for Language Model Pretraining

📄 Paper: https://t.co/KaqXQVuUQL

💻 Code: https://t.co/Jm7ATJD4Gr

With Neil Band (@neilbband) and Ehsan Adeli (@eadeli)

[Stanford Bio-X @StanfordBioX]

Week 6 of the Stanford Sapp Family CS Bio-X Undergraduate Summer Research Program included 3 more amazing faculty presentations! The cohort enjoyed this week's talks from Dr. Annelise Barron ( @annelise_b ), Dr. Martha Cyert ( @CyertMartha ) , and Dr. Ehsan Adeli ( @eadeli )!

[Stanford HAI @StanfordHAI]

📢 New issue brief: World models will reshape how AI interacts with the physical world. Our latest brief examines their emergence, opportunities, risks, and national security implications, and proposes a governance framework to guide policy conversations as the technology matures. https://t.co/vVgpjSHwHb

[Ehsan Adeli @eadeli]

Passionate about physical AI? Join our QuantiPhy Challenge!

[Tiange Xiang @xxtiange]

The QuantiPhy Challenge is now officially open!

Register your team at: https://t.co/ThGVfltWMz

Submit your results to win amazing prizes!!!

[AGI Summit @agisummitai]

🧠 Speaker Spotlight: Ehsan Adeli @eadeli

AI in medicine is moving beyond research papers and prototypes.

Ehsan Adeli is building translational AI systems that can move from the lab into real clinical care — combining medical AI, computer vision, ambient intelligence, and mental health research.

🔹 Director, STAI — Stanford Translational AI in Medicine & Mental Health @StanfordAILab
🔹 Co-Director, Stanford AI for Mental Health Initiative
🔹 Works across computer vision, ambient intelligence & computational neuroscience
🔹 Focused on real-world applications in aging, neurodegeneration, mental health & clinical care

As AI becomes part of healthcare, the question is not just what models can predict — it’s how they can support clinicians, patients, and care systems in the real world.

Hear Ehsan on stage at AGI Summit SF 2026.

📅 July 18–19, 2026
📍 Palace of Fine Arts, San Francisco
🎟 Tickets: https://t.co/Qdd1D2ahpA

🏷️ 15% off automatically applied through the link

#AGISummit #MedicalAI #HealthcareAI #MentalHealthAI #sanfrancisco

[Amir Zamir @zamir_ar]

Turns out it's possible to generate videos that maximally excite an arbitrary brain region using a simple search-based algorithm. It's a fully computational approach, so it's another way to speculate what a brain region represents, alongside other neuroscientific methods.

Select an arbitrary brain region->algorithmically generate a video that jacks it up. See the visuals on the webpage https://t.co/UzKyN8MHda

In silico (for now)