📢 Just announced! Join us for the #KempnerInstitute workshop “Learning Dynamics in Natural and Artificial Intelligence: Evolution, Adaptation, and the Foundations of Efficient Learning.” Learn more, register, or submit an abstract 👉 bit.ly/3QwJlHR

Tremendously excited to announce that I will be joining @rockefeller.edu as an Assistant Professor and Head of Lab starting in January 2027! My group will be broadly focused on theoretical neuroscience, and mathematical problems in neural computation in the large.

Congratulations, Jacob! We’ve been extremely lucky to have you at Harvard. Can’t wait to see the exciting science that comes out of your lab.

New blog post: Jailbreak Scaling Laws for #LLMs Prompt-injection attacks can boost jailbreak success from slow polynomial to exponential growth as inference-time samples increase. New on the Deeper Learning blog: bit.ly/4eK3ZfC #AI @cpehlevan.bsky.social

New preprint: "Linear equivalence of nonlinear recurrent neural networks." For large nonlinear (potentially chaotic) RNNs with random connectivity, the full N×N covariance matrix takes the same form as that of a ~linear~ network with the same couplings, driven by independent noise.

🚀 Starting Day 1 of #ICLR2026 with an exciting lineup of presentations from researchers at the #KempnerInstitute! Take a look at the full list of today’s Kempner talks 👇 @iclr-conf.bsky.social #AI #NeuroAI @satpreetsingh.bsky.social @kanakarajanphd.bsky.social @annhuang42.bsky.social

🧠👃A new study by #KempnerInstitute associate faculty member Venkatesh Murthy & collaborators shows that maximizing information recreates an olfactory design shared by multiple species. Out now in @pnas.org: bit.ly/4uQ6Omw @neurovenki.bsky.social @jzv.bsky.social #neuroscience

NEW: #Kempner researchers develop a mean-field theory of task-trained RNNs that bridges random and learned connectivity—and find macaque motor cortex is best captured by an intermediate, task-specific recurrent structure. Read the blog post 👇 🔗 bit.ly/47f3Ldl

I am totally pumped about this new work . "Task-trained RNNs" are a powerful and influential framework in neuroscience, but have lacked a firm theoretical footing. This work provides one, and makes direct contact with the classical theory of random RNNs: www.biorxiv.org/content/10.6...

Looking forward to presenting on "How behavior shapes recurrent circuits across sensory systems and species: from vision to touch" at the University of Chicago Neuroscience and ML workshop on Wednesday! Details below 👇🧵

I’m deeply thankful to my supervisor, Mark Brandon (@markbrandonlab.bsky.social) for his patience, guidance, and constant support throughout this project, and to our collaborators in the Cengiz Pehlevan (@cpehlevan.bsky.social) lab at Harvard for their thoughtful and generous contributions.

All theory is wrong until verified by data. Greatly indebted to @mhyaghoubi.bsky.social, @markbrandonlab.bsky.social, @douglasresearch.bsky.social for finding the hippocampus encoding reward prediction! Grateful to my advisor @cpehlevan.bsky.social, @kempnerinstitute.bsky.social. #RL #hippocampus

Delighted to have contributed to this work. Huge kudos to everyone involved.

I’m very happy to share the latest from my lab published in @Nature Hippocampal neurons that initially encode reward shift their tuning over the course of days to precede or predict reward. Full text here: rdcu.be/eY5nh

Very excited about this new work from the omnipotent Owen, with me and Ashok Litwin-Kumar! Can we reconcile low- and high-dimensional activity in neural circuits by recognizing that these circuits ~multitask~? (Plausibly, yes 😊)

Congratulations to #KempnerInstitute community members @msalbergo.bsky.social and @mweber.bsky.social — recipients of @schmidtsciences.bsky.social AI2050 Fellowships! 🎉 Discover their innovative research shaping the future of AI 👉 bit.ly/47Do4R3 #AI

First paper from the lab! We propose a model that separates estimation of odor concentration and presence and map it on olfactory bulb circuits Led by @chenjiang01.bsky.social and @mattyizhenghe.bsky.social joint work with @jzv.bsky.social and with @neurovenki.bsky.social @cpehlevan.bsky.social

Now in PRX: Theory linking connectivity structure to collective activity in nonlinear RNNs! For neuro fans: conn. structure can be invisible in single neurons but shape pop. activity For low-rank RNN fans: a theory of rank=O(N) For physics fans: fluctuations around DMFT saddle⇒dimension of activity

Applying to do a postdoc or PhD in theoretical ML or neuroscience this year? Consider joining my group (starting next Fall) at UT Austin! POD Postdoc: oden.utexas.edu/programs-and... CSEM PhD: oden.utexas.edu/academics/pr...

William Qian, Cengiz Pehlevan: Discovering alternative solutions beyond the simplicity bias in recurrent neural networks https://arxiv.org/abs/2509.21504 https://arxiv.org/pdf/2509.21504 https://arxiv.org/html/2509.21504

⏳ Less than 1 day left until the Brain & Mind Workshop submission deadline! 🔍 Submit to our Finding or Tutorials track on OpenReview. Findings track submission: openreview.net/group?id=Neu... Tutorial track submission: openreview.net/group?id=Neu... More info: data-brain-mind.github.io

Since I'm back on BlueSky - with @frostedblakess.bsky.social and @cpehlevan.bsky.social we wrote a brief perspective on how ideas about summary statistics from the statistical physics of learning could potentially help inform neural data analysis... (1/2)

Excited to share new computational work, led by @jzv.bsky.social, driven by Juan Carlos Fernandez del Castillo + contribution from Farhad Pashakanloo. We recover 3 core motifs in the olfactory system of evolutionarily distant animals using a biophysically-grounded model + efficient coding ideas!

Great to have this video about my @darpa.mil Artificial Intelligence Quantified (AIQ) program out! Very exciting program with absolutely fantastic teams. Stay tuned for some jaw dropping announcements! www.youtube.com/watch?v=KVRF...

I am extremely grateful to be awarded the National University of Singapore (NUS) Development Grant, and to be a Young NUS Fellow! Look forward to collaborating with the Yong Loo Lin School of Medicine on exciting projects. This is my first grant and hopefully many more to come! #NUS #NeuroAI

Our new Simons Collaboration on the Physics of Learning and Neural Computation will develop powerful tools from #physics, #math, computer science and theoretical #neuroscience to understand how large neural networks learn, compute, scale, reason and imagine: www.simonsfoundation.org/2025/08/18/s...

If you work on artificial or natural intelligence and are finishing your PhD, consider applying for a Kempner research fellowship at Harvard: kempnerinstitute.harvard.edu/kempner-inst...

Congratulations to #KempnerInstitute associate faculty member @cpehlevan.bsky.social for joining the new @simonsfoundation.org Simons Collaboration on the Physics of Learning and Neural Computation! www.simonsfoundation.org/2025/08/18/s... #AI #neuroscience #NeuroAI #physics #ANNs

Very excited to lead this new @simonsfoundation.org collaboration on the physics of learning and neural computation to develop powerful tools from physics, math, CS, stats, neuro and more to elucidate the scientific principles underlying AI. See our website for more: www.physicsoflearning.org

🚨 Excited to announce our #NeurIPS2025 Workshop: Data on the Brain & Mind 📣 Call for: Findings (4- or 8-page) + Tutorials tracks 🎙️ Speakers include @dyamins.bsky.social @lauragwilliams.bsky.social @cpehlevan.bsky.social 🌐 Learn more: data-brain-mind.github.io

The post is based on a paper written with Yue M. Lu., @jzv.bsky.social, Anindita Maiti and @cpehlevan.bsky.social evan. Check it out now at PNAS: doi.org/10.1073/pnas... (2/2)

New in the #DeeperLearningBlog: the #KempnerInstitute's Mary Letey presents work recently published in PNAS that offers generalizable insights into in-context learning (ICL) in an analytically-solvable model architecture. bit.ly/4lPK15p #AI @pnas.org (1/2)

At #ICML2025, presenting work done at @flatironinstitute.org w Matt Smart and @albertobietti.bsky.social on in-context denoising (arxiv.org/abs/2502.05164). Come to Matt’s oral, Thursday, 4:15-4:30 PM, West Ballroom A, and see us right after at poster #E-3207, 4:30-7:00 PM, East Exhibition Hall A-B.

Great to see this one finally out in PNAS! Asymptotic theory of in-context learning by linear attention www.pnas.org/doi/10.1073/... Many thanks to my amazing co-authors Yue Lu, Mary Letey, Jacob Zavatone-Veth @jzv.bsky.social and Anindita Maiti!

#eNeuro: Obeid and Miller identify distinct neural computations in the primary visual cortex that explain how surrounding context suppresses perception of visual figures and features. ‪@harvardseas.bsky.social‬ vist.ly/3n6tfb2

📣 Grad students and postdocs in computational and theoretical neuroscience: please consider applying for the 2025 Flatiron Institute Junior Theoretical Neuroscience Workshop! All expenses are covered. Apply by April 14. jtnworkshop2025.flatironinstitute.org

New preprint! We trained an RNN using RL to solve a decision making task used to characterize suboptimal decision making by Schizophrenic patients. First project exploring comp psych models, thanks to @adam-manoogian.bsky.social @shawnrhoadsphd.bsky.social @bqian.bsky.social @cpehlevan.bsky.social

Honoured to have been selected as a #SloanFellow Thankful for all the support from family, mentors, collaborators, colleagues and students along the way! @sloanfoundation.bsky.social

(1/30) New preprint! "Symmetries and continuous attractors in disordered neural circuits" with Larry Abbott and Haim Sompolinsky bioRxiv: www.biorxiv.org/content/10.1...

Theory in neuroscience, you say? How about this preprint by @david-g-clark.bsky.social, with a couple of others you might recognize? :-) #neuroscience

Our preprint with @frostedblakess.bsky.social, @jzv.bsky.social, @cpehlevan.bsky.social is out! We develop a simple reinforcement learning model that recapitulates 3 disparate hippocampal dynamics. With ablation studies, these representations improve the speed and flexibility of policy learning.

The official ad for this postdoc position is now (finally) live, see academicpositions.harvard.edu/postings/14486!

Come by at Neurips to hear Hamza present about properties of various feature learning infinite parameter limits of transformer models. Poster in Hall A-C #4804 at 11 AM PST Paper arxiv.org/abs/2405.15712 , code github.com/Pehlevan-Gro... Work with Hamza Chaudhry and @cpehlevan.bsky.social

Excited to share my #NeurIPS2024 paper with @jzv.bsky.social, @BenjaminSRuben, and @cpehlevan.bsky.social on mechanistic mismatches in data-constrained models of neural dynamics! (1/n)

(1/5) Fun fact: Several classic results in the stat. mech. of learning can be derived in a couple lines of simple algebra! In this paper with Haim Sompolinsky, we simplify and unify derivations for high-dimensional convex learning problems using a bipartite cavity method. arxiv.org/abs/2412.01110

NEW: we have an exciting opportunity for a tenure-track professor at the #KempnerInstitute and the John A. Paulson School of Engineering and Applied Sciences (SEAS). Read the full description & apply today: academicpositions.harvard.edu/postings/14362 #ML #AI

Glad to share this theory paper on learning to align neural representations with sparse connectivity. Work led by graduate student @leo-bo-liu.bsky.social, in a wonderful collaboration with Yuhai Tu from IBM Research and @shanq.bsky.social from Flatiron Institute. #neuroscience 🧪

We recently found that odor information across the 2 cortical hemispheres is highly coordinated despite the distributed & fragmented sensory representations. Can this alignment arise from biological realistic, continual, correlation-based synaptic plasticity & sparse inter-hemispheric connections?

Some evidence for grokking in piriform cortex: arxiv.org/abs/2411.03541 joint effort from Tanishq Kumar, Blake Bordelon, @neurovenki.bsky.social, @cpehlevan.bsky.social.