Charalampos (Babis) Papamanthou

@chbpap

professor of computer science at @Yale | co-director of @YaleACL | chief scientist at @lagrangedev | researching and teaching cryptography and security

New Haven, CT cs.yale.edu/homes/cpap/ Joined May 2015

198 Following 1.5K Followers 799 Posts

Latest posts 5

Charalampos (Babis) Papamanthou @chbpap Oct 23

Continuing the work started at @lagrangedev, I am excited to announce a @Yale @Penn collaboration on a black-box compiler from static to dynamic SNARKs, yielding post-quantum dynamic SNARKs. Work led by amazing @BawejaAnubhav from @Penn! eprint.iacr.org/2026/2445

LAGRANGE @lagrangedev Oct 21

Tweak an AI model's weights and the proof of what it computed starts over from zero. @chbpap shows how dynamic zk-SNARKs update the proof when the model does.

View quoted post on X

Charalampos (Babis) Papamanthou @chbpap Oct 17

Impressive!

Yuval Efron @ElodinStorm Oct 17

Dolev–Strong is arguably the most well-known consensus protocol, yet in about 45 years no deterministic protocol improved on its O(n^3) communication.

With @komasito55 & Ling Ren, we get O(n^2 log^4 n) for Byzantine Broadcast, t<n faults, O(t) rounds:
eprint.iacr.org/2026/2504
View quoted post on X

Charalampos (Babis) Papamanthou @chbpap Sep 16

Our @YaleACL seminar this semester will mostly feature talks from distinguished colleagues on cryptography and AI. yacl.cs.yale.edu/seminar/

yacl.cs.yale.edu Seminar To be notified about future talks, register to our mailing list and calendar. To view past talks, check our YouTube. Interested in giving a talk? Reach out!

Charalampos (Babis) Papamanthou @chbpap Sep 3

1/ While preparing our CCS 2026 presentation for our DeepProve project at @lagrangedev, one application we have been thinking about is proving AI safety benchmarks without disclosing the model.

Charalampos (Babis) Papamanthou @chbpap Aug 20

This work led by @alrshirzad while interning at @lagrangedev has been accepted to TCC 2026! Congratulations!

Charalampos (Babis) Papamanthou @chbpap Aug 3

Most SNARKs encode computations into finite fields. Snarking integer arithmetic needed, for example, in ML and RSA, incurs a big overhead. Our new paper with the @lagrangedev research team builds SNARKs that work with integers natively---see our new paper eprint.iacr.org/2026/347!
View quoted post on X