Andis Draguns
Bio
Andis Draguns is a machine learning researcher and Principal Researcher at Contramont Research, a 501(c)(3) nonprofit AI safety research lab. He is also an MS student at the University of Latvia's Institute of Mathematics and Computer Science (IMCS UL) and a MATS alumnus. His research focuses on AI security and alignment, particularly adversarial robustness, cryptographic backdoors in language models, and mechanistic anomaly detection. He co-authored the NeurIPS 2024 paper "Unelicitable Backdoors in Language Models via Cryptographic Transformer Circuits," which introduced a novel class of backdoors that defenders cannot trigger even with full white-box access. He received LTFF funding for a project on finding and characterising provably hard cases for mechanistic anomaly detection, a technique aimed at flagging when AI systems produce outputs for anomalous internal reasons.
Links
- Personal Website
- https://www.draguns.me/
- Twitter / X
- LessWrong
- -
Grants
from Long-Term Future Fund
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Details
- Last Updated
- Mar 22, 2026, 2:16 PM UTC
- Created
- Mar 20, 2026, 2:47 AM UTC