MIRAGE-Persist
Studying how security failures persist across long-running, tool-using AI systems and how to evaluate them reliably.
Latest
🎉 Happy news! Our ERUF paper, Representation-Aware Unlearning via Activation Signatures: From Suppression to Entity-Signature Erasure, has been accepted to EMNLP 2026 Findings!
Continued the BlackboxNLP reproducibility task paper on attention-sink circuits and implementation sensitivity.
Began experimental work on new research directions in secure, long-horizon AI agents.
Joined Daffodil International University as Contractual Faculty.
Submitted my representation-aware machine unlearning work to ACL Rolling Review.
Completed my B.Sc. in CSE from BRAC University with a CGPA of 3.95/4.00.
Published GradG-AttnSleep at IEEE ICITEE.
Ongoing research
Studying how security failures persist across long-running, tool-using AI systems and how to evaluate them reliably.
Representation-aware diagnostics and interventions for injected or manipulated objectives in AI agents.
Reproducing and stress-testing proposed mechanisms behind attention sinks across implementations and settings.
Testing whether compact activation-level interventions can improve reliability in compressed language models.
Investigating internal signals for detecting and mitigating compromised behavior in mixture-of-experts models.
Building interpretable sleep-staging systems that remain dependable across datasets, recordings, and subjects.
Research outputs
Dual-mode visual explanations for attention-based sleep-stage classification.
A reproduction and reliability analysis of a proposed GPT-2 attention-sink circuit.
An AI-assisted workspace for exploring, summarizing, and connecting research literature.
Live project ↗A local-first research companion for structured paper analysis and scholarly debate.
GitHub ↗Academic experience
Teaching computer science with an emphasis on conceptual clarity, real-world examples, and accessible technical communication.
Supported Data Structures and Electronic Devices courses through laboratory teaching, grading, assessment, and student mentoring.
I am open to research discussions and academic collaboration in trustworthy AI, LLM safety, interpretability, and AI for health.
syed.naveed.mahmood@g.bracu.ac.bd