cat research.md
# i am interested in ai particularly in mechanistic interpretability and ai alignment.
$ ls active/
investigating how ai safety properties like alignment, robustness, interpretability degrade in low-resource and tonal language contexts.
bridging a decade of research, this review analyzes 70+ papers to identify the nine failure modes currently threatening AI safety.
addressing the challenge of LLM hallucinations in RAG systems, this paper explores simple, interpretable uncertainty signals for real-time detection.
by embedding strict safety standards into public tenders, african governments can instantly transform ai safety from a passive policy goal into an enforceable market requirement.
"your project landed in the top half of all submissions. strong work."
an open-source protein-aware screening tool that catches adversarial DNA sequences evading standard hamming-distance checks by translating to amino acid homology, defending against context-scrubbed multi-agent LLM biosynthesis attacks.
"your project landed in the top half of all submissions. strong work."
research compares LSTM neural networks against Arps hyperbolic decline models for oil production forecasting using the volve field dataset.
"your paper has been accepted (naice 2026)"
$ cat interests.txt
papers and preprints will appear here as they are completed.
in the meantime: send a mail if you want to talk about any of this.