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Ahmed researches self-supervised learning and mechanistic interpretability, with a focus on how coherence structures in language models give rise to emergent generalization. He co-authored work on coherence optimization for self-improvement and has contributed to papers in cognitive interpretability, activation steering, and efficient reasoning.
He studies Electrical Engineering and Computer Sciences at UC Berkeley as a KAUST Scholar.