Ainouche Abderahmane

My work sits at the intersection of applied modern NLP and AI with the humanistic sciences. I build domain-adapted, low-resource language systems that make historically significant, structurally complex textual corpora machine-readable and analytically tractable. My interests center on large-scale information extraction, relation mining, and structuring unstructured textual data into queryable, provenance-aware knowledge bases. I focus on leveraging transfer learning, fine-tuning, and modern frameworks to handle diachronic, highly inflected languages, always with an emphasis on interpretability, traceability, and interdisciplinary usability. The broader goal is to bridge computational methods with humanities research, transforming fragmented cultural and historical records into transparent, scalable resources for scholars and practitioners alike.