Anna Widiger is a computational linguist based in San Francisco with 11 years of experience applying both rule-based and machine learning approaches to NLP problems such as text normalization, classification, NER and event detection across multilingual corpora (20+ languages). She blends rigorous cognitive psychology training—experimental design and statistical analysis in R/SPSS—with hands-on software development (Java, SQL, regex, Perl/bash) to build practical language technologies and educational language-learning modules. Her background includes corpus alignment work at the European Commission’s JRC and parser/grammar development for German and Russian, reflecting deep expertise in linguistics-informed engineering. Comfortable with spaCy, scikit-learn and Keras, she iterates between research and production, bringing psycholinguistic insight to ML-driven NLU systems. An often overlooked strength is her long history of part-time software roles since 2004, which gives her a pragmatic, product-focused perspective on academic research.
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