John Cadigan is a computer scientist specializing in natural language processing with 12 years of experience building production-ready ML systems and research-driven solutions. Based in San Diego, he currently applies multimodal semantic media forensics and procedural-language NLP at SRI International after leading machine learning efforts at Ntent where he built record-linkage, news classification, truecasing, and NER models and helped ship a platform for non-experts. His background spans low-level C++ system design for multi-camera instrumentation to large-scale NLP experiments (including Transformer-based language modeling and Spark topic modeling), showing fluency across engineering stacks. He holds an MS in Computational Linguistics from the University of Washington and brings uncommon linguistic depth—degrees in Russian and Korean plus CELTA teaching experience—that informs robust, language-aware modeling. Colleagues rely on him to bridge research publications and production systems, translating novel algorithms into debuggable, inspectable pipelines.
12 years of coding experience
5 years of employment as a software developer
Master of Science (MS), Computational Linguistics, 3.90, Master of Science (MS), Computational Linguistics, 3.90 at University of Washington
B.A., Russian Language and Literature, 3.86, B.A., Russian Language and Literature, 3.86 at University of California, Berkeley
Korean Language, Korean Language at 연세대학교 / Yonsei University
Russian Language and Literature, Russian Language and Literature at Smol'ny Institute
(CELTA) Certificate in Teaching English to Speakers of Other Languages, Teaching English as a Second or Foreign Language/ESL Language Instructor, (CELTA) Certificate in Teaching English to Speakers of Other Languages, Teaching English as a Second or Foreign Language/ESL Language Instructor at ST. GILES INTERNATIONAL SCHOOL OF ENGLISH
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