Summary
Andrew Cattle is an NLP and AI lecturer and researcher with a PhD in Computer Science and a decade of experience building production ML systems and language-driven products. He has moved between academia and industry—publishing on computational humour and figurative language during his PhD work, then operationalizing retrieval-augmented generation, vector search, and prompt engineering at startups and Amazon for voice and meeting-driven applications. Comfortable across Python, Java, Ruby/Rails and modern ML toolchains, he focuses on practical, privacy-conscious deployments (e.g., scaling ingestion to thousands of meetings per hour and administering Qdrant). He pairs rigorous research instincts—having developed novel asymmetric relatedness measures that outperformed word2vec on humour tasks—with hands-on engineering that reduced test failure review by an order of magnitude. Based in Vancouver, he teaches applied AI and mentors capstone projects, acting as the bridge between students, industry sponsors, and real-world product constraints.
10 years of coding experience
13 years of employment as a software developer
Master's Degree Linguistics, Master's Degree Linguistics at Seoul National University
Bachelor's Degree Software Engineering, Bachelor's Degree Software Engineering at University of Ottawa
Hong Kong University of Science and Technology (HKUST)
English, Korean, French