Joachim Wagner is a research fellow in Dublin with over a decade of experience building and evaluating models for written language, from opinion extraction and text labeling to grammatical error detection and MT quality assessment. His work blends deep NLP expertise with practical skills in high-performance computing, storage management and scalable experiment design, reflecting a career that began programming in 1983 and spans systems administration to postdoctoral research. At ADAPT and CNGL he has delivered reproducible experiments on HPC clusters, supervised students, reviewed peer research, and translated academic ideas into tools useful to industry partners. Known for familiarity with a wide range of machine learning and statistical approaches, he pairs theoretical insight with hands-on implementation across languages and toolkits. Notably, his background includes low-level computer-architecture teaching and early language-learning software development, giving him an uncommon cross-section of systems-level and linguistic perspective.
10 years of coding experience
14 years of employment as a software developer
PhD, Computational Linguistics, Computer-Assisted Language Learning, PhD, Computational Linguistics, Computer-Assisted Language Learning at Dublin City University
Magister Artium, Computation Linguistics, Magister Artium, Computation Linguistics at Universität Osnabrück
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Joachim Wagner - Research Fellow at Dublin City University