Xinyu Chen is a graduate research assistant at the University of New Mexico with nine years of professional experience bridging airline mainframe systems and contemporary machine learning research. He combines 15 years of IBM Mainframe and DB2 expertise—having built a production rule-based fare pricing engine deployed at major Chinese carriers—with four years of research in unsupervised learning and parallel computing and a year focused on CNN visualization. Based in Albuquerque, he translates large-scale, legacy transactional requirements into research-driven, high-performance solutions that span from low-level systems to neural model interpretation. Notably, his background enables him to optimize both production-critical business logic and experimental ML pipelines, making him a pragmatic researcher who understands operational constraints.
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