Kei Uchiumi is an algorithm engineer based in Japan with nearly two decades of experience building machine learning–driven natural language processing systems and extracting information from large-scale data. He has moved between industry research and product engineering roles—from Yahoo! JAPAN and Denso IT Laboratory to senior engineering posts at LINE and SB Intuitions—now driving algorithms at MNTSQ. His work blends principled probabilistic models (e.g., Pitman–Yor semi-Markov models and variable-order infinite HMMs) with practical downstream optimization like tokenization tuned for task performance. He is a published researcher with multiple conference papers and research awards, demonstrating an ability to turn academic ideas into production-ready NLP tools. Colleagues would note both his deep theoretical grounding and a consistent focus on measurable impact in real-world systems. An unusual strength is his sustained record of advancing unsupervised/weakly supervised methods for language structure across industry and research settings.
13 years of coding experience
18 years of employment as a software developer
Master of information science, Natural Language Processing, Machine Learning, Master of information science, Natural Language Processing, Machine Learning at 筑波大学 / University of Tsukuba
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