Chuansheng is the technical backbone of KONTEXT. With an MSc in Autonomous Systems from the Technical University of Denmark, he builds the systems that let the platform listen, learn, and scale.
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Before KONTEXT, he worked independently on LLM-based systems for advisory automation and internal tools, exploring how large models, retrieval, and probabilistic inference can be made reliable in real-world settings. Earlier in his career, he also worked in quantitative finance, building data systems and machine-learning models for fixed-income investment decisions.
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At KONTEXT, he turns raw, messy public conversation into structured, place-based insight, building the infrastructure that lets the platform listen to cities in real time. His work spans:
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- Large language models and NLP, used to read and interpret urban conversations
- Data pipelines and engineering (ETL, databases, and scalable ingestion)
- Machine learning and model deployment
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What drives him is not just building smarter models, but building systems that stay understandable and useful when the things gets messy.