Alban Mouton is a versatile CTO and co-founder with 12 years of software engineering experience, blending hands-on full‑stack development with technical leadership at Koumoul. His background spans academic research and teaching, commercial software engineering, and open-source contributions that touch both front-end UX (vuetify-jsonschema-form) and back-end search/indexing (mongoosastic). He builds practical web services and APIs with attention to data indexing and resilient serialization, and has added performance-minded features like bulk indexing for Elasticsearch. Based in the Greater Saint-Nazaire area, he pairs a Master’s in Computer Science with a maker’s curiosity for new UI components and robust back-end integrations. Colleagues describe him as someone who moves comfortably between prototyping client apps and hardening server-side systems. He aims to keep growing Koumoul as a small, effective engineering shop that ships innovative, efficient web services.
12 years of coding experience
5 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at University of South Brittany
Create beautiful and low-effort forms that output valid data. Published on npm as @koumoul/vjsf.
Role in this project:
Front-end Developer
Contributions:19 releases, 1085 commits, 63 PRs in 4 years 5 months
Contributions summary:Alban has been contributing to the front-end aspects of the `vuetify-jsonschema-form` repository. The commits primarily involve the implementation of UI components for forms that use JSON schemas, including the addition of features such as date pickers, color pickers, and custom components. The user has also improved the user experience by incorporating features like tooltips, the ability to handle a specific file type, and improvements to array item display.
Index Mongoose models into elasticsearch automatically.
Role in this project:
Back-end Developer
Contributions:7 commits in 2 months
Contributions summary:Alban primarily focused on improving the functionality and robustness of the `mongoosastic` library. Their contributions include enhancing the mapping of nested arrays within Elasticsearch, adding features to specify river options for data synchronization, and making the serialization process more resilient. They also introduced bulk indexing capabilities for more efficient data ingestion and fixed a callback issue.
indexelasticjavascriptnodejsmongoose
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