Cristian Ninicu
Software Engineer at Lanterne
Iași, Romania
Summary
👤
Senior🎓
Top SchoolCristian Ninicu is a versatile software engineer with nine years of experience building full-stack applications using Java, JavaScript/TypeScript, React, Node.js, MongoDB and AWS across startups, freelance projects and global teams. He has shipped production services at Amazon and contributed front-end and back-end features at companies like Shoreline and Adobe, while also delivering bespoke consultancy work for clients such as Integrity Labs and Structural Management Solutions. With master's studies in Computational Linguistics and Computer Science, he blends practical engineering with a curiosity for language-aware systems and continuous self-improvement. Now based in Iași and currently at Lanterne, Cristian pairs an optimistic, empathetic mindset with a track record of adapting between large-scale cloud environments and lean product teams. He’s known for translating complex requirements into maintainable, user-focused solutions and for treating every role as an opportunity to learn and improve the world around him.
9 years of coding experience
7 years of employment as a software developer
Master's degree, Computational linguistics, Master's degree, Computational linguistics at Universitatea „Alexandru Ioan Cuza” din IașiMaster's degree, Computer Science, Master's degree, Computer Science at Universidad de Murcia
English, Romanian, Russian
Github Skills (24)
classify4
gestures3
synchronize3
rule3
conceptual-model3
web-application3
wave3
gcp2
gesture2
statistics2
google-cloud-platform2
json2
webcam2
react2
streaming2
Programming languages (2)
Github contributions (5)
cninicu/gezr
Oct 2020 - Jan 2021
Having a number of Webcam-captured video streams, build a Web application that detect, classify, compare, and synchronize hand and arm gestures performed by (human) users. A conceptual model will be created/(re)used in order to express (classes of) gestures, anatomic features, associated actions, etc. A rule-based approach could be adopted – for example, if the "wave" gesture is detected in at least 74% of video feeds exposed by a video-conferencing system, then the conference session will be ended. Also, different statistics of interest will be offered in graphical form and as JSON-LD data. Study An Ontology for Reasoning on Body-based Gestures. Consult also Awesome Streaming and Recognition APIs. Bonus: capturing and exposing useful provenance.
Contributions:51 pushes, 5 branches in 3 months
rulestreamsexpressprovenanceweb-application
DoubleNy/Demokratie-bringer
Dec 2016 - Apr 2017
Contributions:29 pushes, 1 branch in 3 months
javapythongame
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