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cristiansafta

Cristian S

@cristiansafta

Python Tutor for Beginner Programming Lessons

Schweiz
Englisch
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
I offer practical one-to-one Python lessons for beginners. We work through short examples, write and change code together, and practise understanding errors. My lessons use structured slides, guided exercises and simple programs covering variables, input and output, calculations and conditions. You receive example code, a short recap and practice tasks. Message me with your current level and learning goal so we can plan a focused first lesson.... Mehr lesen

Kompetenzen

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cristiansafta
Cristian S
offline • 

Meine Dienstleistungen

Online Programmieren lernen
I will teach you python basics in a live beginner lesson
Ab25 $ / ProjektWeitere Details
Online Programmieren lernen
I will teach you rag and vector search in a live beginner lesson
Ab35 $ / ProjektWeitere Details

Arbeitserfahrung

Logitech

Engineering Intern

Logitech • Vollzeit

Aug 2025 - Aug 2026 • 1 yr

Designed and released an open-source Logitech Options+ plugin that connects Logitech peripherals to Home Assistant, enabling low-latency, real-time control of smart-home devices via the Creative Console and Actions Ring; launched in beta on the Logitech Marketplace and reached 5k+ installs. More specifically, researched Matter and Home Assistant, set up a multi-device Wi-Fi/Matter testbed, and implemented a layered C# architecture using the Logi Actions SDK and Home Assistant WebSocket APIs, with dynamic device discovery, event-driven synchronization, debounced controls, and support for lights, switches, covers, and scripts. Designed, built and evaluated a real-time screen-to-light control pipeline for immersive gaming, using a TypeScript Matter stack to translate on-screen visual events into physical smart-light reactions and assess whether standardized Matter-based lighting can meet strict latency requirements. More specifically, built controlled latency-measurement tools, implemented real-time screen capture and image-processing components, generated and transmitted lighting commands over Wi-Fi to Matter-compatible devices, and analyzed end-to-end latency, throughput, bottlenecks, reliability, stability, scalability, and compatibility across smart lights from different manufacturers