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Kseniya Mikhno's avatar
Kseniya Mikhno
Brisbane City QLD 4000, Australia
Python Developer | IoT, ML & Full Stack
New to Contra
Python Developer | IoT, ML & Full Stack
Cover image for Developed a web-based job tracking
Developed a web-based job tracking system for a waterproofing business, allowing clients to monitor project progress through a secure web portal accessed via unique QR codes. The waterproofing business needed a way for their clients to track the status of ongoing projects without constant phone calls or emails. They wanted something simple, accessible, and secure. Built a full-stack web application where each job gets a unique QR code. Clients scan the code and are taken to a secure portal showing real-time progress updates on their project. The backend handles job management, status updates, and client authentication. Key features include QR code generation linked to individual jobs, a secure client portal for real-time project tracking, an admin dashboard for managing jobs and updating statuses, and a web-based interface accessible from any device. Python for backend logic, SQL for data management, and web technologies for the client-facing portal.
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Cover image for Built a desktop application for
Built a desktop application for managing repair jobs, designed for small businesses that need to track incoming repairs, parts, costs, and customer information in one place. The application features a clean interface for logging new repair jobs, tracking their status through completion, managing customer records, and generating reports. All data is stored in a SQL database with full CRUD operations. Key features include job intake and status tracking, customer and parts management, cost calculation and invoicing, and reporting for business insights. Built with Python for the application logic and UI, and SQL for persistent data storage.
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Cover image for Developed and integrated a machine
Developed and integrated a machine learning system for geospatial mineral exploration analysis in collaboration with an industry partner. The system processes terrain and geological data to identify potential mineral deposits. The project involved building data pipelines to ingest and clean geospatial datasets, training machine learning models to recognize patterns associated with mineral deposits, and creating visualizations of the analysis results. Key features include automated geospatial data processing, machine learning model training and evaluation, integration with industry partner workflows, and visual output of exploration analysis results. The tech stack included Python for data processing and model development, SQL for data management, and machine learning libraries for predictive analysis.
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Cover image for Developed an IoT-based communication system
Developed an IoT-based communication system that converts web-submitted text messages into Morse code signals transmitted via LED using Raspberry Pi GPIO controls. The goal was to build a system that bridges web-based text input with physical hardware output, demonstrating IoT communication principles through a practical Morse code implementation. I built a web interface where users submit text messages. The backend processes the text, converts each character into its Morse code equivalent, and sends the signal pattern to Raspberry Pi GPIO pins. An LED physically blinks the Morse code in real time. Key features include a web-based text input interface, real-time text-to-Morse-code conversion, Raspberry Pi GPIO integration for LED signal output, and a full-stack architecture connecting the web layer to the hardware layer. The tech stack included Python for backend logic and GPIO control, Raspberry Pi for hardware interfacing, and web technologies for the user-facing input form.
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SQL(2)