Aleksandra Karpova

I’m a software engineer focused on real-time industrial data pipelines, distributed control-system components, and AI-powered software. My academic foundation in artificial intelligence and quantum and classical machine learning (including a thesis on Quantum Kernel Classification) shapes how I design robust, data-driven systems.

At OPTECS B.V., I built and integrated Smart Grinding Control Distributed System components across data preprocessing, feature filtering/extraction, fuzzy inference, and dynamic model calculation. I also developed AI-based components for real-time data gathering and feature extraction from visual and sensor inputs.

I care about performance, reliability, and testability. By optimizing the camera capture and processing pipeline, I doubled real-time video ingestion throughput (10 Mbps to 20 Mbps) and reduced per-sensor processing latency (120 ms to 45 ms), while also cutting memory usage (1.8 GB to 900 MB).

I’ve additionally delivered practical industrial engineering support through OPC UA integrations and simulation tools for testing without access to live equipment, and I improved automated test coverage from 50% to 85% across critical components. I’m now looking to keep pushing real-time, AI-enabled systems from prototype to production with strong engineering discipline.