Piotr Krawiec
Software Engineer at Software Mansion
Subcarpathian Voivodeship, Poland
Summary
👤
Senior🎓
Top SchoolPiotr Krawiec is a software engineer with eight years of experience, blending Python, C++ and data science to build production-ready ML systems, IoT devices, and infrastructure. He holds a master's in Engineering and Data Analysis (diploma with distinction) and currently contributes at Software Mansion after an internship there. Piotr has designed end-to-end solutions—from embedded MQTT data collectors and microcontroller firmware to Postgres/TimescaleDB-backed pipelines, Docker deployments and Grafana/Streamlit observability. At DVLift and Omniscopy he shipped predictive maintenance and anomaly-detection features that bridged stakeholder needs and machine-learning experiments. An active open-source contributor, he implemented a wavelet-based feature-extraction plugin for the NFStream network analysis project, showing both algorithmic depth and practical documentation. Outside work he runs a home lab (TrueNAS Scale) and experiments with self-hosted tools, reflecting a continuous curiosity for systems and ops.
8 years of coding experience
3 years of employment as a software developer
Master's degree, Engineering and Data Analysis, Master's degree, Engineering and Data Analysis at Rzeszow University of Technology
Github Skills (9)
machine-learning10
python10
network-analysis10
data-science10
numpy10
data-analysis10
traffic-analysis9
data-mining9
packet-capture8
Programming languages (14)
Github contributions (5)
nfstream/nfstream
Sep 2022 - Oct 2022
NFStream: a Flexible Network Data Analysis Framework.
Role in this project:
Data Scientist
Data ScientistContributions:6 commits, 3 PRs, 1 comment in 3 days
Contributions summary:Piotr's contributions center around implementing and documenting a wavelet-based feature extraction plugin, demonstrating a strong focus on data analysis within the context of network traffic. The user added a new plugin (`WFPlugin`) that computes features based on wavelet transforms applied to packet size data. They also incorporated example code, improved documentation, and fixed a hardcoded value, indicating a solid understanding of both the underlying algorithm and practical implementation within the project.
pythondata-miningtraffic-analysisndpideep-packet-inspection
finloop/aplikacje-bazodanowe
Oct 2021 - Jan 2022
Projekt na przedmiot Aplikacje bazodanowe.
Contributions:1 review, 75 commits, 2 PRs in 2 months
javaprojekt
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