Dipl.-Ing. Kamil Kaczmarczyk

+ Future Avionics Architect - Autonomy, Connectivity and Digital Aircraft + CORE and Mission Systems Architect - Legacy Fleet of Airbus Helicopters + Research & Technology Programs Architect - Autonomous Systems and Artificial Intelligence

+ Function Design Responsible - Flight Data Continuous Recording avionics system for all fleet + Led avionics system development throughout an entire product lifecycle from early design, full V&V development cycle, certification, Entry Into Service and serial support (7x EASA Certifications) + Management & architecture - all avionics' families (Avionique Nouvelle / HelioniX® / X-projects)

+ Function Owner - function & digital product development for helicopter operations monitoring + Project Leader & Data Analytics Engineer - flight data monitoring, data-driven added value for helicopter operational safety and design + Research Engineer - Anomaly Detection, Predictive Maintenance, Health and Usage Monitoring

+ Thesis subject: Anomaly Detection and Analysis in Flight Test Data + Performed Machine Learning research in unsupervised learning and built a pipeline to identify and rank anomalies and unusual events in flight data for data quality improvement for predictive maintenance and identification of abnormal flight situations for helicopters operational safety.

+ Made a test-bed for investigations of dynamic properties, control algorithms and trajectory planning of space manipulators working in the simulated micro-gravity conditions. + Designed and conducted a series of experiments of Differential Analyzer Thermophob instrument designed with Russian Federal Space Agency Roscosmos for Phobos-Grunt Martian Moon mission. + Wrote prototype SW for motion analysis of a tumbling satellite leading to docking operation of two spacecraft.

+ Designed two micro-satellite simulators: Thermal Spacecraft Simulator computing the external radiation fluxes and attitude with trajectory as well as Electrical Harness Spacecraft Simulator optimising harness, electromagnetic field and weight together with power consumption.

Applied Machine Learning, Reinforcement Learning, Deep Learning, Computer Vision, Robotics using stack of Python (Scikitlearn, TensorFlow, Keras, OpenCV), C++, ROS, Linux, Git, AWS. Portfolio at slideshare.net/KamilKaczmarczyk/selfdriving-car-machine-learning-portfolio and github.com/kamil-k

Systems, Autonomous Flight, Radars&Sensors, Troubleshooting, Controls, Flight & Space Dynamics