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Specializing in engineering software for scientific instrumentation and quantum sensing
I am a Software Engineer at Quantum Diamonds GmbH, developing cutting-edge software for quantum sensing devices used in semiconductor chip failure analysis. My work bridges machine learning, sensors, and instrumentation to solve complex scientific and engineering challenges.
Previously, I spent three years as a Postdoctoral Researcher at DESY, applying machine learning algorithms for virtual diagnostics of the European XFEL. I earned my PhD from the University of Malta in collaboration with CERN, where I developed real-time machine learning models for predicting magnetic fields in the ELENA synchrotron used for antimatter research.
Neural Networks, Computer Vision, NLP, TensorFlow, PyTorch
Python, Java, C, Qt, Application Development
Pandas, NumPy, SQL, Elasticsearch, Cloud (AWS, GCP)
MATLAB, R, Instrumentation, Real-time Systems
Applied ML classifiers and computer vision techniques for Bragg crystal energy calibration at the European XFEL, achieving 68% extraction rate with low false positives using the Hough Transform method.
Developed real-time machine learning models for magnetic field prediction in CERN's Extra Low Energy Antiproton ring, commissioning and calibrating the measurement system for antimatter research.
Implemented natural language processing techniques to extract meaningful keywords from large datasets, creating streamlit interfaces and establishing cloud infrastructure for data processing.
I'm always open to discussing machine learning, scientific computing, or quantum sensing projects.
Get in Touch