Michael Mesarcik
Applied Machine Learning Scientist
📍 Amsterdam
📧 mimesarcik@gmail.com
🔗 GitHub | LinkedIn | Google Scholar
About
I am an applied machine learning scientist with a PhD in anomaly detection for distributed sensing systems. I have experience in both the space and energy sectors, and a strong background in research and production environments.
Skills
- Programming: Python, Linux, Java, C++, C, CUDA, Verilog, VHDL, SQL
- Technologies: PyTorch, TensorFlow, AWS, GCP, Pandas, Scikit-learn, Matplotlib, SciPy
- Languages: English, Czech
Projects
- ROAD – Anomaly detection for radio telescopes (PyTorch)
- RFI-NLN – Semantic segmentation for RFI detection (TensorFlow)
- DL4DI – VAE-based data visualisation for radio telescopes (TensorFlow)
- REDTOOTH – Real-time acoustic data transmission (Java)
- DRFM – Radar signal processing system for a low cost FPGA (Verilog)
Education
- PhD, Informatics – University of Amsterdam (2019–2024)
- MSc, Electrical Engineering – University of Cape Town (2017–2018)
- BSc, Computer Engineering – University of Cape Town (2013–2016)
Experience
- Machine Learning R&D Engineer – Alliander (2024–Now)
- Teaching Assistant – University of Amsterdam (2020–2022)
- Data Science Intern – DataProphet (2018–2019)
Selected Publications