Csenger
Molnár

• Designed and maintained Azure SQL databases for production systems, covering migration, schema design and performance optimization.
• Built pipelines that carry data from manufacturing equipment through Azure IoT Hub into Azure SQL, so production data is collected and stored reliably.
• Planned the database architecture and data models that reporting, analytics and application development are built on.
• Developed internal tools and desktop applications in Python and PyQt to automate workflows and open up access to production data.

• Analysed audio signals in Python with Librosa and NumPy, writing custom filtering, feature extraction and preprocessing pipelines.
• Developed and trained deep learning models in PyTorch, including CNN architectures for audio pattern recognition.
• Built a PyQt application the research team used daily for data visualisation and model evaluation.

• Contributed to a large-scale military application used by European Union partners.
• Migrated legacy components from AngularJS to Angular to improve maintainability and performance.
• Implemented features, fixed bugs and tested across the stack in Java, Scala and SQL.

• Developed a frontend application in Angular and TypeScript for investors to track stock prices.
• Automated Python workflows that generated and stored daily Excel reports.
• Integrated kdb+ as the data source, writing the queries that supplied time series data to the frontend.

Specialised in machine learning and data science.

• Machine learning, deep learning and statistical modelling.
• Neural network architectures including CNNs, GNNs and fully connected networks.
• Data mining, clustering, graph algorithms and large-scale data analysis.
• Graph-based data mining and spectral methods.

Thesis, written in partnership with Systematic: graph neural networks for predicting ship types in the AIS maritime dataset.

• Software engineering principles, object-oriented programming and software architecture.
• Data structures, algorithms, databases and computer systems fundamentals.
• Mathematics for computer science, including statistics, probability theory and linear algebra.
• Web development, REST APIs and version control.