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sergioald/README.md

Hi, I'm Sergio 👋

Applied AI & research software for engineering systems
Digital twins · anomaly detection · sensor-data QA/QC · scientific Python

Python Research Software Digital Twins LinkedIn

About me

I build applied AI and research-software tools for engineering systems.

My work connects machine learning, sensor data, simulation, and domain knowledge to help monitor, validate, and understand complex physical systems.

I am especially interested in:

  • Digital twins for engineering and infrastructure systems
  • Anomaly detection from sensor, acoustic, and operational data
  • Data-quality checks for experimental and monitoring workflows
  • Scientific Python tools for reproducible computational research

Selected projects

Project Area Shows
Hydraulic Digital Twin Digital twins Synthetic sensor data, anomaly detection, fault classification, reporting
TDMS Sync Checker Sensor-data QA/QC TDMS timing checks, synchronisation diagnostics, split-file continuity
Structural Audio Anomaly Detection Structural monitoring Feature extraction and anomaly detection for structural-test audio
LDSFL Meander Scientific modelling Morphodynamic modelling, reproducible simulations, CLI/GUI tools

Technical focus

  • Applied AI: anomaly detection, classification, signal features, model validation
  • Engineering data: TDMS files, sensor synchronisation, data quality, experimental workflows
  • Scientific Python: NumPy, pandas, SciPy, Matplotlib, scikit-learn
  • Research software: reproducible scripts, documentation, examples, reporting

Repository style

I try to make repositories useful as engineering artefacts, not only as code.

Where possible, projects include:

  • A clear problem statement
  • Installation and usage instructions
  • Example data or synthetic data
  • Visual outputs
  • Assumptions and limitations
  • Reproducible workflows

Contact

Contact

I am interested in applied AI, research software, digital twins, and engineering-data workflows.

Pinned Loading

  1. synthetic-hydraulic-digital-twin-demo synthetic-hydraulic-digital-twin-demo Public

    Synthetic hydraulic digital-twin demo for sensor validation, energy modelling, anomaly detection, fault-state classification and automated reporting.

    Python 2

  2. LDSFL_Meander LDSFL_Meander Public

    LDSFL-Meander is a Python reduced morphodynamic model for meandering rivers, with CLI and GUI workflows, dimensional/dimensionless inputs, geometry preprocessing, and reproducible planform simulati…

    Python 1

  3. audio-anomaly-detection-structural-testing audio-anomaly-detection-structural-testing Public

    Audio anomaly detection for structural testing using WST features, CAE feature maps, NCC, and classifiers.

    Python 1

  4. tdms-sync-checker tdms-sync-checker Public

    Metadata-first TDMS QA/QC tool for timing checks, split-file continuity, activity review, and optional engineering diagnostics.

    Python