Career Profile
Senior Software Engineer at ANSYS specializing in Python, DevOps, and CI/CD. Core contributor to PyMAPDL with 472+ GitHub stars. Focused on AI automation and intelligent systems.
Skills & Proficiency
Python
Software Design
Project Management
API Development
DevOps
Cloud
Frontend
AI Systems
Machine Learning
Experiences
PyAnsys Ecosystem - Main Maintainer of PyMAPDL
- Lead maintainer of PyMAPDL (472+ stars): gRPC API development for Python-C++ interface
- Architected CI/CD pipelines with GitHub Actions for automated testing and deployment
- Docker containerization: MAPDL solver Ubuntu image for cloud deployment
- Managed 200+ issues/PRs with comprehensive documentation and code reviews
- Mentoring engineers and supporting customer engagements
PyAnsys Ecosystem - Core Contributor
- Developed Python libraries for ANSYS products: PyMAPDL, ansys/actions, ansys-tools-path, ansys-sphinx-theme
- Implemented gRPC-based APIs for client-server communication
- Built automated testing frameworks and CI/CD pipelines
- Created developer tools and comprehensive documentation
- Drove technological transformation with code best practices
- Applied machine learning algorithms (clustering and deep learning) to detect abnormal behavior in cardiac cells optical data
- Developed Python-based GUI workflow for microscope image analysis and data extraction
- Applied FEM and ML techniques to optimize industrial composites (honeycomb, recycled aggregates)
- Collaborated on ML for materials property prediction and text mining research databases
- Co-developed web platform for industry access to materials modeling expertise (EU-funded, Fraunhofer/Enthought/Bosch)
- Applied data science techniques (neural networks, multi-constraint optimization) to reduce costs in steel manufacturing
- Developed Python/JavaScript addon for ANSYS to simplify continuum mechanics calculations
- Built Python scripts to analyze machinery performance data and propose optimizations
- Created numerical models for manufacturing process improvement
Education
Micro to macro-scale material modelling using numerical techniques for energy harvesting applications. Fully-funded scholarship
- Developed my own non-linear finite element code in Matlab for piezoelectric harvesters based on Euler-Bernoulli beams. Validated experimentally.
- Used commercial finite element packages to obtain the equivalent mechanical properties of micro composite structures (Homogenization).
Strong background in numerical methods and programming.
Strong background in numerical methods.
Special award, Graduated with honours. Best student record award.
Data Science Projects
A (small) list of projects, repositories and/or ideas I am involved in.
Machine learning for damage detection
- Machine learning algorithms such as Principal Component Analysis (PCA) and Gaussian Mixture Models (GMM) for damage detection in rolling bearings.
Financial fraud detection using machine learning
- Using machine learning algorithms (boosted decision trees) to detect fraud in credit cards records.
Marketig campaing prediction
- Predict the success rate of a marketing campaing given previous records.