Dr Germán Martínez-Ayuso

• Main maintainer of PyMAPDL library, an open source Python interface to Ansys MAPDL structural solvers.
• Co-owner of Ansys github enterprise organization. Help to maintain Azure CICD pipelines and implementing best practices.
• Co-maintainer of MAPDL solver Ubuntu docker image Containerization of applications for cloud deployment.
• Contributor to MAPDL solver and its gRPC data interface. Implementation of new methods to transfer data from the C++ application server to a Python client.
• Mentoring new employees and interns.
• Supporting customer engagements.

• Contributor to PyMAPDL library.
• Supporting other Ansys libraries ansys/actions, ansys-tools-path, ansys-sphinx-theme, etc
• Supporting the technological transformation of business units. Implementing best code practices, maintaining CICD pipelines in many organization packages, etc.

• Application of machine learning algorithms (clustering and deep learning techniques) to detect abnormal behaviour in real cardiac cells optical data and fluorescent calcium measurements.
• Image processing for data extraction. Application of machine learning techniques to extract data features.
• Design and development of a workflow to analise of microscope images. Development of a graphic user interface in Python.

• Using numerical techniques based on finite element methods and machine learning techniques to optimise industrial composites such as honeycomb or recycled aggregates.
• Collaborated with colleagues using Machine Learning to predict materials properties and accelerate materials discovery. Text mining on research databases.
• Collaborated with industrial and academic partners to develop a web platform for industry access to materials modelling expertise. This project was funded by the European Union and companies such as Fraunhofer, Enthought, Bosch, etc.

• Application of techniques from the domain of data science such as data pre-processing, neural networks and multi constraint optimisation to reduce costs in steel manufacturing industry.
• Developed an addon in Python and JavaScript for a commercial finite element software ANSYS. This addon integrates in the interface of ANSYS application and perform operations to simplify continuum mechanics calculations.
• Developed Python scripts to collect and analyse large data sets from internal company website to analyse machinery performance and propose optimisations.
• Developed numerical models to improve manufacturing processes in the industry. The processes range from material behavior prediction to optimisation of properties such as geometry, elastic properties, viscosity, etc.

Developed numerical models of a wing energy harvester using Matlab to couple different commercial software. Used Matlab to analyse and study large data sets from experiments.