Jalil Latrach

Skills

• Software development: I have been writing software for over a decade using different technologies, with applications ranging from desktop apps written in C++ (before I realized that life is too short to manage memory manually) and Python and full-stack web applications, to data analysis and machine learning applications.
• Machine learning: I used machine learning extensively for a myriad of applications, ranging from degradation quantification of mechanical system using a combination of signal analysis (i.e., Fourier, Wavelet) and convolutional and recurrent neural networks, to physics-informed neural networks for geochemical modeling in the context of carbon storage.
• Big data analytics: I worked on various projects where I dealt with large multimodal datasets (up to hundreds of thousands of data points). I wrote scripts to scrape, filter, organize, analyze, and visualize these data.
• GIS and geospatial data analytics: I have a good experience working with GIS software (mainly ArcGIS and QGIS) for various geospatial data analyis tasks such as spatial interpolation, raster analysis, overlay analysis, and cartography.
• Numerical modeling: I have a good grasp of numerical modeling
• Geochemical modeling: I have experience modeling geochemical systems using software like PHREEQC and Geochemist Workbench, with focus on applications related to geological carbon storaoge (CO₂ solubility and mineral trapping).

Publications highlight