A geoprofessional, lecturer and entrepreneur who ventured into software engineering, modern data management and predictive analytics, operating at the forefront of the digital transformation of the Geoprofession.
Passionate about using data and machine learning to improve engineering design (ED) methodologies, and creating intelligent assistants that enable synergistic human-machine ED workflows. Excited to be working on cutting edge projects at Groundwork AI while helping our clients succeed with AI and ML.
During my doctoral studies, I earned the opportunity to build expertise in both Geotechnics and Computer Science through relevant coursework and research projects. It all came together, however, when I started writing software, building production-ready databases and predictive solutions. Practice does make perfect and no better way to become good than to build stuff.
When it comes to Machine Learning, it is easy to be dazzled by (and/or to dazzle with) presentations of impressive predictions leveraging powerful frameworks. I know because I've seen them and given them. Nothing wrong with that, inspiring others pushes us all forward. It is important to notice though, that is most cases what we see are proof-of-concept studies.
Going from a proof-of-concept to a reliable end-to-end predictive solution that clients (a) see the point in using and (b) feel confident using, is the equivalent of graduating from Division III football straight to playing professionally at the NFL.
As a staunch advocate of the digital transformation of the Geoprofession, my work is focused on making high quality AI/ML tools widely available to Geoprofessionals.
I drew the figure above because operating in different spaces often makes it challenging to describe what my products and focus areas are. In addition, I have the pleasure of teaching Machine Learning, Modern Databases and Applied Analytics at Columbia University and NYU.
Please feel free to connect, I am always up for a good challenge or a casual exchange of ideas.
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