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Nataliya Portman received an advanced level of education from leading Canadian universities (McGill University, University of Waterloo and University of Toronto) and a unique experience working with world-renowned scientists on challenging pattern recognition problems. Her postdoctoral research at Montreal Neurological Institute led to a Computer Vision algorithm that allows automatic detection of small brain structures in brain regions where they are barely visible. Nataliya's doctoral work on mathematical modelling of biological growth contributed to multiple disciplines including computational anatomy, optimization methods, quantitative biology and confocal microscopy. Nataliya also gained industrial experience developing novel machine learning applications for non-invasive nutrient analysis of near-infrared spectra. Nataliya has a keen interest in mathematically advanced recognition algorithms and applications of big data technologies to solve complex scientific problems. |
| github: https://github.com/nportman |
Project
I worked on applying machine learning (deep neural networks) to electronic structure theory.
