Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 3


Scientific Projects:
• Protein database augmentations:  Improving ML prediction of point mutation effect prediction by introducing augmentations to protein structure/sequence datasets.
• Cytochrome P450 metabolism prediction:  DNN for structure-based classification of CYP450 substrates.
• ML prediction of dissociation kinetics:  Experimented with applying classical ML methods to predict protein-ligand dissociation kinetics with a manually curated database.

Pet ML projects:
• Neural 3D Reconstruction:  Reproduced and modified FastMVSNet method to improve the deep multi-view stereo for depth fusion on DTU database.  Deep Learning university course team project.
• Adversarial attack and Defence:  Implementation of the adversarial attack and defence on CNN model trained onFashionMNIST dataset