I'm experienced R&D Engineer in Deep Learning with over two years of expertise in computer vision and natural language processing reinforcing corporate brand as innovative.
- Automatic essay evaluator Linguask for assessing natural language text by analytical measures, e.g., vocabulary, syntax, cohesion etc. Special attention is given to quality ensuring techniques that (partially) automate routine operations and restrict programmers from violating style rules and designing non-working code.
- Сlosed-source deep learning package
spinerused in AI Lab of Innopolis University to explore morphometry of vertebrae and intervertebral discs, measure coronal and sagittal Cobb angles, classify and segment osteoporosis on each vertebra. - Open-source Django-driven app Doctorinna for determining the user's risk group for various diseases. This project was mentioned by Lab Director in Huawei Yegor Bugayenko in his blog post.
- Closed-source
albumentations-integrable packagepurelungused in AI Lab of Innopolis University for suppressing bone shadows, context-aware image crop, image segmentation, and auto-inverse operation in the Chest X-ray images.
- Currently working on inherently interpretable machine learning architecture under supervision of Ivan Titov (Prof. in University of Edinburgh, h-index 45).
- European Spine Journal (Q1): "A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation", available online, under supervision of Bulat Ibragimov (Prof. in University of Copenhagen, h-index 26).
- Deep Learning
- Adversarial attacking and defense
- Interpretable Machine Learning
- MLOps
- Simulation modelling
- Quantum programming
- Branding / Visioning
- See more in my Curriculum Vitae
Interested in me? — here is how to reach:
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P.S. Click ⭐ in this repo to prevent your gradients from vanishing 😱