Evgeniy Andreev
Lead Mobile Engineer at Tawasal SuperApp
Abu Dhabi Emirate, United Arab Emirates
Summary
👤
Senior🎓
Top SchoolEvgeniy Andreev is a Lead Mobile Engineer with 14 years of experience, currently leading the iOS team for Tawasal SuperApp in Abu Dhabi and instituting asynchronous development practices, code review discipline, and remote knowledge sharing. He blends a solid academic foundation in applied mathematics and physics with hands-on mobile development using F#, Xamarin and Fabulous, shipping core logic and cross-platform UI for high‑traffic communication services. An open-source contributor, Evgeniy has improved LaTeX formula rendering in .NET’s xaml-math and advanced feature engineering and dimensionality reduction in the Shogun ML toolbox, demonstrating strengths across back-end, algorithmic, and performance-focused work. Comfortable operating at the intersection of mobile UX and low-level algorithmic code, he brings a pragmatic, research-informed approach to solving tricky parsing, rendering, and data-processing problems.
14 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Applied Mathematics and Physics, Bachelor's degree, Applied Mathematics and Physics at Samara State Aerospace University
English, Russian
Github Skills (28)
algorithm10
algorithms10
formula10
c-language10
dimensionality-reduction10
data-science10
net10
mathematics10
machine-learning10
dotnet10
math10
data-structure10
asp-net10
latex10
parsing10
Programming languages (16)
Github contributions (5)
shogun-toolbox/shogun
Jul 2011 - Sep 2013
Shōgun
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:172 commits, 1 comment in 2 years 2 months
Contributions summary:Evgeniy primarily contributed to the Shōgun machine learning toolbox by implementing and modifying preprocessors and algorithms related to feature engineering and dimensionality reduction. Their work included splitting and refactoring existing code, adding new functionalities, and adapting examples for existing methods. These contributions involved both adding core algorithmic functionality as well as enhancing the usability of pre-existing features like the implementation of a Fibonacci Heap for the Isomap algorithm.
cmakedata-sciencegunc-plus-plusmachine-learning
ForNeVeR/xaml-math
Feb 2017 - Mar 2019
A collection of .NET libraries for rendering mathematical formulae using the LaTeX typesetting style, for the WPF and Avalonia XAML-based frameworks
Role in this project:Back-end Developer
Back-end DeveloperContributions:2 reviews, 56 commits, 21 PRs in 2 years 1 month
Contributions summary:Evgeniy primarily contributed to the .NET libraries for rendering mathematical formulas in the xaml-math repository. Their commits focused on enhancing the parsing of LaTeX formulas, including the addition of features like color support and SVG rendering. They made changes to the parsing logic, implemented culture-invariant parsing, and refactored existing code to improve the rendering of various mathematical symbols.
rendermathdotnetformulaenet-library
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