Alexey Stukalov
Staff Bioinformatics Scientist
Redwood City, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAlexey Stukalov is a Staff Bioinformatics Scientist with 17 years of experience combining deep computational mathematics and hands-on software engineering to build robust analysis pipelines for novel nano-bio technologies. Based in Redwood City, he leads development of statistical inference and ML methods at Seer and brings a strong track record of publishing high-impact viral research from roles at TUM, Max Planck, and CeMM. A PhD and summa cum laude MS in Computational and Applied Mathematics from MSU underpin his ability to translate advanced math into practical tools for mass-spectrometry and genomics. Alexey is also an active open-source contributor to the Julia ecosystem, improving core data handling in widely used projects like DataFrames.jl and CSV.jl—work that highlights his focus on performance, edge-case robustness, and clean refactoring. He uniquely bridges academic rigor and production engineering, often surfacing subtle data-parsing and numerical edge cases before they impact downstream science.
17 years of coding experience
8 years of employment as a software developer
Lomonosov Moscow State University
Github Skills (22)
csv-parse10
testing10
data-manipulation10
data-structure10
csv-parsing10
data-structures10
linear-algebra10
julia10
programming-language9
numerical-methods9
performance-optimization9
scientific-computing9
fileio9
file-access9
file-processing9
Programming languages (10)
Github contributions (5)
JuliaData/DataFrames.jl
Dec 2014 - Oct 2020
In-memory tabular data in Julia
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 review, 48 commits, 27 PRs in 5 years 10 months
Contributions summary:Alexey primarily refactored and improved the RDA (R Data) file format reader within the Julia dataframes.jl repository. Their contributions involved code optimization, by minimizing code duplication, adding new data structures for efficient stream handling, renaming functions for clarity, and implementing a dict-based dispatch mechanism for reading methods. Furthermore, the user added support for complex number import and implemented tests for NA/NaN values, thus improving the robustness and functionality of the RDA reader.
memorydataframesdatatabular-datadata-frame
JuliaLang/julia
Jul 2015 - Apr 2021
The Julia Programming Language
Role in this project:Back-end Developer
Back-end DeveloperContributions:16 commits, 19 PRs, 268 comments in 5 years 9 months
Contributions summary:Alexey contributed to the Julia programming language by implementing and modifying core functions related to mathematical operations and linear algebra. They added the `clamp!` function to the `base/math.jl` file and corrected existing code in `base/linalg/symmetric.jl` and `base/linalg/matmul.jl` to improve functionality. The user also made improvements to the `mapreduce` function, including fixes for 1-element ranges, and handled small array cases, demonstrating knowledge of array manipulation and performance optimization within the Julia ecosystem. Furthermore, the user addressed errors in documentation and corrected typos.
sciencejulia-languagemachine-learningjulialangpetsc
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.