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elchibek5/README.md

Hi, I'm Elchibek

Software engineer. I build learning tools and small ML and AI projects that you can run and check for yourself.

Start here

Project What it is
LeetCode Patterns in Java 269 LeetCode and 16 Codeforces solutions grouped by technique, each with its key idea and complexity, all compiled in CI. Comes with a coach skill for Claude Code and Codex that gives hints instead of answers.
EEG motor imagery baseline Cross-subject 4-class brain-computer-interface classifier (Riemannian log-covariance features + XGBoost), validated by participant: 43–46% on people it never saw (chance is 25%). Reproduces on the public PhysioNet EEG dataset in two commands, no GPU.
PaperPilot Reviews ML papers for reproducibility, and checks that every quote it cites is really in the paper. Runs as a web app with Gemini, or inside your coding agent with no API key.
How Long Is a Day? Interactive 3D tour of the solar system that explains, with simple geometry, why a day lasts 24 hours on Earth and 117 days on Venus.
AlgoMentor Spring Boot + React app that returns a validated JSON review of an algorithm solution; runs on a fresh clone with no API key.

Tools

Java · Spring Boot · Python · TypeScript · React · three.js · scikit-learn · XGBoost · C++

Contact

LinkedIn

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  1. algomentor-backend algomentor-backend Public

    Spring Boot API that reviews an algorithm solution and returns a strict, validated JSON report (correctness, complexity, edge cases). Runs with no API key in demo mode.

    Java

  2. paperpilot paperpilot Public

    Review ML papers for reproducibility with every quoted citation checked against the paper text. CLI + Streamlit app (Gemini), plus a skill for Claude Code and Codex that needs no API key.

    Python

  3. leetcode-patterns-java leetcode-patterns-java Public

    269 LeetCode (Java) and 16 Codeforces (C++) solutions grouped by technique, each with its key idea and time/space complexity. Every file compiles in CI. Includes a hints-first coach skill for Claud…

    Java 1

  4. eeg-motor-imagery-baseline eeg-motor-imagery-baseline Public

    Cross-subject EEG motor imagery classification (4-class BCI) in Python: Riemannian log-covariance + XGBoost, validated by participant. 43–46% on unseen subjects (chance 25%), reproducible on public…

    Python