Hi, I'm Stas 👋

Software Engineer | Systems Programming | Control Theory

I am a Rust enthusiast at heart, building high-performance, safe, and concurrent systems. My expertise spans from systems programming in Rust and C++ to Reinforcement Learning and Robotics in Python.

Rust Projects (Primary Focus)

🔄 Life OS

A holistic engine designed to reduce cognitive overload by aggregating life data. It syncs Google Fit (health), Calendar (events), Obsidian Tasks, and life goals into a unified planning interface

• Focus: OAuth2 flows, async API orchestration, reliable state management.
• Key tech: Rust, Tokio, Google API, Serde.

🌆 Rust City Sim

High-performance, lightweight simulator for urban road networks and traffic dynamics.

• Focus: Building a simulation environment exposed as a Python library for city management research.
• Key Tech: PyO3, Bevy, nalgebra, capnp, petgraph.

📦 AUR Auto Updater

A smart AUR helper that manages background updates for Arch Linux packages with parallel execution

• Focus: Dependency graphs, performance optimization, asynchronous task execution.
• Key Tech: Petgraph (graph theory), Tokio, Crossterm.

🚀 Artifacts Server Handler

Automated repository manager for Arch Linux and Ubuntu distributions.

• Focus: High-throughput, zero-copy architecture, and automated CI/CD pipelines.
• Key tech: Rust (Actix-web), Tokio, Linux Internals.

🤖 Rust Telegram Budget Bot

A pragmatic tool for personal finance that transforms Telegram messages into formatted Google Sheets entries.

• Status: Operational (Refactoring planned).
• Key tech: Teloxide, Google Sheets API.

Systems & Engineering (C++)

🕹️ LQR Control Implementation

Robust implementation of a Linear-Quadratic Regulator for dynamical systems with hard constraints and real-time performance requirements.

• Focus: Numerical stability, matrix operations, C++23 modern features.
• Stack: C++23, Eigen, Control Theory.

🔒 Industrial High-Load Project

Ongoing development of performance-critical modules in a professional industrial environment. NDA project

• Focus: Low-latency, memory safety, systems integration.
• Stack: C++17/23, CMake, Linux.

Research & AI (Python)

🤖 Reinforcement Learning Frameworks

Applying RL algorithms to solve complex control and environment problems.

• Projects: Gym Environment | RL Implementation
• Interests: Proximal Policy Optimization (PPO), Deep Q-Learning (DQN).
• Stack: Python, PyTorch, Gymnasium.

Let's Connect

• Email: racoonatwork@gmail.com
• Telegram: ristleell

The line below was generated by Gemini just for fun, but I liked it

"In Rust we trust, in C++ we optimize, in Python we experiment."