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👋 Hi, I'm Gyashu Rahman

Software Engineer | Full Stack | High-Performance Systems | Scalable Architect

LinkedIn LeetCode Portfolio Email


🚀 About Me

Full-stack engineer with experience building scalable, user-focused 0→1 products. Delivered platforms serving 1,000+ users, AI-powered tools, and high-performance dashboards using React, Node, MySQL, and Rust/WASM. Strong execution, systems thinking, and product mindset.

  • 🔭 Currently: Building high-performance systems & developer tools
  • 🌱 Exploring: Systems architecture, low-latency optimization & distributed systems
  • 🏆 Problem Solving: 650+ LeetCode problems (1780+ rating)

🛠️ Tech Stack

Programming Languages: C++ Rust Python JS TS
Systems & Performance: SIMD Lock-free HTTP/2 Tokio
Frontend Development: React Next.js WASM Tailwind CSS Framer Motion
Backend & Databases: Node.js Express MongoDB MySQL RocksDB Firebase
DevOps & Cloud: Docker Kubernetes Oracle Cloud AWS CMake Git

🏗️ Featured Projects

🕸️ Hybrid Speed Crawler

Production-grade C++ web crawler achieving 50-100 pages/sec with fault tolerance and policy compliance.

🏆 Highlights: 50-100 pages/sec throughput • 10× CPU gains via SIMD • Robots.txt compliance • RocksDB persistence | View Code | Documentation

C++ libcurl RocksDB SIMD CMake

  • Created an open-source, cross-platform webpage analysis engine with 1,000+ downloads across Rust, WASM, CLI, and C++ interfaces — delivering actionable insights on SEO, accessibility, and performance.
  • Enabled tailored quality evaluation for diverse web domains by designing a modular scoring system supporting 8+ analysis profiles (e-commerce, news, portfolio, etc.) and customizable thresholds.
  • Attained ultra-fast performance of less than 100ms per page and 180+ pages/sec in batch mode by developing parallelized DOM parsing, connection pooling, and achieving a 36–40× throughput gain over sequential execution.y.

⚡ Webpage Quality Analyzer

Cross-platform Rust analyzer with 1,000+ downloads deploying to 4 targets from a single codebase.

🏆 Highlights: 1,000+ downloads • 36-40× speedup • 180+ pages/sec batch throughput • WASM + C++ bindings | Live Demo | GitHub | npm | crates.io

Rust WASM TypeScript C++ Tokio

  • Built a high-performance web crawler capable of fetching 100+ pages/sec, powered by multi-threaded scheduling and domain-aware rate limiting across 256 partitions for large-scale indexing.
  • Ensured uninterrupted crawling with minimal data loss by implementing a RocksDB-backed persistence and crash recovery system, enabling safe checkpointing and auto-resume.
  • Reduced average fetch time to 0.5–2.0s and maintained a low memory footprint of less than 20MB by optimizing the network stack with HTTP/2 multiplexing, connection pooling, and SIMD parsing.

🔧 Other Projects (Click to Expand)

🔧 Intelligent BLDC Motor Fault Detection

ML-Powered Predictive Maintenance System | View Code

Python scikit-learn MATLAB pandas

  • Developed ensemble ML models (Random Forest, SVM) achieving 95%+ accuracy for fault classification across 5 motor states.
  • Engineered advanced feature extraction pipelines optimizing inference latency to <50ms for real-time embedded deployment.
  • Simulated complex motor behavior and fault scenarios using MATLAB Simulink enabling comprehensive testing with 10,000+ samples.
  • Built scalable data infrastructure with end-to-end pipelines for predictive maintenance applications.

🌐 Social-Arena

Full-Stack Social Media Platform | Live Demo | View Code

MERN Firebase Socket.io MongoDB

  • Architected full-stack social media platform with RESTful APIs and real-time chat using Socket.io, supporting 500+ concurrent WebSocket connections.
  • Implemented secure authentication using bcrypt and JWT, reducing login issues by 15% through improved UX flows and error handling.
  • Designed MongoDB schema with optimized indexing achieving <100ms query response times and supporting horizontal scalability for 1,000+ users.
  • Optimized React rendering with useMemo and useCallback hooks, implementing virtual scrolling for feeds supporting 1,000+ posts.

🤖 Chrome-Assistant

Intelligent AI Browser Companion | View Code

Manifest V3 Google GenAI TensorFlow.js Webpack 5 React

  • Developed Chrome extension with React and Manifest V3, integrating TensorFlow.js for in-browser AI-powered text features improving productivity by 30%.
  • Reduced extension bundle size by 25% using Webpack 5 optimizations including tree shaking, code splitting, and dynamic imports for faster load times.
  • Implemented context-aware UI with seamless DOM integration and responsive design, supporting both light and dark modes with smooth transitions.

🎵 Fingerpad Glove

AI-Powered Interactive Music System | View Code

C++ Arduino Supercollider TensorFlow Lite

  • Developed an interactive musical instrument using microcontroller, LDRs, and motion sensors with real-time audio synthesis.
  • Programmed in C++ and Supercollider to generate dynamic tones based on real-time hardware interactions.
  • Designed for user-friendly operation and seamless synchronization with other instruments.

📫 Let's Connect

I'm always excited to discuss projects, innovative ideas, or potential collaborations. Let's build something amazing!

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"The best way to predict the future is to invent it." - Alan Kay

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