"I don't just write code. I architect systems that scale."
Check out my portfolio website:
🔗 mohammad-hussein-dev.github.io
Built with pure HTML/CSS/JS • Dark/Light mode • Responsive design • All my projects in one place • 📄 Download Resume
Backend engineer with a deep foundation in Physics and Mathematics. I architect scalable systems, design production-ready APIs, and ship code that solves real business problems.
| Aspect | Details |
|---|---|
| 🎯 Current Focus | Architecting production-grade backend systems and shipping real-world APIs |
| 🔭 Right Now | Building scalable platforms with Django REST, FastAPI, and PostgreSQL |
| 🧠 Approach | System-first thinking — every decision evaluated for long-term impact |
| 📚 Foundation | Physics & Mathematics — algorithmic thinking and problem decomposition |
| 💡 Impact | Systems designed for observability, performance, and maintainability |
| Capability | Details |
|---|---|
| API Design | RESTful APIs with HATEOAS, versioning, rate limiting, pagination, OpenAPI docs |
| Database Design | Schema design, indexing strategies, query optimization, partitioning |
| Caching | Redis, CDN integration, memoization patterns |
| Async Processing | Celery + Redis for background tasks and job queues |
| Security | JWT/OAuth2, RBAC, input validation, XSS/SQLi prevention |
| DevOps | Docker, GitHub Actions CI/CD, 12-Factor App, environment management |
Real systems shipped. Not tutorials.
- CI/CD Pipelines — GitHub Actions with automated testing, linting, and deployment
- Container Orchestration — Docker Compose for multi-service apps, ready for Kubernetes
- Database Migrations — Zero-downtime schema migrations with Django migrations + backups
- Testing Strategy — pytest with 96%+ coverage, TDD workflow
- Environment Management — 12-Factor App methodology, environment-based configuration
| Category | Technologies |
|---|---|
| Languages | Python, JavaScript |
| Backend | Django, Django REST Framework, FastAPI |
| Data | PostgreSQL, SQLite, Redis |
| Async | Celery, Redis |
| DevOps | Docker, Git, GitHub Actions, Linux (Arch) |
| Testing | pytest, unittest |
| Scientific | NumPy, Matplotlib, SymPy, Pandas, PyTorch |
| Web Basics | HTML5, CSS3 |
Bridging languages. Connecting knowledge.
Beyond engineering, I transform complex technical content between English ↔ Persian with precision and cultural sensitivity.
| Service | Details | Expertise |
|---|---|---|
| 📚 Technical Translation | Software docs, API references, scientific papers | Django, Python, ML, Physics |
| 🎓 Academic Writing | Research papers, theses, lab reports | LaTeX, APA, IEEE formatting |
| 🌐 Localization | RTL adaptation, cultural context, UI/UX text | Persian/Arabic markets |
| ✍️ Content Creation | Technical blogs, tutorials, documentation | SEO-optimized, developer-friendly |
| Project | Type | Status |
|---|---|---|
| 🐍 Python Documentation (FA) | Official docs localization | 🔵 In Progress |
| 🎯 Django Tutorial Series | Video + blog translation | ✅ Completed |
| 🔬 Physics Lab Reports | Academic paper translation | ✅ Completed |
| 🤖 ML Research Papers | Scientific paper summaries | 🔵 In Progress |
Explore my complete portfolio:
📁 content-studio — A comprehensive collection of translations, technical writing, academic research, presentations, and office works.
Challenge: Simulate electromagnetic-thermal systems without expensive FEM/FVM solvers
Solution: Physics-Informed Neural Network with three selectable architectures (MLP, MLPPINN, TransformerPINN)
Impact: Relative L2 error < 9.09e-04 for electric field, mesh-free, runs on CPU in ~5 minutes
Tech:PyTorchPINNTransformerRoPEGQASwiGLUPythonNumPyMatplotlib
Status: ✅ Production-Ready — View on GitHub | GitLab Mirror
Challenge: Build a scalable task management system with role-based access
Solution: Django + DRF + PostgreSQL + Redis + Celery + Docker
Impact: 96% test coverage, sub-200ms API response times, CI/CD deployed
Tech:DjangoDRFPostgreSQLRedisCeleryDockerpytestGitHub Actions
Status: ✅ Production-Ready — View on GitHub
Challenge: Simulate complex 2D trajectories with air resistance and variable gravity
Solution: NumPy vectorization + Matplotlib animation + pytest for numerical accuracy
Impact: 100% test coverage, 10x faster than naive implementation, bilingual UI
Tech:PythonNumPyMatplotlibpytest
Status: ✅ Completed — View on GitHub
Challenge: Select optimal school locations from 100 candidates with multi-objective constraints
Solution: DEAP framework + custom fitness functions + parallel evaluation
Impact: 40% improvement over greedy baseline, fully containerized deployment
Tech:PythonDEAPNumPyMatplotlibpytestDockerGitHub Actions
Status: ✅ Completed — View on GitHub
| Project | Description | Status |
|---|---|---|
| django-boilerplate | Production-ready Dockerization with multi-stage builds, PostgreSQL, and developer tooling. Reduced setup time from 15-30 minutes to under 2 minutes. | ✅ Merged |
| studybuild-data-cleaning-01 | Data cleaning on an e-commerce dataset — resolved missing values, duplicates, gender inconsistencies, and calculation errors. Delivered a production-ready dataset for EDA and ML. | ✅ Merged |
| studybuild-customer-analysis-02 | Customer Behavior Analysis — performed RFM-style segmentation, Pareto 80/20 analysis, churn risk identification, and discount effectiveness evaluation. Delivered a Jupyter notebook, cleaned dataset, executive dashboard (4 charts), and data-driven business recommendations for the CEO. Transformed raw e-commerce data into actionable strategic insights. | ✅ Merged |
| linear-regression-project | Comprehensive documentation and code quality overhaul for a linear regression project. Added badges, Table of Contents, expanded installation guide, project structure, results section (R² & MSE), CONTRIBUTING.md, CODE_OF_CONDUCT.md, Google-style docstrings with type hints, improved error handling, PEP 8 formatting, combined subplots for visualization, grid lines, legends, 150 DPI resolution, and accessibility-focused color scheme (blue for train, green for test). | ✅ Merged |
| large-file-memory-optimization | Code quality and documentation overhaul for a Pandas memory-optimization pipeline. Added Google-style docstrings and type hints across all modules, replaced print() with structured logging, built a full argparse-based CLI (--output, --compression, --verbose), implemented dtype/name-based auto-detection for columns, added multi-format compression support (snappy, gzip, brotli, lz4, zstd), and expanded README with badges, API usage examples, and a CONTRIBUTING.md guide. | ✅ Merged |
| large-file-memory-optimization | Test suite and CI/CD pipeline for the same memory-optimization project. Added pytest suite with 25+ test cases covering data loading, memory analysis, optimization logic, preprocessing pipeline, and save/compression — including edge cases like empty DataFrames and invalid inputs. Set up GitHub Actions workflow with a test matrix across Python 3.9–3.12 and Codecov coverage reporting. | ✅ Merged |
Key improvements made in the new PR:
- ✅ Badges (Python version, Scikit-learn, License, PRs Welcome)
- ✅ Table of Contents for easy navigation
- ✅ Expanded installation guide with virtual environment instructions
- ✅ Detailed project structure with module descriptions
- ✅ Results section with R² and MSE metrics
- ✅ CONTRIBUTING.md with development setup, commit guidelines, and PR checklist
- ✅ CODE_OF_CONDUCT.md based on Contributor Covenant
- ✅ Google-style docstrings and type hints for all functions
- ✅ Improved error handling (FileNotFoundError in preprocess.py)
- ✅ PEP 8 code formatting
- ✅ Combined training/test plots in a single figure with subplots
- ✅ Grid lines, legends, 150 DPI resolution, and accessibility colors
- ✅ test_size changed to 0.2 with random_state=42 for reproducibility
Key improvements made in the memory-optimization PRs:
- ✅ Google-style docstrings and full type hints (PEP 484) for all modules
- ✅ Structured logging replacing all print() statements
- ✅ Input validation and specific exception handling
- ✅ CLI interface with argparse (--output, --compression, --verbose)
- ✅ Auto-detection of columns by dtype pattern and name keywords
- ✅ Multi-format compression support (snappy, gzip, brotli, lz4, zstd)
- ✅ README overhaul — badges, CLI section, API examples, Contributors table, TOC
- ✅ CONTRIBUTING.md with dev setup, style guide, and PR process
- ✅ pytest suite with 25+ test cases across 5 modules
- ✅ GitHub Actions CI matrix — Python 3.9, 3.10, 3.11, 3.12
- ✅ Coverage reporting via pytest-cov + Codecov integration
I'm an active member of the StudyBuildCommunity organization — a collaborative community for Statistics, Data Science, Machine Learning, and AI. I contribute to open-source projects and collaborate with fellow data scientists and engineers.
Active projects in development. Follow the commits.
| Project | Stack | Status | Goal |
|---|---|---|---|
| PINN Extension to 2D | PyTorch + NumPy + Matplotlib | 🔵 In Progress | Extend the electro-thermal PINN to 2D spatial domains |
| Real-Time Chat Backend | Django Channels + WebSockets + Redis | 🔵 In Progress | Scalable chat with read receipts and typing indicators |
| ML-Powered Recommendation Engine | scikit-learn + FastAPI + PostgreSQL | 🟡 Planning | Content recommendation system with A/B testing |
| BI Project Management System | React + Express + MongoDB | 🟡 Planning | Combining business intelligence with project management (collaboration with Ahmad Raza Rajpoot) |
I architect scalable backend systems and production APIs with Django, DRF, and FastAPI.
Whether you need a full-stack app, an admin panel, a REST API, or performance optimization — I'm ready.
- 📄 Resume: Download my latest resume
- 🌐 Portfolio: mohammad-hussein-dev.github.io
- 🔗 LinkedIn: mohammad-hussein-dev
- 🐙 GitHub: mohammad-hussein-dev
- 🦊 GitLab: mohammad-hussein-dev
- 💬 Telegram: @mohammad_hussein_dev
- 🐦 X: @mohammad_h_dev
- 📺 YouTube: mohammad_hussein_dev
- 📧 Email: king.mohamd.09876@gmail.com
- 💼 Karlancer: MohammadHossein.Gh
- 📄 Parscoders: mohammad_hussein
- ✍️ Typeiran: Mohammad Hussein Ghafoori
- 💼 Lancerify: Mohammad Hussein
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- 📌 Ponisha: MHussein1
- 📌 Upwork: Ready for freelance
"Clean code, solid architecture, and on‑time delivery."