About Me
Reza Pourrahim Software Engineer | MSc in Data Science
📍 Leiden, Netherlands
Professional Summary
As a skilled Software Engineer with 5+ years of expertise in Python development, I specialize in building robust and scalable software solutions. My experience spans distributed systems, IoT applications, and AI integration, with a particular focus on microservices architecture and cloud infrastructure optimization.
During my Master's in Data Science at the Sapienza University of Rome, I collaborated with esteemed professors and researchers at KDD Lab - CNR at Pisa, working on cutting-edge projects in Data Science, Machine Learning, and Explainable AI. A highlight of this period was developing a novel data and model-agnostic dialogue system for my master's thesis.
Currently based in the Netherlands with an Orientation Year Residence Permit, I bring a unique combination of technical expertise and international experience to my work. My background includes successfully implementing large-scale systems that have demonstrably improved efficiency and reliability in production environments.
Key Areas of Expertise
Backend Development
Expert in Python frameworks (Django, Flask, FastAPI, Twisted) with focus on scalable architectures
Cloud & DevOps
Proficient in Docker, Kubernetes, and CI/CD pipelines with proven deployment optimization
IoT & System Integration
Experienced in implementing IoT solutions with industrial protocols and real-time monitoring
AI & Machine Learning
Strong background in implementing ML models and AI systems with focus on explainability
Professional Experience
Software Engineer
Implemented event-driven microservices architecture using Twisted's asynchronous programming model, integrating IoT devices through industrial protocols (HTTP, TCP, Modbus)
Architected and developed a scalable web application using Python, Flask, and JavaScript, featuring real-time data visualization, device management, and comprehensive test automation with Locust for performance analysis
Transformed monolithic system into a distributed microservices architecture, improving scalability and maintainability while leading Python 2 to 3 migration
Designed and implemented cloud infrastructure using Docker and Kubernetes on DigitalOcean, optimizing CI/CD pipelines through GitLab
Built automated testing framework with pytest, including unit tests, integration tests, and end-to-end testing, achieving comprehensive test coverage
Enhanced event processing pipeline for metadata analysis using deep learning models and microservices architecture
Developed OAuth-based authentication system with Nginx configuration for secure access management
Created data analysis tools for processing and visualizing system performance metrics
Technical Environment
AI Researcher (Master's Thesis)
Research focused on eXplainable Artificial Intelligence (XAI) projects, specifically in Natural Language Processing (NLP) and Dialogue Systems
Developed an innovative eXplainable AI (XAI) dialogue system for natural language understanding using Bidirectional LSTM models, achieving 76% accuracy in query classification
Built full-stack web application with FastAPI backend and Vue.js frontend, implementing RESTful APIs to serve ML models and explanations
Designed interactive UI components with BootstrapVue for model interpretability visualization and user interaction, enhancing user engagement by 45%
Collaborated with research team to evaluate model performance and interpretability across multiple datasets, ensuring robust validation of the approach
Technologies & Methods Used
Research Impact
This research contributed to the field of Explainable AI by developing a novel approach to making machine learning models more interpretable and accessible to end-users through natural language interaction.
Full-stack Developer
Specialized in developing and implementing enterprise-level ERP solutions, focusing on creating scalable and efficient business systems using Python and the Odoo framework.
Developed and deployed enterprise ERP solutions using Python and Odoo framework, implementing custom modules for client-specific business requirements, which resulted in a 15% improvement in workflow automation efficiency.
Built responsive web interfaces using JavaScript and Bootstrap, integrated with backend Python services for seamless data flow, enhancing the user experience and system accessibility.
Designed and implemented RESTful APIs for third-party system integration, optimizing data exchange workflows and reducing manual data entry by 50+ hours monthly.
Improved database performance through query optimization and efficient indexing strategies in PostgreSQL, achieving a 7% increase in data retrieval speed.
Led technical onboarding of new team members while maintaining clear communication with clients on project milestones, resulting in a 10% increase in team productivity.
Technologies & Tools Used
Project Impact
Successfully delivered multiple enterprise-level ERP implementations that streamlined business operations, improved data management, and enhanced cross-functional collaboration for various clients. The solutions implemented continue to serve as foundational systems for client operations.
Education
M.Sc. in Data Science
Research Focus
Specialized in Machine Learning, Deep Learning, and Explainable AI, culminating in a master's thesis on developing an innovative dialogue system for model interpretability.
Key Coursework & Projects
Advanced Machine Learning
Deep Neural Network Models, CNN & LSTM projects, Computer Vision applications
Neural Networks for Data Science
Convolutional Networks, RNNs, Attention-based Models
Statistical Methods in Data Science
12 ECTS comprehensive statistical analysis and application
Cloud Computing
AWS IaaS projects, cloud infrastructure development
Data Management
Relational and Non-relational Database Systems, Large-scale Data Management
Smart Environments
Network Behavior Clustering in LoRaWAN research project
Notable Projects
- Developed innovative dialogue system for XAI as master's thesis project
- Published research on Network Behavior Clustering in LoRaWAN
- Conducted Differential Analysis of Gene Expression in Digital Epidemiology
B.Sc. in Computer Engineering
Key Areas of Study
Bachelor's Thesis
Group Constraints Clustering based on Ensemble Learning - Explored advanced clustering techniques with practical applications in data analysis
Publications
Exploratory Approach for Network Behavior Clustering in LoRaWAN
Research Context
This research addresses the growing significance of IoT networks in modern infrastructure, focusing on the critical need for network optimization and behavior analysis in LoRaWAN deployments. The study presents novel approaches to understanding and improving IoT network efficiency through advanced data analysis techniques.
Abstract
The research examines the increasing deployment of IoT networks across various applications, from home automation to smart cities. We developed a systematic approach for analyzing network data from LoRaWAN platforms, enabling device profiling and anomaly detection. The study processed 997,183 packets from 2,169 devices, revealing valuable insights about network behavior patterns and system optimization opportunities.
Key Contributions
Developed a novel approach for analyzing large-scale IoT network behavior data
Created clustering algorithms for device profiling and anomaly detection
Demonstrated practical applications in network optimization and maintenance
Technologies & Methods Used
Research Impact
This research has contributed significantly to the field of IoT network optimization, providing practical methodologies for network operators to improve system efficiency and reliability. The findings have direct applications in smart city infrastructure and industrial IoT deployments, particularly relevant for organizations implementing large-scale IoT solutions.
Featured Projects
Enterprise Order Processing System
Engineered a comprehensive order processing system for managing customer tickets and barcodes, featuring a robust Flask-based RESTful API. The system emphasizes data integrity, scalability, and maintainability through modern software engineering practices and extensive testing protocols.
Key Technical Achievements
Developed efficient data processing pipeline utilizing Python and Pandas, optimizing order and barcode management workflows
Architected scalable database infrastructure combining PostgreSQL with SQLAlchemy ORM, implementing version control through Alembic migrations
Achieved 100% test coverage through comprehensive pytest suite, ensuring robust system reliability and maintainability
Implemented sophisticated data validation using Pandera and Flask-Marshmallow, ensuring data integrity throughout the system
System Architecture Highlights
Backend Infrastructure
- RESTful API with Flask
- PostgreSQL with SQLAlchemy ORM
- Alembic Database Migrations
Quality Assurance
- 100% Test Coverage with pytest
- Comprehensive Data Validation
- Detailed API Documentation
Technologies Used
AI-Based Dialogue System for eXplainable AI
Developed a revolutionary dialogue system that bridges the gap between complex AI models and end-users, enabling natural language interactions for model interpretability. This system makes AI decision-making processes more transparent and accessible to non-technical users.
Key Features & Achievements
Implemented BiLSTM-based model achieving 76% accuracy in query classification
Built intuitive user interface increasing user engagement by 45%
Developed model-agnostic explanation system compatible with various ML models
Technologies Used
Enterprise IoT Integration Platform
Led the development of a comprehensive IoT integration platform handling 30+ different device types, implementing robust error handling and real-time monitoring capabilities. The system serves as a central hub for device management and data processing.
Technical Highlights
Microservices architecture with Twisted framework achieving 99.9% uptime
Containerized deployment reducing system deployment time by 87%
Implemented comprehensive monitoring and error handling reducing system errors by 40%
Technologies Used
LoRaWAN Network Behavior Analysis
Developed an innovative approach for analyzing IoT network behavior, processing data from nearly one million network packets across 2,000+ devices. The project resulted in a published paper in a prestigious journal.
Research Outcomes
Created novel clustering algorithms for network behavior analysis
Implemented successful anomaly detection methodologies
Published findings in Springer journal with practical applications
Technologies Used
Technical Expertise & Skills
Core Technical Expertise
Backend Development
Python Ecosystem
Advanced expertise in Python development, specializing in building scalable backend systems and distributed architectures. Proficient in implementing event-driven systems and asynchronous programming patterns.
API Development
Extensive experience in designing and implementing RESTful APIs, including authentication systems, data validation, and comprehensive documentation. Strong focus on creating maintainable and scalable API architectures.
Cloud Infrastructure & DevOps
Proven track record in designing and implementing cloud-native solutions, with expertise in containerization, orchestration, and automated deployment pipelines. Experience in optimizing system performance and reliability in production environments.
Infrastructure & Tools
CI/CD & Version Control
Database Systems & Data Processing
Strong foundation in database design, optimization, and management, with experience in both relational and non-relational databases. Skilled in implementing efficient data processing pipelines and optimizing database performance.
Database Technologies
Data Processing
AI & Machine Learning
Applied experience in developing and implementing machine learning solutions, with particular focus on explainable AI systems and natural language processing. Strong understanding of deep learning architectures and their practical applications.
Frameworks & Libraries
Specializations
Professional Competencies
Project Management
Experience in leading technical projects and collaborating with cross-functional teams. Proficient in agile methodologies and project management tools.
Communication & Documentation
Strong technical writing skills with experience in creating comprehensive documentation, technical specifications, and user guides. Effective communicator across technical and non-technical audiences.