Ali Yaseen Email and Phone Number

• Salhad Welfare Medical Center: Developed a comprehensive medical center website for Salhad Welfare Medical Center, integrating PHP, MySQL, and REST APIs to handle user queries, service listings, and updates efficiently.• Airebrokers: Developed a dynamic website for a real estate broker agency using React and Redux for the frontend, ensuring a responsive and user-friendly interface. Implemented a Python Flask backend to handle server-side logic and database interactions, enhancing data retrieval efficiency by 30%.• Multi-Agent Data Synthesis and Concept Extraction System: Built a multi-agent system integrating Neo4j, Elasticsearch, and LLMs to automate concept extraction and generate technical outlines, leveraging OpenAI embeddings for enhanced data processing and interoperability. Implemented RESTful endpoints with OpenAPI documentation for efficient access and usage.

• Soniox Video Downloader: Developed a Python-based processing pipeline to download and process audio and captions from YouTube channels, using Ray.io for multiprocessing and AWS S3 for scalable data storage and management, increasing data processingefficiency by 40%.• Amazon Web Scraper Tool: Built an automated web scraping tool using Python, BeautifulSoup, and Selenium to extract product and store data from Amazon, integrated with multiple Apollo APIs for domain, employee, and executive data retrieval. Implemented user agents and proxies to ensure data extraction reliability, handling high-volume data extraction for over 500 stores daily.• Horse Racing Prediction Model: Developed a predictive model using Python with Random Forest and Time Series Analysis on historical horse racing data to optimize wagering strategies. Applied feature engineering, cross-validation, and hyperparameter tuning to achieve over 90% accuracy. • Handwritten text SVG Text generator desktop application: Developed a Python-based desktop application that converts JPG images into SVG files using OCR and image processing, extracting and manipulating handwritten text to simulate natural handwriting variations for automated SVG generation.• Fraudulent Job Posting Detector: Developed a machine learning model achieving 99% accuracy for identifying fraudulent job postings using Python, Scikit-learn, TF-IDF, and SMOTE for class imbalance correction. Leveraged Random Forest, Naïve Bayes, and Neural Networks for robust predictive performance, showcasing advanced data preprocessing and model tuning skills.

• Developed and deployed web applications using Ruby on Rails (ROR) for the Weatherman project. Implemented essential features, enhancing user experience.• Collaborated with senior developers and stakeholders to troubleshoot and resolve software issues, honing strong teamwork and communication skills.• Communicated effectively and provided timely project updates.