Raafat Osman

Joined the Advanced Analytics team at Infineon to design, test, and monitor AI-powered systems for analyzing lab testing data in semiconductor manufacturing. The role combined machine learning and backend software engineering to build scalable, production-ready anomaly detection tools. -> Machine Learning: • Analyzed lab testing data using matplotlib and seaborn; created Jupyter notebooks for data visualization and insights. • Developed a custom anomaly detection algorithm in scikit-learn, tailored to domain-specific signals. • Built ETL pipelines to extract data from various formats, transform time series into distance matrices, and load them for analysis. • Tuned and validated models using metrics aligned with production testing requirements. -> Software Engineering: • Developed a packageable Python tool (>12K lines) using object-oriented programming and clean architecture principles. • Wrote unit tests and end-to-end tests with pytest, ensuring high code reliability. • Authored internal documentation for team usage and onboarding. • Actively participated in code refactoring, applying Clean Code principles to enhance maintainability. • Diagnosed and resolved critical bugs during high-pressure phases. • Used logging to track runtime behavior and facilitate debugging. • Collaborated in a SCRUM environment using Jira and Bitbucket for project management and versioning. -> MLOps & Deployment: • Used DVC for dataset versioning, ensuring reproducibility of machine learning experiments. • Automated parts of the ETL workflow to streamline data preparation and reduce manual effort. • Structured the codebase for scalability and modular integration, allowing for seamless updates and component integration. -> Technologies: Python, scikit-learn, DVC, pandas, matplotlib, seaborn, Jupyter, pytest, OOP, logging, Bitbucket, Jira, SCRUM

• Researched and studied the efficiency of solar panels to power a bird feeding system autonomously. • Collected and treated data from several areas and times of the year to select the optimal dimensions for the panels, ensuring maximum efficiency. • Analyzed environmental factors, such as sunlight hours and seasonal variations, to design a sustainable energy solution. • Gained experience in data collection, energy systems, and project planning under real-world constraints.

• Organized and promoted events for the IEEE Student Club, including communicating with external parties, securing speakers, and coordinating event logistics. • Managed social media posts and content creation to engage and inform potential attendees. • Actively gathered attendees through outreach and digital campaigns, ensuring strong participation. • Organized the IEEExtreme Coding Challenge 2021 in partnership with the Order of Engineers in Tripoli, Lebanon, bringing together participants for a global coding competition. • Developed teamwork, communication, and organizational skills while working in a collaborative environment to ensure successful event execution. • Demonstrated leadership by taking responsibility for key aspects of event planning and promotion.

• Drafted patent applications for a software application and innovative logistics methodology, focusing on detailed technical documentation and clear articulation of concepts. • Collaborated with inventors and lawyers to capture and describe novel solutions in the field of logistics and software development. • Gained insight into the intersection of technology and intellectual property, expanding my understanding of innovation in software and machine learning applications.