As Head of NLP, I lead the design, development, and execution of advanced NLP systems, particularly focusing on automatic speech recognition (ASR), language models, and diarization. My role includes: • Strategic Planning and Roadmapping: I define the learning and development roadmap for NLP projects, ensuring team members acquire skills in areas such as RNNs, LSTMs, GRUs, Transformers, and large language models (LLMs). • NLP System Design: I oversee the integration of state-of-the-art NLP models like BERT, AraBERT, and DeepSpeech, working on both research-based advancements and real-world applications, such as building Arabic ASR systems and enhancing their performance. • Research and Development: Focused on Arabic NLP, I lead efforts to explore and fine-tune pre-trained models for tasks like text correction, speech recognition, and diacritization. • Team Training and Mentorship: I design structured training materials and provide mentorship to teams, ensuring they understand both the theory and practical aspects of NLP. I assess their skill levels through curated assessments. • Cross-Disciplinary Collaboration: I collaborate with engineers and data scientists to build pipelines that support large-scale text and audio processing, integrating voice activity detection (VAD) and audio data preprocessing. • Model Optimization: I optimize NLP and speech models for accuracy, efficiency, and scalability, using techniques such as noise reduction, voice diarization, and pre-trained embedding models (e.g., AraVec).By combining technical expertise in machine learning and NLP with leadership in planning and team development, I ensure the successful deployment of cutting-edge NLP systems tailored to project needs, especially in Arabic language processing.

As a passionate tech enthusiast and an Alpha Ambassador for Microsoft Learn Student Ambassadors,I actively engage in empowering students with cutting-edge technology skills. I focus on areas like Artificial Intelligence, Machine Learning, and Cloud Computing, with a commitment to sharing knowledge through workshops, events, and collaborative projects. My role allows me to inspire and guide fellow students in leveraging Microsoft technologies to solve real-world problems, while continuously learning and growing alongside a global community of innovators.

Key Responsibilities: 1. Curriculum Development: ◦ Design and develop a comprehensive data engineering roadmap, ensuring alignment with current industry standards and emerging technologies. ◦ Create structured modules that provide students with practical and theoretical knowledge essential for data engineering roles. 2. Team Leadership: ◦ Lead and mentor a team of subject-matter experts, guiding them in delivering high-quality content and educational experiences. ◦ Provide ongoing support to mentors to ensure consistency in teaching methodologies and adherence to the roadmap. 3. Program Oversight: ◦ Monitor and evaluate the performance of mentors, ensuring that all instructional activities align with the program's goals and maintain the highest educational standards. ◦ Ensure smooth execution of the curriculum, addressing any challenges and ensuring timely delivery of all modules. 4. Quality Assurance: ◦ Continuously assess and enhance the curriculum and teaching methods, incorporating feedback and industry developments to improve program quality. ◦ Maintain a student-centered approach, ensuring learners are equipped with the critical skills required to thrive in the data engineering field.Impact: • Cultivate a robust educational environment that empowers students with the expertise necessary for careers in data engineering, while driving program excellence through leadership and innovation.

Upon concluding this training, I spearheaded a graduation project in data engineering, where I led my team in developing an advanced, end-to-end data solution. Our project leveraged a suite of open-source tools to create a highly scalable and efficient data pipeline, demonstrating our expertise in modern data engineering practices.Key Highlights:- Data Ingestion & Integration: We employed 'Apache Kafka' for real-time data streaming and integration, ensuring seamless data flow from various sources into our system.- Data Processing: Utilizing 'Apache Spark', we designed a robust data processing framework capable of handling large-scale data transformations and analytics with high performance and reliability.- Data Storage: We integrated 'Apache HBase' for distributed, scalable data storage, allowing us to manage and query vast amounts of data efficiently.- Data Quality & Governance: We incorporated best practices for data quality management and governance, ensuring data accuracy, consistency, and compliance throughout the pipeline.Skills Demonstrated:- Leadership & Team Coordination: Effectively led a diverse team, coordinated tasks, and ensured alignment with project goals, showcasing strong leadership and project management skills.- Technical Expertise: Applied advanced knowledge of data engineering tools and frameworks, demonstrating proficiency in real-time data processing, large-scale data management, and interactive data visualization.-Problem-Solving: Tackled complex data challenges, designed innovative solutions, and optimized system performance, highlighting our problem-solving capabilities.This project not only highlighted our technical abilities but also showcased our capability to deliver a comprehensive and integrated data solution using cutting-edge open-source technologies

• Conducted data science workshops at Creativa Hub Alexandria Branch, focusing on data cleaning, feature engineering, and machine learning fundamentals.• Collaborated with team members under the guidance of Eng. Ahmed Hisham to enhance skills in data analysis and modeling techniques.

This rigorous training program provided in-depth practical experience in Data Warehousing, SQL, Advanced SQL, Power BI, Tableau, and statistical analysis. I mastered the design, implementation, and optimization of data warehouses, enabling efficient data management and retrieval. Through comprehensive hands-on projects, I honed my skills in developing interactive and visually compelling dashboards that deliver actionable insights, empowering business decision-making. Additionally, I refined my analytical capabilities, leveraging advanced BI methodologies and industry-leading tools to solve complex business challenges and drive data-driven strategies. This experience significantly enhanced my proficiency in Business Intelligence and data analytics, equipping me to contribute to enterprise-level decision support systems effectively.

During my training at IEEE KSU , I gained significant expertise in computer vision. The training focused on learning deep learning techniques and utilizing neural networks to understand and analyze visual data. I learned to design and implement models that enable systems to recognize objects, classify images, and analyze faces, enhancing understanding and performance in diverse fields such as medical imaging and security.

During my training, I gained proficiency in data analysis tools and techniques, focusing on Excel and Power BI. I developed advanced skills in:Excel and DAX: Mastered data modeling and complex calculations.PivotTables and Power Query: Streamlined data analysis and automated data transformation.Power BI: Created interactive dashboards and visualizations to derive insights.Following the training, I applied these skills by building a comprehensive dashboard for Contoso company. This project involved:Data Modeling: Structured and analyzed Contoso’s sales and financial data using DAX and PivotTables.Data Transformation: Leveraged Power Query to clean and prepare the data for analysis.Dashboard Creation: Designed an interactive Power BI dashboard that visualized key performance indicators (KPIs) and trends, enabling data-driven decision-making.