BI Developer and Data Analyst

About Me

My name is Moataz Elmesmary, and I am a skilled BI Developer and Data Analyst!

I have a particular interest in analyzing data to discover trends and interpreting data to produce positive change. A DA with experience in SQL, Power BI, Tableau, Python, Excel, ETL processes, dashboarding, MSBI Stack and data-warehousing with a strong ability to transform raw data into actionable insights. Created the most-starred DataScience Roadmap in MENA (Top 3% GitHub repositories).

I earned my bachelor's degree in Computer and Information Sciences from Mansoura University, specializing in Medical Informatics. This interdisciplinary program gave me a solid foundation in computer science and allowed me to explore how technology can address medical challenges.

During my studies, I took courses such as Computer Vision, Digital Image Processing, AI and Health Information Management where I gained a deep understanding of medical image analysis.

I led projects that taught me how to bridge theory and practice. My graduation project, "Smart Suit / Upper Exoskeleton for Patients with Paralysis Using AI and Robotics," integrated computer vision techniques like YOLOv7 and Mask R-CNN to create practical solutions for individuals with mobility challenges. By using a camera I measured the distance between the camera and the object and I segmented the object to make grasping easier. Leading this effort taught me problem-solving, and perseverance in overcoming challenges.

I've worked on several projects that reflect my interest in AI and data-driven solutions. For instance, I developed a diabetes prediction system using Random Forest models and Flask for deployment. This project taught me how to handle end-to-end pipelines, from data preprocessing to deployment. Another project on car price prediction involved data visualization, regression, and clustering techniques. I applied image processing in a signature restoration project, where I tackled issues like noise removal and color restoration. I developed a machine learning model for breast cancer detection using perceptron and SLP, optimized the perceptron, preprocessed the data and visualized weight changes and accuracy over epochs to track model performance. I also worked on a smart wearable upper-limb exoskeleton controlled by voice commands which integrated object detection, segmentation, voice detection, simulation / AR with a mobile app. I went deeply into CNN, detection techniques, and I explored lane lines detection for self-driving cars through ITI summer computer vision internship.