Fourat Kandil

– Migrated a relational database to a graph database to better capture relationships between data points. – Constructed and modeled the graph structure to improve data connectivity and flexibility. – Calculated similarities between graph entities to detect redundancies, ambiguities, and inconsistencies. – Applied clustering algorithms to group similar data for enhanced analysis and organization. – Explored and compared data modeling approaches to support more effective data-driven insights.

– Design and implementation of data ingestion and transformation pipelines from heterogeneous sources using both batch and real-time processing. – Contribution to the development of a fraud detection engine combining business rules and AI algorithms. – Design of real-time alert systems and development of an investigation dashboard, incorporating analyst feedback to refine rules and improve model performance

– Designed an intelligent travel recommendation system using LLMs to extract structured information from YouTube vlogs and blogs and generate personalized itineraries. – Processed over 500 vlogs, achieving 87% accuracy in information extraction and 85% accuracy in itinerary generation – Working with different teams to help them make better decisions based on data. – Cleaning and exploring data to understand it better. – Helping develop new solutions to solve business problems.

– Developed real-time data extraction mechanisms for tournaments, player rankings, and match statistics. – Designed an intuitive user interface for displaying data insights and efficiently processing large datasets. – Created features for event analysis, dynamic statistics, and tournament data management, providing insights into performance trends.

– Developed an image recognition system to identify and classify vehicle-types, contributing to territorial monitoring and security, with an accuracy of 92% – Implemented deep learning models to detect vehicles in live video streams.

– Designed and developed backend systems to manage IoT device data, including registration, categorization, and real-time tracking. – Implemented a secure and scalable database structure to store IoT sensor data and device metadata. – Integrated APIs to enable dynamic communication between IoT devices and the platform, ensuring reliable data exchange. – Developed authentication and authorization protocols for secure device and user access. – Collaborated with front-end teams to create dashboards for monitoring IoT device activity and analytics.