Donia Gamal

Donia Gamal

Cairo, Egypt

Donia Gamal

Technical Lead | Academic Lecturer
Category : Systems automation
Over more than a decade at Ejada LTD., I have led and contributed to a wide spectrum of enterprise-scale projects spanning AI engineering, fintech platforms, and internal digital transformation systems. My recent work includes leading the design of an agentic AI-driven SDLC platform, leveraging modern LLM ecosystems such as AutoGen, LangChain, and LangGraph to automate software development lifecycles. In parallel, I led backend and frontend teams delivering large-scale banking solutions for Al Rajhi Bank, including e-commerce adapters, microservices architectures, and high-performance portals using Spring Boot, Angular, Kafka, and cloud-native platforms. I have also driven the development of full-stack enterprise systems such as HR evaluation platforms, learning management systems, and workflow automation tools, implementing scalable architectures, secure integrations, and data-driven dashboards. Across these initiatives, I consistently combined technical leadership, system architecture, and hands-on development to deliver robust, high-impact solutions aligned with business and operational goals.

Working hours

  • Monday:09h30 To 18h30
  • Tuesday:09h30 To 18h30
  • Wednesday:09h30 To 18h30
  • Thursday:09h30 To 18h30
  • Friday:Not available
  • Saturday:Not available
  • Sunday:13h00 To 20h00
Cyber-hate speech detection for low-resource languages: a multi-task framework that combines paraphrasing, cross-lingual translation, and supervised classification (pre-trained and from-scratch deep models) to detect abusive content across languages. Extensive experiments show effectiveness on several language pairs and dialectal Arabic variants.
Engineering Arabic benchmark Twitter dataset spanning dialects; compared feature extraction and classifier architecture; improved classification accuracy through preprocessing, feature engineering and algorithm selection. Evaluated across social media, product reviews and entertainment datasets (IMDB, Yelp, Amazon).
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