Lamees Alhumaid

Designed and prepared Arabic children’s story datasets to support AI model training and evaluation. Conducted benchmark experiments on OCR, TTS, LLM, and SLM models. Leading an AI project and coordinating tasks among trainees to ensure progress, collaboration, and high-quality deliverables. Led the implementation of AI Guardrails evaluation pipelines to assess model safety, reliability, and alignment with responsible AI practices. Published internal technical reports on TTS and OCR benchmarking through Naseej Innovation Lab, influencing model evaluation standards and research directions. Designed and delivered an AI Awareness webinar focused on responsible AI adoption, practical risks, and real-world use cases, engaging students and professionals. Contributed to the development of an AI Agent prototype, supporting workflow orchestration, LLM integration, and intelligent task automation experiments. Contributed as an AI Research Contributor in an RDIA-supported research project, focused on developing high-quality Arabic children’s story datasets for AI model training and evaluation. Involved in dataset design, AI-driven content generation, data validation, and enhancing dataset quality to support reliable model performance.

Developed an AI-powered skill assessment and training recommendation system. Built and integrated an AI-based personalized story generator app for children. Co-authored a research paper, focusing on methodology and data preparation.