Everlyne Mwangi
Computational Researcher | AI & High-Performance Computing
Thika, Kenya
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Everlyne Njeri Mwangi is an aspiring computational researcher pursuing a Bachelor of Business and Information Technology at Mount Kenya University. Her work focuses on building scalable AI systems and data processing pipelines, with a growing interest in high-performance computing as a foundation for scientific research.
She has developed projects spanning document analysis, computer vision, and digital healthcare systems, emphasizing efficiency and real-world impact in resource-constrained environments. Through her leadership roles in the AWS Cloud Club and She Code Africa, she actively contributes to the tech community by organizing learning initiatives and mentoring peers.
Everlyne is currently transitioning into research, with a focus on applying computational methods to data-intensive scientific domains, as a pathway toward advanced studies in high-performance computing.
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Responsible AI in Practice: Building Bias-Aware NLP Models with Python
In this hands-on workshop, participants will learn how to identify and mitigate bias in NLP models using Python. We'll explore real-world examples from healthcare and education, audit sentiment analysis models for bias, and discuss responsible AI development in an African context. With libraries like transformers, pandas, and scikit-learn, attendees will walk away with practical tools and a new lens for building ethical AI systems that work for everyone. No prior AI ethics experience required — just Python curiosity!
Building Intelligent Educational Experiences with GenAI on AWS
This talk will walk the audience through how we’re using Generative AI and AWS services to power NexaReality, an AI-first EdTech platform revolutionizing STEM learning through immersive, personalized experiences. As the AI Engineer behind the project, I’ll demonstrate how we integrated LLMs, real-time simulation tools, and voice/chat interfaces into an education system that responds intelligently to learners — all while leveraging the scalability, security, and flexibility of AWS.
We’ll cover:
Architecture breakdown of GenAI + AWS stack
Using Amazon Bedrock and SageMaker to fine-tune and serve models
Real-world lessons from building for resource-constrained environments
Managing cost-effective inference and feedback loops at scale
Vision for AI-powered learning across Africa
Everlyne Mwangi
Computational Researcher | AI & High-Performance Computing
Thika, Kenya
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