Inclusive AI, engineered for impact

The Chair of Inclusive Technology and Collective Engagement, led by Prof. Giulia Barbareschi, welcomes Nancy Bou Kamel as a new member of the team. With her background as a Data Scientist and Machine Learning Engineer, Nancy strengthens the technical AI expertise of the lab at RC Trust at a time when inclusive AI is becoming increasingly relevant for research, policy, and society.

Nancy specializes in designing and deploying production-ready intelligent systems solutions that perform reliably under real-world conditions. Her research focuses on developing inclusive AI tools that facilitate the daily lives of people with disabilities. In particular, she works on resource constrained architectures and speech processing, aiming to create accessible, real-time interfaces that function efficiently even on embedded or low-power systems.

In her Master’s thesis at Cardo Systems, Nancy engineered a high performance Automatic Speech Recognition (ASR) command model for voice-enabled agents. By utilizing Knowledge Distillation to compress models from 1GB to a custom RNN-Transducer architecture (<500K parameters), she achieved a 75% reduction in latency. This technical milestone is a key step toward making voice technologies more responsive and accessible in everyday, resource-constrained contexts.

Beyond speech AI, Nancy brings experience in building end-to-end Retrieval-Augmented Generation (RAG) systems using LangGraph, fine-tuning Large Language Models via LoRA, and orchestrating high-scale cloud infrastructure on AWS. Her profile combines deep technical expertise with a clear societal focus aligning closely with the vision of Prof. Barbareschi’s chair: developing AI systems that are inclusive by design rather than exclusionary by default.

Nancy is also a former winner of the Facebook Women Hackathon and an active contributor to the open-source community, where she develops tools for semantic search and multimodal document analysis.

With Nancy Bou Kamel joining Prof. Barbareschi’s team, the chair further expands its capacity to develop AI systems that are technically robust, socially responsible, and practically deployable.