Artificial intelligence research theme

AI for optimising urban traffic management

Urban mobility is a growing challenge for rapidly expanding cities, where traffic congestion can affect productivity, sustainability and quality of life. This project explores how artificial intelligence can support smarter and more efficient traffic management in Dubai.

Funded by Dubai Future Foundation and led by Professor Nikolay Mehandjiev, the I-C-ROUTE project combines Generative AI, Multimodal Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) to identify similar traffic scenarios, predict journey times, and recommend effective traffic control strategies. The research will develop interpretable traffic-data embeddings, a natural-language interface and a semantic search platform capable of visualising predicted congestion and mitigation strategies using historical traffic data.

The project will support smarter mobility decisions and enhance traffic operations across Dubai. It also contributes to the development of ethical and interpretable AI, while strengthening the city's position as a leader in smart city innovation and applied artificial intelligence.

Type 2 diabetes (T2D) continues to present a major challenge to healthcare systems globally, including in the UAE. While previous studies have often focused on epidemiological or genetic risk factors in isolation, understanding how these factors interact remains a significant challenge.

Led by Dr Marc Haber in collaboration with the University of Birmingham Centre for Health Data Science and Mohammed Bin Rashid University of Medicine and Health Sciences, this project combines genomics, machine learning and artificial intelligence to investigate phenotypic differences and disease heterogeneity in T2D populations.

By analysing patterns associated with disease onset and prognosis, the research aims to support more personalised approaches to prevention, diagnosis and treatment, while advancing understanding of diabetes within the UAE population.