The Interdisciplinary Ph.D. Track on AI and Data Science focuses on harnessing the big data revolution and artificial intelligence to better design, operate and manage the built environment and environmental systems. The data and methodological scope is defined broadly to encompass artificial intelligence, machine learning, complex networks, data mining, computer vision, graph analytics, deep learning, and natural language processing. This interdisciplinary track includes courses that balance data science methodology and disciplinary elements from different civil engineering areas.
Some of Our Research Specialties
- Urban intelligence and computing
- Automated infrastructure monitoring
- Transportation big data
- Disaster and multi-hazard engineering informatics
- AI-aided infrastructure engineering and management
- City-scale predictive analytics
- Data-driven approaches to understand environmental processes - including climate change - and aid sustainable decision-making