Societal networks and urban systems can be improved using mathematical methods for analysis, design and optimization. Systems include transportation, health care, financial, water, waste management and emergency services, and they suffer from two major problems: a severe shortage of resource supply and excessive demand. Key outcomes involve using insights from data generated by these networks to improve the supply and curb demand, and large-scale deployments in cities around the world are a major result. Examples include:
- Designing "nudge" engines,
- Personalized recommendation engines,
- Big data algorithms and systems,
- Mobile phone-based sensing algorithms.