I have an interdisciplinary background in Transportation, Computer Science and Information Technology. My main expertise are: Big Data Analytics, Large-Scale Optimization, Public Transport, Demand Management, and Shared Mobility. My general area of research is at the intersection of optimisation, machine learning, and computer simulation. Under the umbrella of buzz words ‘big data’, ‘IoT’, and ‘sharing economy’, my research focuses on the inference (understand), prediction (inform) and optimisation (design), through the integration of novel data sources, mostly from connected devices or infrastructures, into mathematical learning models.
Accelerating the adoption of technological advances as the foundation for innovation is an important means to increase public transport appeal and hence, its use as the preferred mode will be directly related to reducing congestion in urban areas. Technological advances include mobile sensors (e.g., smart card, WiFi) that allow the collection of diverse data and direct customer communications. This data supports the development of customer-centric performance metrics, measures of equity and inclusion to inform policy, and information for better planning of operations and services. Technological advances also include the new on-demand services (e.g., Uber, DiDi) that currently impact ridership of public transport. However, they also offer opportunities for improving public transport accessibility via partnerships. In this context, leveraging on my interdisciplinary background (IT, Computer Science and Transportation), my research activities in this area center around transforming public transport using technology as a new foundation in operations, planning and control, and designing mobility-as-a-service platform for innovation in multimodal service delivery.
New vehicle technologies (e.g., connected, autonomous vehicles), emerging service models (e.g., on-demand shared mobility,) and innovative mobility concepts (e.g., mobility as a service) constitute the primary sources of ongoing and future changes in mobility landscape. They offer the promise to improve flexibility and accessibility, however not the certainty of delivering better services, liveable and sustainable cities. The uncertainty rests not only on technologies but also on users (needs, ownership) and policies, as well as where the balance between new services and private car use may settle. In light of these requirements, my research vision aims at exploring opportunities and designing services to shape how the future mobility system together with travel demand management (TDM) and information provision could potentially deliver better and sustainable urban mobility solutions.