Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended ....Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.Read moreRead less
Human-Machine Teaming:Designing synergistic learning of humans and machines. This proposal investigates the design of systems in which humans and machines use their different abilities to learn together for mutual benefit. Machine learning has been commoditised, applied in areas such as medical image reading and autonomous vehicles, however it typically operates separately from humans, supplanting human skills and leading to deskilling. Using human-computer interaction research techniques, co-de ....Human-Machine Teaming:Designing synergistic learning of humans and machines. This proposal investigates the design of systems in which humans and machines use their different abilities to learn together for mutual benefit. Machine learning has been commoditised, applied in areas such as medical image reading and autonomous vehicles, however it typically operates separately from humans, supplanting human skills and leading to deskilling. Using human-computer interaction research techniques, co-design and iterative prototyping in the domains of radiology training and environmental learning, we will devise and evaluate exemplar systems that support humans to interactively frame problems, explore and learn, while utilising and improving machine models, leading to a guiding framework for designing human-machine teaming.Read moreRead less
Building crowd sourced data curation processes. This project aims to tackle the growing problem of data curation. The capacity to effectively utilise the increasing number of datasets available to organisations for timely decision making is diminishing, due to onerous data preparation and curation tasks that have to be performed before the data can be consumed by analytics platforms. The project will be a first attempt at using a novel process-oriented approach in micro-task crowdsourcing, and w ....Building crowd sourced data curation processes. This project aims to tackle the growing problem of data curation. The capacity to effectively utilise the increasing number of datasets available to organisations for timely decision making is diminishing, due to onerous data preparation and curation tasks that have to be performed before the data can be consumed by analytics platforms. The project will be a first attempt at using a novel process-oriented approach in micro-task crowdsourcing, and will create new knowledge to harness the full potential of crowd sourced data curation. This is expected to make a significant benefit towards enhanced organisational capacity to accelerate the time-to-value from data analytics projects.Read moreRead less
Effective, efficient and scalable processing of the graph of graphs. This project aims to develop novel approaches to realise the value of the graph of graphs (GoG), which has been widely used to capture the relations among the structured entities. Several key challenges will be addressed: better models to capture the similarity and cohesiveness of the structured entities, increased efficiency, and greater scalability of the processing and analytics of the GoG. The novel models and algorithms de ....Effective, efficient and scalable processing of the graph of graphs. This project aims to develop novel approaches to realise the value of the graph of graphs (GoG), which has been widely used to capture the relations among the structured entities. Several key challenges will be addressed: better models to capture the similarity and cohesiveness of the structured entities, increased efficiency, and greater scalability of the processing and analytics of the GoG. The novel models and algorithms developed within this project will be incorporated into a prototype for both evaluation and to demonstrate real-world practical value for business, industry, and academia. Success in this project should see significant benefits for many important applications such as health, cyber-security and e-commerce.Read moreRead less