With the evolution of mobile communication, crowdsourcing has shown its irreplaceablity in our life. In 2021, Uber drivers completed 6.3 billion trips, a 26% increase year-on-year, 118 million users used Uber, generating $17.4 billion revenue, a 56% increase year-on-year. The Worldwide AI Spending Guide from International Data Corporation forecasts global spending on AI systems will pass $300 billion in 2026 with a 26.5% annual growth rate for 2022-2026, and the product recommendations are involved in two top AI use cases, accounting for 12% of total revenue. A large portion of online activities are for crowdsourcing services, from finance to education and health. Data-driven innovation including crowdsourcing is transforming Australia's economy and society, improving the growth and prosperity. It is timely to conduct research on advanced spatial crowdsourcing analytics for various applications.
This project aims to create a next generation recommender system that enables enhanced task allocation and route recommendation on spatial crowdsourcing platforms. The new Crowd-guided Advanced Spatial Crowdsourcing Analytics (CASCA) system will be effective, efficient, crowd-guided, and situation-aware. By enhancing the capabilities of platforms and optimising the service and route recommendation in offline-to-online digital marketing and sharing economy, significant economic and social benefits will be brought to government, society, enterprises, and users.
Scholarships are valued at $AUD35,886 per annum (plus increment) for three years. Tuition fees will be waived by the university. The positions are open now, and will be open until they are filled. There are up to 4 international PhD scholarships available.
This is an international collaboration project involving RMIT University (Xiangmin Zhou, Jeffrey Chan), Hong Kong University of Science and Technology (Lei Chen), and Athena Research & Innovation Center (Timos Sellis).
*****Research Topics*****
* Develop effective strategies to manage large-scale crowdsourcing data for Crowd-guided Advanced Spatial Crowdsourcing Analytics.
* Apply big data processing framework and design resource allocation and monitoring techniques to enable the real-time responsible crowdsourcing task allocation and route planning.
* Develop a workable system that will be employed as showcase for Crowd-guided Advanced Spatial Crowdsourcing Analytics.
*****What we expect from you*****
Required:
* A first-class honours degree in Computer Science;
* A MS degree in Computer Science with a major thesis component.
* Ranked in the top 10% in your class at a reputable national university; or
* Ranked in the top 30% of your class at a Top 100 research university by world standards.
* Research background on social media analysis, recommender systems, database system or data mining areas.
In addition, having one or more of the following is desirable:
* A personal recommendation describing your research abilities from someone known by the supervisors, or a well-known research leader in a closely related field;
* Outstanding programming ability as evidenced by a history of open source contributions through GitHub or other means.
*****Interested?*****
Express your interests and send me your application support documents including (i) cover letter expressing your motivations and ambitions, (ii) your CV, (iii) copies of all academic qualifications, and (v) other relevant documents.