Real-Time User Sentiment Prediction for Ambient Aw...
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Real-Time User Sentiment Prediction for Ambient Aware Personalised Recommendation Systems using Deep Learning Spatial-Temporal Models

Eligibility: UK/EU/International

Award Details: No award (self-funding)

Duration: Full Time - 3 years 6 months fixed term; Part Time - 5 years fixed term

Application deadline: Ongoing 

Informal enquiries are essential before application; contact Dr. Rahat Igbal to discuss this opportunity.

Congratulations on taking your first steps toward a Research Degree with Coventry’s Faculty of Engineering, Environment and Computing. As an ambitious and innovative University, we’re investing an initial £100m into our new research strategy, ‘Excellence with Impact’. Through original approaches from world-leading experts, we’re aiming for our research to make a tangible difference to the way we live. As a research student you are an integral part of Coventry’s lively and diverse research community and contribute to our reputation for excellence. With our exceptional facilities and superb support mechanisms you are afforded every opportunity for academic success.

The Project

The ever growing number of embedded and networked enabled physical devices collectively termed as the ‘Internet of Things (IoT) has become an enabler for facilitating richer context awareness, personalisation through integration of intelligence, into everyday consumer devices. The global IoT market is expected to hit $7.1 trillion by 2020 (IDC) and is projected to drive the circulation and use of some 50 billion connected devices. This influx of personal, mobile and wearable devices requires human centered technologies to more effectively understand user behaviour, preferences, though interpreting their behaviours and sentiments in order to provide appropriate, timely and effective recommendations pertaining to the users context and needs. This level of user awareness and personalisation can benefit ubiquitous connected ecologies of people, artefacts and the environment as can found with the emergence of smart cities and wider digital economies and societies. The proposed research aims to monitor and model of user level sentiment influencing their behaviours through the use of personal and pervasive computing artefacts and novel computational intelligence techniques. Generate more effective recommendation delivery based on identifying users current needs, activity and usage patterns of ubiquitous computing artefacts.

About the Centre/Department

Our research in Mobility & Transport works across our faculties and focuses on the design and engineering of future transport systems, including the growing influence of the internet and connectivity. The focus is on inclusive, sustainable and safe transport integrating the strongest research elements in design and engineering. The Centre currently has around 50 staff and 70 PhD students.

Successful Applicants

  • A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the Project element or equivalent with a minimum 60% overall module average, or
  • A Masters Degree in a relevant subject area will be considered as an equivalent. The Masters must have been attained with overall marks at merit level (60%). In addition, the dissertation or equivalent element in the Masters must also have been attained with a mark at merit level (60%).
  • The potential to engage in innovative research and to complete the PhD within a prescribed period of study
  • Language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component).

Eligibility & Application Procedure

Eligibility:

All UK/EU/International students are eligible to apply that meet the academic requirements, the eligibility criteria can be found making an application page.