PhD Study : Towards Trusted Cognitive Intelligence for User-centric Smart Systems

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Summary

Data Analytics has evolved over the years from Descriptive (what has happened) to Diagnostic (why did it happen) to Predictive (what could happen) and Prescriptive (what action could be taken). It is currently in the process of shifting towards Cognitive Analytics, which aims to create cognitive capabilities by learning from interactions with humans, environments and situated artifacts. In parallel, Computational Intelligence (CI), predominantly built upon data analytics, has recently made significant progress owing to increased computation power, improved machine learning algorithm performance, and the availability of big data. It has shown huge potential and to some extent reached industrial strengths offering real- world deployment opportunities such as face-recognition-based security checks and image analysis based medical diagnosis.  Nevertheless, CI based applications suffer from challenges around explanability and interpretability due to the opaque nature of learning algorithms. This can lead to the lack of trust and has been identified as a key barrier to the uptake and acceptability of AI innovations.

There is also a gap from the knowledge learned (models and patterns) to problem-solving, namely the capabilities of reasoning and inference compared with application business logic for decision support or application specific functions. Existing CI techniques are still struggling in reasoning and inference. Both data analytics and CI highlight the need of trusted cognitive intelligence in terms of technological evolution of AI techniques as a daily technology and their adoption at scale becoming a driver for economy development.

This project aims to address the aforementioned challenge by marrying strengths of computational intelligence, data analytic and human-level intelligence. It will develop models, algorithms, methods and technologies that enable and support the synergy, symbiosis, and augmentation of human and artificial intelligence. Specifically, the project will first develop symbolic modelling and representation of human-level cognition and decision-making processes, then explore two approaches to enhancing CI systems with explainable and interpretable capabilities. The first is to develop methods to bootstrap or train CI algorithms with the semantic, expandable cognitive models, thus making the CI based learnt findings explainable and interpretable. The second approach is to view CI-based agent/systems and humans as a hybrid intelligent system combining machines' strengths in effective and efficient discovery of implicit knowledge or hidden patterns from large-scale data, and humans’ advantage of conducting cognitive analysis such as reasoning and making instinct judgments under dynamic and multiple factors.

The project will focus on developing methods and mechanism for shared awareness and the collaborative ways, i.e. joint plans and strategies, to achieve shared goals with appropriate explanations in different circumstances and for different purposes. The project is aimed at developing generalizable advanced AI techniques applicable to different use scenarios such as smart healthcare and personalized learning, esp. for people with cognitive impairment. It is expected to generate high-value scientific outputs in top-tier journals and provide inputs to research grant applications. The project is built upon extensive research expertise on data analytics, AI and cognitive analytics in School of Computing, and promote Ulster’s strategic research directions under ongoing initiative such as data science, CARL and AI Centre of excellence.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

  • Sound understanding of subject area as evidenced by a comprehensive research proposal

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • Publications record appropriate to career stage
  • A comprehensive and articulate personal statement
  • Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.

Funding and eligibility

The University offers the following levels of support:

Vice Chancellors Research Studentship (VCRS)

The following scholarship options are available to applicants worldwide:

  • Full Award: (full-time tuition fees + £19,000 (tbc))
  • Part Award: (full-time tuition fees + £9,500)
  • Fees Only Award: (full-time tuition fees)

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.

  • Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
  • Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
  • Other non-ROI EU applicants are ‘International’ are not eligible for this source of funding.
  • Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living

The Doctoral College at Ulster University

Key dates

Submission deadline
Friday 7 February 2020
12:00AM

Interview Date
Late March 2020

Preferred student start date
Mid September 2020

Applying

Apply Online  

Contact supervisor

Professor Luke Chen

Other supervisors