Computational Behaviour Analysis for Human Digital Twins

Summary

Computational Behaviour Analysis (CBA) is an emerging interdisciplinary research area that draws equally from computer science and the study of human behaviour. It is intended to develop computational models and methods to represent and analyse human behaviour and their dynamics – a key element towards creating a human digital twin (HDT) – a digital replica of a human. Its ultimate purpose is to quantitatively assess the quality of human behaviour, identify long-term patterns and predict behaviour trajectories, thus recognising changes and potential behaviour projection. CBA plays a critical role for continuous, reproducible, and more objective assessments of human behaviour, and simulation-based prediction through digital twin and real human interactions. CBA is built upon but goes beyond activity modelling and recognition.

Such a quantitative assessment of the quality of relevant behaviours essentially corresponds to the analysis of how (well) activities are performed and has the quality of these activities changed. It is the central component of a human digital twin in a digital world which imitates and manifests the exact same behaviours as humans in the real world. Nevertheless, given the differences among individuals and the evolutionary nature of human behaviour, the capabilities of existing approaches to CBA are rather limited.

For analysing human behaviour and their dynamics digital twinning requires: (i) robust bootstrapping techniques for model estimation that draw from both domain knowledge and task-specific sample data at different levels of abstraction; (ii) adaptation techniques for data-driven personalization of statistical behaviour models; (iii) behaviour dynamic modelling to capture and model the changing nature of behaviours; and (iv) approaches for unsupervised modelling of “normal” behaviour and automatic detection of deviations from it. CBA for HDT has so far received little attention; the research is still in its infancy.

This project will bridge the aforementioned knowledge gap by developing (a) an enhanced behaviour model based on specific application context; (b) the evolution mechanisms of the model to capture behaviour dynamics from specific application scenario; (c) model based behaviour simulation and trajectory prediction methods.

Central to the above research is the development of core digital markers which can best characterise human behaviour and their dynamic changes. Subsequently they will be used for change detection and projection of future behaviour and consequences for various application scenarios.

This proposed research will be undertaken under the initiative of PwC’s Advanced Research and Engineering Centre (ARC), in collaboration with two NI Universities supported by a £6.7M funding. The application scenario will be  based on either digital health or process automation and robotics in digital transformation and empowerment.

The award holder will work as part of the ARC team in Ulster University in the brand-new ARC research lab in the University’s new Belfast campus, able to interact with PwC’s ARC team as well as fellow researchers in the Pervasive Computing and Artificial Intelligence Research Centres in the School of Computing.

In addition to the standard DfE studentship, covering tuition fees and living stipend, the awardee of this studentship will receive £6000 top-up stipend per academic year, £18,000 in three years.

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.

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.

  • First Class Honours (1st) Degree
  • Masters at 70%
  • Experience using research methods or other approaches relevant to the subject domain
  • Work experience relevant to the proposed project
  • Publications - peer-reviewed

Funding and eligibility

The University offers the following levels of support:

Department for the Economy (DFE)

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £18,000 (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

In addition to the standard DfE studentship, covering tuition fees and living stipend, the awardee of this studentship will receive £6000 top-up stipend per academic year, £18,000 in three years.

The Doctoral College at Ulster University

Key dates

Submission deadline
Thursday 5 January 2023
04:00PM

Interview Date
January 2023

Preferred student start date
As soon as possible

Applying

Apply Online  

Contact supervisor

Professor Luke Chen

Other supervisors

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