Senior Lecturer in Computer Science
My educational background and research experience are in Computer Science, Data Science and e-Science.
In 2007, I was awarded a PhD degree in Computer Science on the research topic of dynamic load balancing and communication latency optimisation of distributed simulations on computational grid at the University of Birmingham.
I was a Postdoctoral Research Fellow in Cloud Computing at the University of Leeds (2010-2013) and a Higher Scientific Officer (HSO) in e-Science at the Rutherford Appleton Laboratory and Daresbury Laboratory of Science and Technology Facilities Council (STFC) (2006-2010).
I am also a Fellow of Higher Education Academy (FHEA) and held a Postgraduate Certificate in Academic Practice since 2017.
My research interests are in the theories of Distributed Computing, Computational Intelligence, and Robotics and their applications in Digital Edutainment and Industry 4.0.
Helping enterprising students and graduates start up their own games studios or ICT businesses is also part of my broader teaching and research practices to promote and support student's digital E&I activities at the University Enterprise Zone Digital Incubator and Enterprise Place.
Teaching and supervision
- Introduction to Game Development
- Intermediate Software Development
- Advanced Software Development
- Data Visualisation
- Data Science Product Development
- Computer Science Principles and Practice
Research interests for potential research students
- Cloud computing
- Big data analysis and visualisation
- Intelligent robots
- Gamification for e-learning
2022: Projects at the Industry 4.0 Lab and Immersive Technology Lab (in progress)
With the newly established Industry 4.0 Lab and Immersive Technology Lab at FoT in 2021/2 academic year, I am actively supporting PhD students and colleagues at the School of Engineering to develop Smart Factories module and Industry 4.0 projects with my research experience in discrete event system modelling and simulation, IoT, and Virtual Reality technologies. More tbc.
2021: A Hybrid Machine Learning Approach for Customer Loyalty Prediction
H. F. Lee, Ming Jiang
Customer loyalty prediction is one of the most common applications of machine learning in Customer Relationship Management (CRM). Many research studies have tried to compare the effectiveness of different machine learning techniques applied for the model development. Also due to the simplicity and effectiveness, customer purchase behavioral attributes, such as, Recency, Frequency, and Monetary Value (RFM) are commonly used for predicting the customer lifetime value as a measure of loyalty. However, since RFM focuses on the purchase behaviours of customers only, it often overlooks the effect of other important factors to loyalty such as customer satisfaction and product experience. In this paper, a two-stage hybrid machine learning approach is designed to address this. Firstly, both unsupervised clustering and supervised classification model are used in the predication model building in order to realize the possible incremental value of hybrid model combining two learning techniques. Secondly, the proposed model is trained with behavourial RFM attributes and attitudinal factors such as customer satisfaction and product attributes, in order to better capture the influencing factors to loyalty. Full paper link.
2020: Reinforcement Learning (RL) Enhanced with Imitation Learning Strategy for Intelligent Non-Playable Character (NPC) Design in Virtual Reality Video Game
In this project, Reinforcement Learning (RL) enhanced with imitation learning strategy is developed to train an intelligent Non-Playable Character (NPC) agent (i.e., Rolling Ball) to chase after a randomly placed target (i.e., Cube) on a surface within its four boundaries. The RL approach enhanced with imitation learning strategy and the intelligent agent training system developed with Unity and Windows Mixed Reality platform can be extended and applied into a range of challenging and exciting scenarios of intelligent Virtual Reality game design and development or gamifications. Project Demo.
An Augmented Reality Demonstration Platform of the University of Sunderland One Campus Masterplan
Ming Jiang (University of Sunderland); Dorian Morax (University of Bordeaux).
The project designed and developed a portable Augmented Reality technology based immersive and interactive demonstration platform of the One Campus Masterplan of University of Sunderland to illustrate some of the key visionary concepts, such as the Campus Landscaping, and other major landmarks/sceneries on the One Campus envisaged by the Masterplan, which develops a single unified campus connecting the current City Campus to the South and Sir Tom Cowie Campus at Saint Peter’s to the North in the City of Sunderland. Project Demo.
A New Storytelling of Sistine Chapel Ceiling Frescoes in Mixed Reality
Ming Jiang (University of Sunderland); Gabriel Benit and Nicolas Deguillaume (University of Bordeaux).
The project developed an immersive and interactive Mixed Reality Sistine Chapel e-Learning Platform, on which the Renaissance genius Michelangelo’s sacred representations of humanity are demystified and appreciated with 21st century cutting edge digital technology. Project Demo.
Humanoid Robot as an e-Learning Companion
James Hennerley, Matthew Dickinson, and Ming Jiang, Augmented Reality Enhanced Human Robot Interaction for Social Robots as e-Learning Companions, Proceedings of the 31st International BCS Human Computer Interaction Conference (HCI 2017), University of Sunderland, Sir Tom Cowie Campus at St Peter’s, Sunderland, UK, 3 - 6 July 2017, HCI 2017 - Digital make-believe.
Conference or Workshop Item
Hennerley, James, Dickinson, Matthew and Jiang, Ming (2017) Augmented Reality Enhanced Human Robot Interaction for Social Robots as e-Learning Companions. In: HCI 2017 - Digital make-believe, 3 - 6 July 2017, University of Sunderland, St Peter’s campus, Sunderland, UK.
Jiang, Ming, Kirkham, T. and Sheridan, C. (2016) An Evolutionary Cultural Algorithm based Risk-aware Virtual Machine Scheduling Optimisation in Infrastructure as a Service (IaaS) CLoud. In: 6th International Conference of Cloud Computing and Services Sciences, 23-25 Apr 2016, Rome, Italy. (Unpublished)
I am passionate about data-centric knowledge discovery and digital innovations for solving challenging and interesting real-life problems:
- Distributed and scalable machine learning/data mining algorithms and services
- Intelligent and affective human-robot interactions
- QoS (eg risk, trust and security) modelling and assessments in Cloud/Grid infrastructures (IaaS) and services (SaaS)
- Program Committee Member of the Ninth International Conference of Cloud Computing and Services Science, Heraklion, Greece, 2-4 May, 2019
- Program Committee Member of the Eighth International Conference of Cloud Computing and Services Science, Funchal, Portugal, 19-21 March, 2018
- Program Committee Member of the British HCI Conference, Sunderland, UK, 3-6 July, 2017
- Program Committee Member of the Seventh International Conference of Cloud Computing and Services Science, Porto, Portugal, 24-26 April, 2017
- International Program Committee Member of the INNS Conference on Big Data (INNSBIGDATA 2016), Thessaloniki, Greece, 23-25 October 2016
- Program Committee Member of the Sixth International Conference of Cloud Computing and Services Science, Rome, Italy, 23-25 April, 2016
- Program Committee Member of the Fifth International Conference of Cloud Computing and Services Science, Lisbon, Portugal, 20-22 May, 2015
- Program Committee Member of the Fourth International Conference of Cloud Computing and Services Science, Barcelona, Spain, 3-5 April, 2014
- Technical Program Committee Member of CLOUD COMPUTING 2013: The Fourth International Conference on Cloud Computing, GRIDs, and Virtualization, Valencia, Spain, May 27 - June 1, 2013
- Technical Program Committee Member of CLOUD COMPUTING 2012: The Third International Conference on Cloud Computing, GRIDs, and Virtualization, Nice, France 22-27 July 2012