About

I am an Associate Professor and Programme Leader of three MSc Programmes in the School of Computing at the University of Derby. My teaching expertise is in Data Science and Machine Learning. I am a very active researcher as a member of the Data Science Research Centre at the University.

Before joining the University of Derby, I worked as Senior Lecturer in Data Science and a Course Leader for MSc Sensor and Smart Cities.

I have been involved in more than ten research projects that mostly were supported by Innovate UK and European Committee Research Frameworks and regional SME development frameworks. I obtained PhD award from the University of Leicester in 2009 and continued my research in the fields of Data/Text Mining, Semantic technologies, Deep Machine Learning and Natural Language Processing for healthcare, multimedia and learning systems.

Teaching responsibilities

I am the MSc Programme Leader and Chair for PGT Computing programme committees in the School, as well as the module leader for Data Mining and Foundations of AI.

I have a rich PhD supervising experience with 12 PhD students has been graduated or current working with me in the University of Derby.

Some of the PhD students I have supervised have completed the following dissertations: 

• Abdul Saleem (2017 - 2021), "Presence Aware Power Saving Mode (PA-PSM) Enhancement for IoT Devices for Energy Conservation", publication: Presence Aware Power Saving Mode (PA-PSM) Enhancement for IoT Devices for Energy Conservation, Open Journal of Energy Efficiency 2019 08(03):95-128
• Nicholas Collis (2015 - 2021), "Aquacold - a crowdsourced query understanding and query construction tool for the linked data web"
• Hui Wei (2017 - 2020), "Deep Learning with the context of Natural Language Processing-Improved Parallel CNN Computation", publication: Efficient Non-fused Winograd on GPUs. CGI 2020: 411-418
• Saber Farag (2015 - 2018), "A Novel Disparity-Assisted Block Matching-Based Approach for Super-Resolution of Light Field Images"
• Fahad Alanezi (2014 - 2017), "A Study on Perception of Managing Infectious Disease through Social Networking", publication: Infectious Disease Management Systems in the Gulf Region: The Current Status and Potential Impact, 2016 IEEE Intl Conference on Computational Science and Engineering

Research interests

My current research is in wide areas of Data Science and Machine Learning. The main theme is knowledge discovery and representation from cutting-edge technologies (Data/Text Mining, Semantic technologies, Deep Machine Learning and Natural Language Processing) for supporting industry automation, digital twins and healthcare systems.

There are five major research strands that I am currently working on:

1. Applying advanced AI technologies such as Transformers and Large Language Model to support business and industry automations. 
2. Trustable and Explainable AI technologies.  
3. Health-related Causality Analysis and Discovery through multiple trusted data resources and different formats (Literature, images and clinical dataset)
4. IoT-led context-aware machine learning system to support runtime application systems

I am pursuing research collaborations at all levels with organisations, SMEs or individuals who are interested in or can get benefits from my research work

The projects I have been involved with are as follows:

• Inspector Plus / Project number: 10079284 / Competition: NATEP Helping SMEs innovate in aerospace: Spring 2023 (PI)
• Deep Learning for Engineering Inspection/ Application number: 10080115 / Competition: Feasibility studies for Artificial Intelligence solutions (Co-PI)
• Technology Consultant for supervising students working on ICT Escalator, Innovation Bridge and IMAGE EC funded UK regional projects (PI)
• MyHealthAvatar (WP 4): A Demonstration of 4D Digital Avatar Infrastructure for Access of Complete Patient Information, EU FP7-ICT- 600929, 2013-2016 (Co-PI)
• mEducator (WP leader & replaced principal investigator), Multi-type Content Repurposing and Sharing in Medical Education, EU eContentplus programme, 2009-2012 (Co-PI)
• VPN-Share (co-investigator): Virtual Physiological Human: Sharing for Healthcare, EU FP7-ICT-269978, 2011-2015 (Co-PI)
• EUCLID: Educational curriculum for the usage of Linked Data, EU FP7-ICT-296229, 2012-2014 (Co-PI)
• SugarTube (principal investigator): Semantics Used to Get Annotated video Recording, the Open University, 2011 (PI)
• NoTube: Networks and ontologies for the transformation and unification of broadcasting and the Internet, EU FP7-ICT-231761, IP, 2009-2012 ((Co-PI))
• SOA4ALL, Service-oriented architectures for All, EU FP7-ICT-215219, IP, 2008-2011
• SENSORIA: Software Engineering for Service-Oriented Overlay Computers, EU FP6-IST-2005-16004, 2005-2009
• inContext: Interaction and context-based technologies for collaborative teams, EU FP6-IST-2006-034718, 2006-2008

Qualifications

• Senior Fellowship of Higher Education Academy
• Fellowship of Higher Education Academy

Recent conferences

• Q. Bamboat and H. Q. Yu, "Literature Study on Bias and Fairness in Machine Learning Systems," 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Exeter, United Kingdom, 2023, pp. 1960-1965, doi: 10.1109/TrustCom60117.2023.00267
• J. Pimentel, A. A. McEwan and H. Q. Yu, "A Comprehensive Machine Learning Methodology for Embedded Systems PHM," 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Exeter, United Kingdom, 2023, pp. 1954-1959, doi: 10.1109/TrustCom60117.2023.00266
• Yu, H.Q., Alaba, A., Eziefuna, E. (2024). Evaluation of Integrated XAI Frameworks for Explaining Disease Prediction Models in Healthcare. In: Qi, J., Yang, P. (eds) Internet of Things of Big Data for Healthcare. IoTBDH 2023. Communications in Computer and Information Science, vol 2019. Springer, Cham. https://doi.org/10.1007/978-3-031-52216-1_2
• J. Pimentel, A. A. McEwan and H. Q. Yu, "A Novel Real-Time Framework for Embedded Systems Health Monitoring," 2023 26th Euromicro Conference on Digital System Design (DSD), Golem, Albania, 2023, pp. 309-316, doi: 10.1109/DSD60849.2023.00051
• J. Pimentel, A. A. McEwan and H. Q. Yu, "Towards a Real-Time Smart Prognostics and Health Management (PHM) of Safety Critical Embedded Systems," 2022 25th Euromicro Conference on Digital System Design (DSD), Maspalomas, Spain, 2022, pp. 696-703, doi: 10.1109/DSD57027.2022.00098
• Yu, H. Q., Dynamic Causality Knowledge Graph Generation for Supporting the Chatbot Healthcare System, Future Technologies Conference (FTC) 2020
• H. Q. Yu, Experimental Disease Prediction Research on Combining Natural Language Processing and Machine Learning, 2019 IEEE 7th International Conference on Computer Science and Network Technology (ICCSNT), 2019, pp. 145-150
• H. Q. Yu, Mining Symptom and Disease Web data with NLP and Open linked Data, 5^th International Conference On Machine Vision and Machine Learning (MVML’19), 21-23 August 2019, Lisbon, Portugal
• H. Q. Yu, X. Zhao, Z. Deng, F. Dong, Healthcare-Related Data Integration Framework and Knowledge Reasoning Process. KMO 2017: 386-396
• Joy Eze, Sijing Zhang, Enjie Liu, Elias Chinedum Eze, Hong Qing Yu: Cognitive Radio Aided Internet of Vehicles (IoVs) for Improved Spectrum Resource Allocation. CIT/IUCC/DASC/PICom 2015: 2346-23

Recent publications

Journals:

• Yu, H.Q., O’Neill, S., Kermanizadeh, A. AIMS: An Automatic Semantic Machine Learning Microservice Framework to Support Biomedical and Bioengineering Research. Bioengineering 2023, 10, 1134. https://doi.org/10.3390/bioengineering10101134
• Yu, H. Q., & Reiff-Marganiec, S. (2022). Learning Disease Causality Knowledge From the Web of Health Data. International Journal on Semantic Web and Information Systems (IJSWIS), 18(1), 1-19. http://doi.org/10.4018/IJSWIS.297145
• Yu, H. Q., Dong, F., Semantic Lifting and Reasoning on the Personalised Activity Big Data Repository for Healthcare Research, International Journal of Web Engineering and Technology (IJWET), 2019
• Saleem, Abdul & Jazani, David and Yu, Hong Qing. (2019). Presence Aware Power Saving Mode (PA-PSM) Enhancement for IoT Devices for Energy Conservation. Open Journal of Energy Efficiency. 08. 95-128. 10.4236/ojee.2019.83007
• Jonathon Handscombe, Hong Qing Yu, Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System. Sensors 19(2): 347, 2019
• Zhao, X., Yu, H. Q., Liu, E., A Linear Logic Approach to the Composition of RESTful Web Services, International Journal of Web Engineering and Technology (IJWET), Volume 10 Issue 3, October 2016 Pages 245-271
• Dietze, S., Kaldoudi, E., Dovrolis, E., Giordano, D., Spampinato, C., Hendrix, M., Protopsaltis, A., Taibi, D., Yu, H. Q., Socio-semantic Integration of Educational Resources – the Case of the mEducator Project, in Journal of Universal Computer Science (J.UCS), Special Issue on International Research Projects on Socio‐Semantic Technologies Applied to Education, accepted for publication, 2013
• S. Dietze, , S. Sanchez-Alonso, H. Ebner, H. Q. Yu, D. Giordano,  I. Marenzi, B. Pereira Nunes, "Interlinking educational Resources and the Web of Data – a Survey of Challenges and Approaches", accepted for publication in Emerald Program: electronic Library and Information Systems, Volume 47, Issue 1, 2013
• H. Q. Yu, C. Pedrinaci, S. Dietze, and J. Domingue, "Using linked data to annotate and search educational video resources for supporting distance learning," IEEE Transactions on Learning Technologies, vol. 5, no. 2, pp. 130 –142, 2012
• H. Q. Yu, S. Dietze, C. Pedrinaci, and D. Liu, "A linked data compliant framework for dynamic and web-scale consumption of web services," International Journal of Computer Information Systems and Industrial Management Applications, vol. 3, pp. 796–803, 2011
• S. Dietze, A. Gugliotta, J. Domingue, H. Q. Yu, and M. Mrissa, "An automated approach to semantic web services mediation," Service Oriented Computing and Applications, vol. 4, no. 4, pp. 261–275, 2010

Courses

• Big Data Analytics MSc