Dr Zhibao Mian

Dr Zhibao Mian

Lecturer

+44 (0)1482 462017 | Z.Mian2@hull.ac.uk

Faculty and Department

  • Faculty of Science and Engineering
  • School of Computer Science

Related groups

  • Computer Science

Qualifications

  • MSc (University of Nottingham)
  • PhD / DPhil (University of Hull)

Summary

Dr. Mian is currently serving as a lecturer in the School of Computer Science at the University of Hull. Prior to his return to Hull, he held the position of Associate Professor in the School of Computer Science at Northwest Normal University.

Dr. Mian is actively seeking for highly motivated MSc (Research) and PhD students, for informal inquiries, please contact him at z.mian2@hull.ac.uk.

Live PhD positions with SCHOLARSHIP:

[1] SafeML-based Confidence Generation and Explainability for UAV-based Anomality Detection of Blades Surface in Offshore Wind Turbines, https://auracdt.hull.ac.uk/research-projects/safeml-based-confidence-generation-and-explainability/

[2] A Holistic Predictive Maintenance Framework for Offshore Wind Turbines Components, https://auracdt.hull.ac.uk/research-projects/a-holistic-predictive-maintenance-framework-for-offshore-wind-turbines-components/

[3] An RCM-based Intelligent Maintenance Framework for Offshore Wind Turbines, https://auracdt.hull.ac.uk/research-projects/an-rcm-based-intelligent-maintenance-framework-for-offshore-wind-turbines/

[4] The China Scholarship Council (CSC) PhD scholarship programme scheme, which provides funding to Chinese nationals for a range of PhD programmes. The scholarship enables talented Chinese students to undertake a PhD programme at the University of Hull, building on Hull’s strong relationship with China.

Live PhD positions:

[1] Integrating AIs into model-based intelligent maintenance: https://www.hull.ac.uk/study/postgraduate/research/phd/non-funded/integrating-ais-into-model-based-intelligent-maintenance

[2] Dr. Mian welcome prospective PhD candidates to engage in discussions on additional interesting and relevant topics.

441105 - Algorithms and Data Structures

500083 - Advanced Programming

500091 - Year Out in Industry/Commerce

551456 - Software Engineering Design Patterns

551462 - Design, Develop, Deploy

600091 - Honours Stage Project

700031 - The Modern Researcher 1: Essential Skills, Knowledge and Training

700099 - MSc Dissertation

700105 - Games Achitecture and Concurrency

700109 - Advanced Computational Science

700111 - Development Project

771952 - MSc AI Project (Online)

Recent outputs

View more outputs

Journal Article

An Ordinal Collaboration Network Model with Zero Truncated Poisson Latent Variables and Its Application

Yang, Q., Tian, Y.-Z., Zhang, Y.-J., Wang, Y., & Mian, Z. (2025). An Ordinal Collaboration Network Model with Zero Truncated Poisson Latent Variables and Its Application. Stat, 14(1), Article e70040. https://doi.org/10.1002/sta4.70040

Sequence Outlier Detection and Application of Gated Recurrent Unit Autoencoder Gaussian Mixture Model Based on Various Loss Optimization

Xu, T., Tian, Y., Wu, C., & Mian, Z. (2025). Sequence Outlier Detection and Application of Gated Recurrent Unit Autoencoder Gaussian Mixture Model Based on Various Loss Optimization. Statistical Analysis and Data Mining, 18(1), Article e70001. https://doi.org/10.1002/sam.70001

Analysis of the influencing factors of the trade potential between countries along the 'Belt and Road' and China: a study based on spatial panel data model

Zhang, F. L., Tian, Y., Lam, L. K., & Mian, Z. (online). Analysis of the influencing factors of the trade potential between countries along the ‘Belt and Road’ and China: a study based on spatial panel data model. Enterprise Information Systems, https://doi.org/10.1080/17517575.2024.2448315

A new class of zero-truncated counting models and its application

Tang, X. P., Tian, Y. Z., Wu, C. H., Wang, Y., & Mian, Z. B. (2024). A new class of zero-truncated counting models and its application. Communications in Statistics - Simulation and Computation, https://doi.org/10.1080/03610918.2024.2384561

An empirical analysis of agricultural and rural carbon emissions under the background of rural revitalization strategy–based on machine learning algorithm

Niu, X. Y., Tian, Y. Z., Tang, M. L., & Mian, Z. B. (2024). An empirical analysis of agricultural and rural carbon emissions under the background of rural revitalization strategy–based on machine learning algorithm. Air Quality, Atmosphere and Health, https://doi.org/10.1007/s11869-024-01606-2

Research interests

My research interests center on trustworthy and responsible AI, machine learning, large language models (LLMs), and the application of AI across various domains, including education (teaching, learning, and assessment), business, healthcare, economics and society.

Recently, my primary focus has been on developing a trustworthiness assessment framework for the design, development, and deployment of AI-based systems. This work involves evaluating AI systems for bias, robustness, safety, fairness, explainability, ethical considerations, and related sociotechnical safety factors.

I am also interested in integrating cutting-edge technologies such as AI, IoT, Big Data, Blockchain, and Digital Twins into the field of intelligent asset maintenance within the context of industry 4.0 and 5.0.

Previously, I have conducted research in system safety analysis, reliability-centred maintenance (RCM), and intelligent maintenance. I remain keen on exploring the integration of AI and LLMs into model-driven engineering (MDE), model-based safety analysis, automated model transformations, and their validation and verification.

Dr. Mian is actively looking for prospective Ph.D. students, for informal inquiries, please contact him at z.mian2@hull.ac.uk.

Lead investigator

Project

Funder

Grant

Started

Status

Project

Use of Foundational AI in teaching and assessment – A practical case study in software engineering education

Funder

Council of Professors and Heads of Computing (CPHC)

Grant

£4,980.00

Started

1 February 2024

Status

Complete

Postgraduate supervision

Live PhD positions with SCHOLARSHIP:

[1] SafeML-based Confidence Generation and Explainability for UAV-based Anomality Detection of Blades Surface in Offshore Wind Turbines, https://auracdt.hull.ac.uk/research-projects/safeml-based-confidence-generation-and-explainability/

[2] A Holistic Predictive Maintenance Framework for Offshore Wind Turbines Components, https://auracdt.hull.ac.uk/research-projects/a-holistic-predictive-maintenance-framework-for-offshore-wind-turbines-components/

[3] An RCM-based Intelligent Maintenance Framework for Offshore Wind Turbines, https://auracdt.hull.ac.uk/research-projects/an-rcm-based-intelligent-maintenance-framework-for-offshore-wind-turbines/

[4] The China Scholarship Council (CSC) PhD scholarship programme scheme, which provides funding to Chinese nationals for a range of PhD programmes. The scholarship enables talented Chinese students to undertake a PhD programme at the University of Hull, building on Hull’s strong relationship with China.

Live PhD positions:

[1] Integrating AIs into model-based intelligent maintenance: https://www.hull.ac.uk/study/postgraduate/research/phd/non-funded/integrating-ais-into-model-based-intelligent-maintenance

[2] Dr. Mian welcome prospective PhD candidates to engage in discussions on additional interesting and relevant topics.

Committee/Steering group role

Executive member of CCF Embedded System Committee

2021

Conference organisation

Chair of international conferences

2024

2024 CLNLP (Publicity Chair); 2024 National conference on Flexible Electronics (Sub-forum Chair)

Consultancy/Industry advisory role

Maintenance advisor

2021

For the Kocel Group Limited company.

External examiner role

National postgraduate education evaluation and monitoring examiner

2021

National postgraduate education evaluation and monitoring examiner in Chinese Ministry of Education, responsible for PhD and MSc research thesis sampling and quality audit in Computer Science and Technology and professional degree level assessment and discipline evaluation.

Honorary position

Exceptional Talent

2024

I have been endorsed as Exceptional Talent in SE by the Royal Academy of Engineering in 2024.

Journal editorial role

Journal Editor

2023

American Journal of Artificial Intelligence, Jisuanji Gongcheng/Computer Engineering, Information, MDPI Electronics.

Journal peer reviewer

Journal and Conference Riewer

2022

I am invited for top journals and conferences reviewer including JSS, CMC, Jisuanji Gongcheng/Computer Engineering, MDPI Electronics, MDPI Applied Sciences, MDPI Future Internet, EAAI, RESS, JSA, J. Autonom. Intell., INT J BIOMATH, Insight.

Membership/Fellowship of professional body

Senior Fellow (Higher Education Academy)

2024

Research assessment service

Research project reviewer

2023

The UKRI Talent Peer Review College (PRC), The UK-ISPF reviewer for British Council.

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