Dr Thomas Tan

MemCrypt Limited
2021

Recognition Type Spin-outs and Licences

Research Areas Cyber-security

Research Themes AI and Technologies

Research Centres/Groups Centre for Cybersecurity, IoT and Cyberphysical Systems

Projects MemoryCrypt

Org Units School of Computing Engineering and the Built Environment

Recognition Type	Spin-outs and Licences
Research Areas	Cyber-security
Research Themes	AI and Technologies
Research Centres/Groups	Centre for Cybersecurity, IoT and Cyberphysical Systems
Projects	MemoryCrypt
Org Units	School of Computing Engineering and the Built Environment

Guest Editor, Special Issue on TinyML Empowered Intelligent Systems for Computers & Electrical Engineering (ISSN: 0045-7906)
2024 - 2025

Recognition Type Editorial Activity

Research Areas Optimisation and learning

Research Themes AI and Technologies

Research Centres/Groups Centre for Cybersecurity, IoT and Cyberphysical Systems

Org Units School of Computing Engineering and the Built Environment

Recognition Type	Editorial Activity
Research Areas	Optimisation and learning
Research Themes	AI and Technologies
Research Centres/Groups	Centre for Cybersecurity, IoT and Cyberphysical Systems
Org Units	School of Computing Engineering and the Built Environment

Associate Editor, Cureus Journal of Computer Science (ISSN: 3005-1487)
2024

Recognition Type Editorial Activity

Description Dr Zhiyuan Tan has been appointed as an Associate Editor of The Cureus Journal of Computer Science since July 2024. The journal is a peer-reviewed, open-access publication focused on high-quality research in computer science. The journal emphasizes rapid publication to quickly share innovative ideas and advancements. By providing free access, it promotes global collaboration among researchers, practitioners, and academicians.

Research Areas Cyber-security
Smart cities

Research Themes AI and Technologies

Research Centres/Groups Centre for Cybersecurity, IoT and Cyberphysical Systems

URL https://www.cureusjournals.com/journal/computer-science

Recognition Type	Editorial Activity
Description	Dr Zhiyuan Tan has been appointed as an Associate Editor of The Cureus Journal of Computer Science since July 2024. The journal is a peer-reviewed, open-access publication focused on high-quality research in computer science. The journal emphasizes rapid publication to quickly share innovative ideas and advancements. By providing free access, it promotes global collaboration among researchers, practitioners, and academicians.
Research Areas	Cyber-security Smart cities
Research Themes	AI and Technologies
Research Centres/Groups	Centre for Cybersecurity, IoT and Cyberphysical Systems
URL	https://www.cureusjournals.com/journal/computer-science

Guest Editor: Research Topic on Emerging Technologies, Challenges and Solutions for Zero Trust for Frontiers in Communications and Networks (Electronic ISSN 2673-530X)
2023 - 2024

Recognition Type Editorial Activity

Description Recently, more and more organizations have embraced the zero-trust technologies due to minimizing risk in enforcing accurate, least privilege per-request access decisions in service applications under the circumstance of a compromised network. In a zero-trust architecture, each access request should be authenticated and evaluated whether the request is permitted no matter it originated from external or internal network. In addition, unauthorized people from utilizing devices of authorized users to intrude other devices for lateral movement. Organizations need to evaluate trustworthiness of access requests based on user behaviours and threat intelligence and adapt associated access control policies. To date, the research community has stressed the importance of innovative technologies and integrated solutions for zero-trust.

This Research Topic solicits original and high-quality works on recent advances on the innovative technologies, challenges, and solutions for zero-trust. We aim to enhance the current state of development of zero-trust technologies including algorithms, methodologies, frameworks to evaluate risk of access requests for achieving zero trust and accordingly reduce potential cybersecurity risks.

Topics of interest include, but are not limited to:
• Trust evaluation algorithm for zero-trust
• Cyber threat intelligence for zero-trust
• Edge device risk evaluation for zero-trust
• Emerging innovative access control for zero-trust
• Access policies and selective restrictions for zero-trust
• Novel theories, architectures, applications and paradigms with zero-trust
• Practices and experiences for zero-trust architecture
• Security modelling for zero-trust architecture
• Privacy enhanced technologies for zero-trust
• Effectiveness evaluation and benchmark of zero-trust technologies
• Advances in the use of zero-trust underlying technologies (e.g., AI, blockchain, deterministic networks, cloud/edge computing, etc.)
• Miscellaneous issues for zero-trust

Keywords: Zero Trust, Trustworthiness, Access Control, Risk Management, Security, Privacy

Research Areas Cyber-security

Research Themes AI and Technologies

Research Centres/Groups Centre for Cybersecurity, IoT and Cyberphysical Systems

Org Units University
School of Computing Engineering and the Built Environment

URL https://www.frontiersin.org/research-topics/60754/emerging-technologies-challenges-and-solutions-for-zero-trust

Recognition Type	Editorial Activity
Description	Recently, more and more organizations have embraced the zero-trust technologies due to minimizing risk in enforcing accurate, least privilege per-request access decisions in service applications under the circumstance of a compromised network. In a zero-trust architecture, each access request should be authenticated and evaluated whether the request is permitted no matter it originated from external or internal network. In addition, unauthorized people from utilizing devices of authorized users to intrude other devices for lateral movement. Organizations need to evaluate trustworthiness of access requests based on user behaviours and threat intelligence and adapt associated access control policies. To date, the research community has stressed the importance of innovative technologies and integrated solutions for zero-trust. This Research Topic solicits original and high-quality works on recent advances on the innovative technologies, challenges, and solutions for zero-trust. We aim to enhance the current state of development of zero-trust technologies including algorithms, methodologies, frameworks to evaluate risk of access requests for achieving zero trust and accordingly reduce potential cybersecurity risks. Topics of interest include, but are not limited to: • Trust evaluation algorithm for zero-trust • Cyber threat intelligence for zero-trust • Edge device risk evaluation for zero-trust • Emerging innovative access control for zero-trust • Access policies and selective restrictions for zero-trust • Novel theories, architectures, applications and paradigms with zero-trust • Practices and experiences for zero-trust architecture • Security modelling for zero-trust architecture • Privacy enhanced technologies for zero-trust • Effectiveness evaluation and benchmark of zero-trust technologies • Advances in the use of zero-trust underlying technologies (e.g., AI, blockchain, deterministic networks, cloud/edge computing, etc.) • Miscellaneous issues for zero-trust Keywords: Zero Trust, Trustworthiness, Access Control, Risk Management, Security, Privacy
Research Areas	Cyber-security
Research Themes	AI and Technologies
Research Centres/Groups	Centre for Cybersecurity, IoT and Cyberphysical Systems
Org Units	University School of Computing Engineering and the Built Environment
URL	https://www.frontiersin.org/research-topics/60754/emerging-technologies-challenges-and-solutions-for-zero-trust

Guest Editor, Special Issue on Exploring the Frontier of Zero-Trust Technologies: Overcoming Challenges and Innovating Solutions for Computers, Materials & Continua (Print: ISSN:1546-2218, Electronic ISSN:1546-2226)
2023 - 2024

Recognition Type Editorial Activity

Description In recent times, a growing number of organizations are turning to zero-trust technologies. Their aim is to mitigate risks by strictly enforcing least-privilege access decisions, particularly when their networks face threats. Within this zero-trust framework, every access request, whether from within the organization or outside, must undergo authentication and be scrutinized for proper permissions. This not only ensures access legitimacy but also deters unauthorized individuals from leveraging devices of legitimate users for lateral movements within the network. Hence, it's crucial for organizations to gauge the trustworthiness of each access request, drawing insights from user behavior and threat intelligence. They must then refine their access control policies based on these assessments. The research community has persistently highlighted the vital role of pioneering technologies and comprehensive solutions in advancing the zero-trust paradigm.

This special issue invites submissions of original, high-quality research on the latest developments, challenges, and solutions in the realm of zero-trust. Our aim is to push the boundaries of current zero-trust technology, embracing innovations in algorithms, methodologies, and frameworks. Through these advancements, we hope to evaluate the risk of access requests with greater precision, truly embodying the zero-trust ethos and, in turn, diminishing potential cybersecurity threats. We welcome topics of interest that encompass, but are not limited to:

Trust Evaluation Algorithms for Zero-Trust Frameworks

Cyber Threat Intelligence within Zero-Trust Contexts

Risk Assessment of Edge Devices in Zero-Trust Scenarios

Innovative Access Control Mechanisms in Zero-Trust Systems

Designing Access Policies and Enforcing Selective Restrictions in Zero-Trust Models

Emerging Theories, Architectures, Applications, and Paradigms in the Zero-Trust Domain

Best Practices and Insights from Zero-Trust Architecture Deployments

Security Modeling Techniques for Zero-Trust Architectures

Employing Privacy-Enhancing Technologies in Zero-Trust Settings

Measuring and Benchmarking the Efficacy of Zero-Trust Technologies

Cutting-Edge Technologies Shaping Zero-Trust (e.g., AI, Blockchain, Deterministic Networks, Cloud/Edge Computing)

Diverse Challenges and Aspects of Zero-Trust Implementation

Keywords
Zero Trust, Trustworthiness, Access Control, Risk Management, Security, Privacy

Research Areas Cyber-security

Research Themes AI and Technologies

Research Centres/Groups Centre for Cybersecurity, IoT and Cyberphysical Systems

Org Units School of Computing Engineering and the Built Environment
University

URL https://www.techscience.com/cmc/special_detail/zero-trust

Recognition Type	Editorial Activity
Description	In recent times, a growing number of organizations are turning to zero-trust technologies. Their aim is to mitigate risks by strictly enforcing least-privilege access decisions, particularly when their networks face threats. Within this zero-trust framework, every access request, whether from within the organization or outside, must undergo authentication and be scrutinized for proper permissions. This not only ensures access legitimacy but also deters unauthorized individuals from leveraging devices of legitimate users for lateral movements within the network. Hence, it's crucial for organizations to gauge the trustworthiness of each access request, drawing insights from user behavior and threat intelligence. They must then refine their access control policies based on these assessments. The research community has persistently highlighted the vital role of pioneering technologies and comprehensive solutions in advancing the zero-trust paradigm. This special issue invites submissions of original, high-quality research on the latest developments, challenges, and solutions in the realm of zero-trust. Our aim is to push the boundaries of current zero-trust technology, embracing innovations in algorithms, methodologies, and frameworks. Through these advancements, we hope to evaluate the risk of access requests with greater precision, truly embodying the zero-trust ethos and, in turn, diminishing potential cybersecurity threats. We welcome topics of interest that encompass, but are not limited to: Trust Evaluation Algorithms for Zero-Trust Frameworks Cyber Threat Intelligence within Zero-Trust Contexts Risk Assessment of Edge Devices in Zero-Trust Scenarios Innovative Access Control Mechanisms in Zero-Trust Systems Designing Access Policies and Enforcing Selective Restrictions in Zero-Trust Models Emerging Theories, Architectures, Applications, and Paradigms in the Zero-Trust Domain Best Practices and Insights from Zero-Trust Architecture Deployments Security Modeling Techniques for Zero-Trust Architectures Employing Privacy-Enhancing Technologies in Zero-Trust Settings Measuring and Benchmarking the Efficacy of Zero-Trust Technologies Cutting-Edge Technologies Shaping Zero-Trust (e.g., AI, Blockchain, Deterministic Networks, Cloud/Edge Computing) Diverse Challenges and Aspects of Zero-Trust Implementation Keywords Zero Trust, Trustworthiness, Access Control, Risk Management, Security, Privacy
Research Areas	Cyber-security
Research Themes	AI and Technologies
Research Centres/Groups	Centre for Cybersecurity, IoT and Cyberphysical Systems
Org Units	School of Computing Engineering and the Built Environment University
URL	https://www.techscience.com/cmc/special_detail/zero-trust

Guest Editor, Special Section on Large Language Models for Consumer Health for IEEE Transactions on Consumer Electronics. (ISSN: 00983063)
2024 - 2024

Recognition Type Editorial Activity

Description Consumer Health allows individuals to oversee their health and well-being consistently, empowering through self-care practices, preventive measures, informed decision-making, and personalized solutions. This paradigm stems from a traditional reactive approach to a personalized-proactive model, upholding the principles of a patient-centric system. Large Language Models (LLMs), harnessing the benefits of Natural Language Processing and Deep Learning, have a pivotal role in the transformative landscape of consumer health. These models act as stimulators by ensuring the deployment of personalized health assistants and emerging health information retrieval systems and have the potential to navigate the complexities of
healthcare. This integrated approach allows consumers to harness the manifold facets of healthcare, encompassing medication management, symptom checking, and health education, thereby safeguarding individual well-being. The transformative integration of LLMs into consumer healthcare management stands poised to revolutionize health literacy, nurture proactive health behaviors, and elevate the overall user experience within the healthcare realm.
However, LLMs in consumer healthcare management encounter manifold challenges. The first and foremost challenge is the accurate interpretation of healthcare information and its contextual nuances, given the field's complicated terminology, diverse patient experiences, and the ever-evolving landscape of medical research, all of which carry implications for individual well-being. Privacy concerns related to patient data denote an essential concern, necessitating strict adherence to data security regulations, given the substantial volume of health data processed by these models. Equally influential is the imperative to cultivate trust between consumers and the LLM model, entailing transparent communication about the model's limitations and strengths and providing reliable sources of knowledge to consumers.
Overcoming these challenges is mandatory for the successful deployment of LLMs in Consumer Healthcare Management, wherein a meticulous investigation of trustworthy, personalized, and ethical considerations is critical to transforming the healthcare technology landscape. Scholars, academicians, and researchers are encouraged to contribute manuscripts that evaluate the harnessing of LLMs in consumer healthcare. Such contributions pledge to revolutionize the consumer health landscape and lead the trajectory of future healthcare paradigms.

Topics of interest in this Special Section include (but are not limited to):
• Enhancing Consumer Health Literacy through LLMs
• Delving individual Acceptance and Trust for LLMs Model for Consumer Health
• Customizing personalized features in LLMs for enhancing consumer health
• Security and Privacy of Consumer Health Data for LLMs
• Synergy of LLMs with Wearable Consumer Health devices for Real-Time Insights
• Advancing Semantic Interportblity for diverse consumer Health data set for LLMs
• Evaluating long-term impacts of LLMs on Consumer Health
• Integrating feedback from consumers into LLMs for better insights into Consumer
health
• Converging the LLMs with Electronic Consumer Health Records
• Collaborative learning to elevate the performance of LLMs in Consumer Health
• More Accesicissble LLMs for making inclusive consumer health system
• Computing Risk Management of Consumers through LLMs
• Empowering and Engaging Consumers for self-care using LLMs
• Enhancing Linguistic sensitivity for diverse consumers
• Dietary and herbal supplements planning through LLMs

Research Areas Health and wellbeing
Internet of Things
Healthcare Services
Optimisation and learning

Research Themes AI and Technologies

Research Centres/Groups Centre for Cybersecurity, IoT and Cyberphysical Systems

Org Units School of Computing Engineering and the Built Environment

URL https://ctsoc.ieee.org/images/TCE_FILES/Approved_CFP/May_2024/TCE_SS_CFP_Large_Language_Models_for_Consumer_Health.pdf

Recognition Type	Editorial Activity
Description	Consumer Health allows individuals to oversee their health and well-being consistently, empowering through self-care practices, preventive measures, informed decision-making, and personalized solutions. This paradigm stems from a traditional reactive approach to a personalized-proactive model, upholding the principles of a patient-centric system. Large Language Models (LLMs), harnessing the benefits of Natural Language Processing and Deep Learning, have a pivotal role in the transformative landscape of consumer health. These models act as stimulators by ensuring the deployment of personalized health assistants and emerging health information retrieval systems and have the potential to navigate the complexities of healthcare. This integrated approach allows consumers to harness the manifold facets of healthcare, encompassing medication management, symptom checking, and health education, thereby safeguarding individual well-being. The transformative integration of LLMs into consumer healthcare management stands poised to revolutionize health literacy, nurture proactive health behaviors, and elevate the overall user experience within the healthcare realm. However, LLMs in consumer healthcare management encounter manifold challenges. The first and foremost challenge is the accurate interpretation of healthcare information and its contextual nuances, given the field's complicated terminology, diverse patient experiences, and the ever-evolving landscape of medical research, all of which carry implications for individual well-being. Privacy concerns related to patient data denote an essential concern, necessitating strict adherence to data security regulations, given the substantial volume of health data processed by these models. Equally influential is the imperative to cultivate trust between consumers and the LLM model, entailing transparent communication about the model's limitations and strengths and providing reliable sources of knowledge to consumers. Overcoming these challenges is mandatory for the successful deployment of LLMs in Consumer Healthcare Management, wherein a meticulous investigation of trustworthy, personalized, and ethical considerations is critical to transforming the healthcare technology landscape. Scholars, academicians, and researchers are encouraged to contribute manuscripts that evaluate the harnessing of LLMs in consumer healthcare. Such contributions pledge to revolutionize the consumer health landscape and lead the trajectory of future healthcare paradigms. Topics of interest in this Special Section include (but are not limited to): • Enhancing Consumer Health Literacy through LLMs • Delving individual Acceptance and Trust for LLMs Model for Consumer Health • Customizing personalized features in LLMs for enhancing consumer health • Security and Privacy of Consumer Health Data for LLMs • Synergy of LLMs with Wearable Consumer Health devices for Real-Time Insights • Advancing Semantic Interportblity for diverse consumer Health data set for LLMs • Evaluating long-term impacts of LLMs on Consumer Health • Integrating feedback from consumers into LLMs for better insights into Consumer health • Converging the LLMs with Electronic Consumer Health Records • Collaborative learning to elevate the performance of LLMs in Consumer Health • More Accesicissble LLMs for making inclusive consumer health system • Computing Risk Management of Consumers through LLMs • Empowering and Engaging Consumers for self-care using LLMs • Enhancing Linguistic sensitivity for diverse consumers • Dietary and herbal supplements planning through LLMs
Research Areas	Health and wellbeing Internet of Things Healthcare Services Optimisation and learning
Research Themes	AI and Technologies
Research Centres/Groups	Centre for Cybersecurity, IoT and Cyberphysical Systems
Org Units	School of Computing Engineering and the Built Environment
URL	https://ctsoc.ieee.org/images/TCE_FILES/Approved_CFP/May_2024/TCE_SS_CFP_Large_Language_Models_for_Consumer_Health.pdf

Guest Editor, Special Section on Exploring Emerging Technologies in the Zero Trust Landscape: Challenges and Solutions for IEEE Open Journal of the Computer Society Print ISSN: 0740-7459; Electronic ISSN: 1937-4194
2024 - 2024

Recognition Type Editorial Activity

Description Recently, an increasing number of organizations have adopted zero-trust technologies to minimize risks by enforcing precise, least-privilege access decisions for service applications, especially when networks are compromised. Within a zero-trust architecture, every access request, whether originating from an external or internal network, must be authenticated and evaluated for permission. This approach also prevents unauthorized individuals from using the devices of authorized users to access other devices for lateral movements. Organizations must assess the trustworthiness of access requests based on user behaviors and threat intelligence, adapting their access control policies accordingly. The research community has consistently emphasized the significance of innovative technologies and integrated solutions in the realm of zero-trust.

This special issue calls for original and high-quality works on the latest advancements, challenges, and solutions related to zero-trust. Our goal is to enhance the present state of zero-trust technology development, encompassing algorithms, methodologies, and frameworks. These advancements will assess the risk of access requests more effectively, achieving true zero trust, and consequently reducing potential cybersecurity risks. Topics of interest include, but are not limited to:

Trust Evaluation Algorithms in Zero-Trust Frameworks
Cyber Threat Intelligence in the Context of Zero-Trust
Risk Evaluation of Edge Devices for Zero-Trust
Innovations in Access Control for Zero-Trust Systems
Access Policies and Selective Restrictions within Zero-Trust Models
Novel Theories, Architectures, Applications, and Paradigms in Zero-Trust
Best Practices and Experiences in Zero-Trust Architecture Implementation
Security Modeling within Zero-Trust Architectures
Privacy-Enhancing Technologies in Zero-Trust Environments
Evaluating the Effectiveness and Benchmarking of Zero-Trust
Technologies
Advances in Technologies Underpinning Zero-Trust (e.g., AI, Blockchain, Deterministic Networks, Cloud/Edge Computing, etc.)
Miscellaneous Challenges and Considerations in Zero-Trust
Submission Guidelines
For author information and guidelines on submission criteria, please visit the OJ-CS Author Information page. Please submit papers through the ScholarOne Manuscripts system, and be sure to select the special-section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal.

Questions?
Contact the guest editors at khyeh@nycu.edu.tw.

Prof. Kuo-Hui Yeh (Lead Guest Editor), National Yang Ming Chiao Tung University, Taiwan
Prof. Yingjiu Li, the University of Oregon, US
Prof. Weizhi Meng, Technical University of Denmark, Denmark
Prof. Zhiyuan Tan, Edinburgh Napier University, United Kingdom
Prof. Shi-Cho Cha, National Taiwan University of Science and Technology, Taiwan
Prof. Yang Xiang (IEEE fellow), Swinburne University of Technology, Australia

Research Areas Cyber-security

Research Themes AI and Technologies

Research Centres/Groups Centre for Cybersecurity, IoT and Cyberphysical Systems

Org Units School of Computing Engineering and the Built Environment
University

URL https://www.computer.org/digital-library/journals/oj/cfp-emerging-technologies-in-the-zero-trust-landscape-challenges-and-solutions

Recognition Type	Editorial Activity
Description	Recently, an increasing number of organizations have adopted zero-trust technologies to minimize risks by enforcing precise, least-privilege access decisions for service applications, especially when networks are compromised. Within a zero-trust architecture, every access request, whether originating from an external or internal network, must be authenticated and evaluated for permission. This approach also prevents unauthorized individuals from using the devices of authorized users to access other devices for lateral movements. Organizations must assess the trustworthiness of access requests based on user behaviors and threat intelligence, adapting their access control policies accordingly. The research community has consistently emphasized the significance of innovative technologies and integrated solutions in the realm of zero-trust. This special issue calls for original and high-quality works on the latest advancements, challenges, and solutions related to zero-trust. Our goal is to enhance the present state of zero-trust technology development, encompassing algorithms, methodologies, and frameworks. These advancements will assess the risk of access requests more effectively, achieving true zero trust, and consequently reducing potential cybersecurity risks. Topics of interest include, but are not limited to: Trust Evaluation Algorithms in Zero-Trust Frameworks Cyber Threat Intelligence in the Context of Zero-Trust Risk Evaluation of Edge Devices for Zero-Trust Innovations in Access Control for Zero-Trust Systems Access Policies and Selective Restrictions within Zero-Trust Models Novel Theories, Architectures, Applications, and Paradigms in Zero-Trust Best Practices and Experiences in Zero-Trust Architecture Implementation Security Modeling within Zero-Trust Architectures Privacy-Enhancing Technologies in Zero-Trust Environments Evaluating the Effectiveness and Benchmarking of Zero-Trust Technologies Advances in Technologies Underpinning Zero-Trust (e.g., AI, Blockchain, Deterministic Networks, Cloud/Edge Computing, etc.) Miscellaneous Challenges and Considerations in Zero-Trust Submission Guidelines For author information and guidelines on submission criteria, please visit the OJ-CS Author Information page. Please submit papers through the ScholarOne Manuscripts system, and be sure to select the special-section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal. Questions? Contact the guest editors at khyeh@nycu.edu.tw. Prof. Kuo-Hui Yeh (Lead Guest Editor), National Yang Ming Chiao Tung University, Taiwan Prof. Yingjiu Li, the University of Oregon, US Prof. Weizhi Meng, Technical University of Denmark, Denmark Prof. Zhiyuan Tan, Edinburgh Napier University, United Kingdom Prof. Shi-Cho Cha, National Taiwan University of Science and Technology, Taiwan Prof. Yang Xiang (IEEE fellow), Swinburne University of Technology, Australia
Research Areas	Cyber-security
Research Themes	AI and Technologies
Research Centres/Groups	Centre for Cybersecurity, IoT and Cyberphysical Systems
Org Units	School of Computing Engineering and the Built Environment University
URL	https://www.computer.org/digital-library/journals/oj/cfp-emerging-technologies-in-the-zero-trust-landscape-challenges-and-solutions

Associate Editor, IEEE Open Journal of the Computer Society (Print ISSN: 0740-7459; Electronic ISSN: 1937-4194)

Guest Editor, Special Issue on AI-ZTIoT: AI-enabled Zero Trust for Security of IoT Networks for Ad Hoc Networks, Print ISSN: 1570-8705; Online ISSN: 1570-8713

Lead Guest Editor, Special Issue on Big Data Technologies and Applications in Web 3.0: Trends and Challenges for Smart Society for International Journal of Web Information Systems, ISSN:1744-0084

Associate Editor, Journal of Ambient Intelligence and Humanized Computing (ISSN: 1868-5137, Electronic ISSN: 1868-5145)

Ph.D. degree external examiner for University of the West of England, UK

Publicity Co-chair, IEEE 2023 Conference on Dependable and Secure Computing (IEEE DSC 2023)

The First Prize of the Outstanding Paper Awards - The 2022 Annual Academic Conference of Liaoning Computer Society (China)

Ph.D. degree external examiner for Macquarie University, Australia

Guest Editor, special issue on 'Advance for reliable cloud-edge based AIoT', IET Communications , Online ISSN:1751-8636

Guest Editor, special issue on 'Evolutionary Computation-Based Machine Learning and Its Applications in Complex Control Systems', IET Control Theory & Applications, Online ISSN:1751-8652

Ph.D. degree external examiner for University of Exeter, UK

Ph.D. degree external examiner for University of New South Wales, Australia

External Supervisor for Postgraduate Research Students at Shenyang Aerospace University, China

Dr Thomas Tan's Recognition (210)