Dr. Zia Ush Shamszaman is a Senior Lecturer in the Department of Computing & Games at  the School of Computing, Engineering & Digital Technologies (SCEDT). Prior to starting as an academic, he worked as a postdoctoral researcher at Dublin City University, Ireland and University College Cork, Ireland. Dr. Shamszaman also worked as a Part-time teacher at National University of Ireland Galway.

Dr. Shamszaman's research interests lie in the areas of: 

• Cybersecurity
• Industry 4.0
• Internet of Things (IoT) Social Internet of Things (SIoT)
• Cyber Physical Systems (CPS)
• AI, Explainable AI and Deep Learning
• Semantic Web
• Probabilistic Ontology
• Stream processing
• Big data
• Linked data

KEYNOTE SPEAKER

Seminar on Recent Research Trends and Opportunities in IoT and Cybersecurity at Grreen University of Bangladesh. June, 2022

MEMBERSHIPS

• Senior Member, IEEE; 
• Member, Elsevier Advisory Panel; 
• Member, World Wide Web Consortium (W3C) ;
• Member, Europe Technology Network Community,
• IEEE; Member, brain Community,
• IEEE; Member, Digital Privacy and Trust Community,
• IEEE; Member, Future of Technology Community,
• IEEE; Member, Artificial Intelligence Community,
• IEEE; Member, Internet of Things Community,
• IEEE; Member, Cloud Computing Community,
• IEEE; Member, Big Data Community,
• IEEE; Web of Things Community,

PROGRAM COMMITTEES

• International Conference on Suitable Technologies 4.0, 2020- TPC Member.
• IEEE 5TH World Forum on IoT, 2019- TPC Member.
• International Conference on Suitable Technologies 4.0, 2019- TPC Member.
• Insight Student Conference 2015- organizing committee member.
• International conference on Speech & Language Technology for Low-resource Languages (SPELLL) 2022- Program Chair

REVIEWER

Information Fusion (IF 10.716); IEEE Communications Magazine (IF 10.356); IEEE Internet of Things Journal (IF 9.515); Network Magazine, IEEE (IF 7.503); IEEE Transactions on Industrial Informatics (IF 7.377); IEEE Transactions on Intelligent Transportation Systems (IF 5.744); Information Sciences (IF 5.524); Journal of Network and Computer Applications (IF 5.273); Applied Soft Computing (IF 4.873); Future Generation Computer Science (IF 4.639); IEEE Access Journal (IF 4.098).

ISSUE EDITING

Special Issue "Security and Privacy in Cloud Computing Environment" A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

AWARDS

• Outstanding contribution in reviewing, Journal of Network and Computer Application, Elsevier
• Outstanding contribution in reviewing, Future Generation Computer Systems, Elsevier
• Outstanding contribution in reviewing, Computer and Electrical Eng. Journal, Elsevier
• Second position in Spark Haus Hackathon, Cisco Ireland
• Ph.D. research grant, Science Foundation Ireland
• Foreign Student Scholarship (Master) by Hankuk University of Foreign Studies

Teaching (Post graduate)

• Computing Masters Project Module @ Teesside University
• Research Methods Module @ Teesside University
• Artificial Intelligence Ethics and Applications Module @ Teesside University
• Linked Data @ University of Galway, Ireland

Teaching (Bachelor) 

• Ethical Hacking Module @ Teesside University
• Security Analyst Module @ Teesside University
• Secure Data Acquisition Module @ Teesside University
• Computing Project Module @ Teesside University
• Data Structure @ University of Galway, Ireland

Others

• Research Ethics Committee Member at School of Computing, Engineering and Technologies at Teesside University
• Course Review Committee member at Teesside University

• iShield: An AI-enabled application to secure Healthcare IoT. Funded by KTP-CyberASAP
• AutoTaxi: Probabilistic ontology based accident prediction model for airport ground operations, funded by Science Foundation Ireland
• Enabling the Internet of Everything (IoE), Funded by Cisco, Ireland
• Web of Objects: ITEA2 project.
• Building Energy Management System, funded by ETRI, Korea

I worked in the industry over 7 years till 2011 in the following roles,

• Technical Consultant and Technical Project Manager @ data edge limited, Dhaka, Bangladesh
• Sr. Network and Security engineer @ CSB News Limited, Dhaka Bangladesh
• Network and Security Engineer @ Onenet Communications Ltd., Dhaka Bangladesh

Completed Benchmark Projects for the government of the people's republic of Bangladesh and Bangladesh Central Bank

• Technical Project Manager @ Machine Readable Passport and Machine Readable VIsa project, funded by the government of the People's Republic of Bangladesh.
• Technical Consultant @ Bangladesh Automated Clearing House project funded by World Bank
• Technical Consultant @ Strengthening ICT project for Planning Commission, Ministry of Planning, People's Republic of Bangladesh

Open to supervise if you intend to apply for a funding/scholarship.

Funded PhD Opportunity at Teesside University-Apply here

• Deadline: 01/02/2023 5:00PM
• Studentship code: RDS
• Staff name: Dr Zia Ush Shamszaman
• Research centre: Centre for Digital Innovation
• Start date: Successful applicants will be expected to start May or October 2023.

We are experiencing a cabalistic transformation in manufacturing products because of the digitisation of the process of manufacturing products in the industries and factories [1]. The key technologies in this transformation are, Cyber Physical Systems, Internet of Things (IoT) and Information Systems [1,2,4]. The transformation is so significant and inevitable that it is being considered as the 4th industrial revolution called Industry 4.0 [1, 3, 9].

Social IoT (SIoT) is a recent amendment in the IoT paradigm where human-centric online social network principles are implied into IoT to enable IoT object as a new social element. SIoT work as a common platform for the data coming from IoT devices and social network services to facilitate omnidirectional interactions (human to human, human to object and object to object) among human and objects for creating new services in the future intelligent smart spaces. Industrial IoT (IIoT) has been noticed seriously and largely by the scientific community as well as by the industry because of its tremendous possibilities to leverage automaticity and intelligence mainly in the production, supply chain and manufacturing industries, ie leveraging the 4th industry revolution. The progressing trends towards IIoT from the predominant IoT, necessity of CPS, the vision of utilising SIoT in the smart industries and factories, the immense possibility of AI to incorporate intelligence in the physical objects; and the scalability issues of existing security mechanisms on huge IIoT resources demand an approach that addresses the above mentioned issues and move forward with the vision and possibilities towards the Industry 4.0. Hence, this research proposes an AI-enabled Secure Social Industrial Internet of Things (ASIIoT) that includes the utilisation of resources ie machines, parts, devices, processes, human and physical objects intelligently.

However, the process of this transformation is not trivial and requires significant effort from the research community to overcome the existing challenges mainly because of the complexity, heterogeneity, time-sensitivity and interoperability issues of resource constrained connected objects.

Aim and objectives

The aim of this research is to overcome several existing challenges to leverage Industry 4.0 through exploring the social relation of connected physical objects of IIoT and CPS, ensuring security by developing novel intrusion prevention system for resource constrained connected objects and incorporating intelligence into the physical objects and processes through creating the virtual counterpart of the relevant physical objects including human on the cyberspace.

The primary objective of this research is to develop ASIIoT platforms. The idea of social relationship among resources will ensure the collective participation of resources to accomplish a task together to enhance the performance of the factories and industries. The proposed platform shall include intelligence, real-time monitoring, real-time and historical analysis, control of machines, and control of manufacturing systems and virtualising physical objects to the cyberspace. All the assets will be associated with socially connected actuators and sensors. An architecture will be designed from the semantic ontological perspective and ontology model will be provided to make the relationship meaningful and reusable to the digital world. A novel intrusion prevention system will be developed for resource constrained objects, lightweight cryptography will be used to ensure confidentiality, integrity, non-repudiation and authenticity of data as well as of communication.

A simple scenario would be common machinery elements in the factories eg motor, bearing, axel, bracket, hanger etc. perform various tasks. Regardless of their size and price they are so important for the production systems that even a faulty tiny bearing may cause an entire system to halt which is unacceptable and sometimes unaffordable in terms of money and time. This proposed platform will enable prediction mechanisms that predict the upcoming failure and triggers sourcing process beforehand for a replacement and/or generates notification to take preventive initiatives.

Funding eligibility

The Fully Funded PhD Studentship covers tuition fees for the period of a full-time PhD Registration of up to four years and provide an annual tax-free stipend of £17,668 for three years, subject to satisfactory progress.

The Part-Funded PhD Studentship covers tuition fees for the period of a full-time PhD Registration of up to four years.

Applicants who are employed and if their employer is interested in funding a PhD, can apply for a Collaborative Studentship.

Applications are welcome from UK, EU and International students.

Entry requirements

Applicants should hold or expect to obtain a good honours degree (2:1 or above) in a relevant discipline. A masters level qualification in a relevant discipline is desirable, but not essential, as well as a demonstrable understanding of the research area. Further details of the expected background may appear in the specific project details. International students will be subject to the standard entry criteria relating to English language ability, ATAS clearance and, when relevant, UK visa requirements and procedures.

How to apply

Applicants should apply online for this opportunity using the Online Application (Funded PHD) application form. When asked to specify funding select “other” and enter ‘RDS’ and the title of the PhD project that you are applying for. You should ensure that you clearly indicate that you are applying for a Funded Studentship and the title of the topic or project on the proposal that you will need to upload when applying. To apply for more than one project, you need to complete a further application form and specify the relevant title for each application to a topic or project.

Applications for studentships that do not clearly indicate that the application is for a Funded Studentship and state the title of the project applied for on the proposal may mean that your application may not be considered for the appropriate funding.

Apply now

View our frequently asked questions

Academic enquiries

For academic enquiries, please contact z.shamszaman@tees.ac.uk.

For administrative enquiries before or when making your application, contact research.enquiries@tees.ac.uk.

After an application has been made, please contact research.admissions@tees.ac.uk.

Key dates

• Deadline: 01/02/2023 5:00PM
• Interview date: We envisage that interviews will take place in Mid-March 2023.
• Start date: Successful applicants will be expected to start May or October 2023.