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Syed Attique Shah

Software-Defined Networking (SDN) AI-Enabled Digital Twin Frameworks Multi-Agent Systems Federated Learning Positive Energy Districts Optimization
Birmingham City University School of Computing and Digital Technology

About

Dr. Syed Attique Shah is a Senior Lecturer in Smart Computer Systems at the Department of Computer Science, Birmingham City University (BCU), UK. He also serves as the Course Lead/Director for the MRes in Computing and MSc Advanced Computer Networks at BCU. With over 12 years of experience in teaching and research, he has established a distinguished academic career with expertise in computer science. Prior to joining BCU, he held positions as a Lecturer/Assistant Professor at the Data Systems Group, Institute of Computer Science, University of Tartu, Estonia, and as an Associate Professor and Chairperson of the Department of Computer Science at BUITEMS, Quetta, Pakistan. Dr. Shah completed his Ph.D. at Istanbul Technical University, Turkey, in 2019. During his doctoral studies, he was a Visiting Scholar at several prestigious institutions, including the University of Tokyo, Japan; National Chiao Tung University, Taiwan; and Tallinn University of Technology, Estonia. His international experience spans institutions across Estonia, Turkey, Pakistan, Taiwan, China, and Japan, providing him with valuable insights into diverse academic and professional standards. Recognised globally for his academic contributions, Dr. Shah was listed among the top 2% of scientists worldwide in 2024 by Stanford University and Elsevier. He holds the status of Chartered IT Professional (CITP) and is a Fellow of the Higher Education Academy (FHEA). Additionally, he is endorsed by the Royal Society UK as a Global Talent and is an approved Ph.D. supervisor by the Higher Education Commission (HEC) of Pakistan. He is also recognised by the Staff and Educational Development Association (SEDA), UK, for his contributions to supporting learning. His professional affiliations include IEEE Senior Member and Professional Member of the British Computer Society. With extensive teaching experience, Dr. Shah has designed and delivered courses on Machine Learning, the Internet of Things, Artificial Intelligence, Programming Languages, Computer Networks, Data Science, and Software Engineering at both undergraduate and postgraduate levels. He has supervised over 30 postgraduate students and co-supervised 3 Ph.D. candidates to successful completion. He is currently supervising a PhD student researching the use of AI and digital twinning for energy efficiency. Dr. Shah has served as a reviewer for funding bodies such as the British Council and Chevening Scholarships and has actively participated in academic panels and conference leadership roles. Currently, he is an External Examiner (2025–2029) for the BSc Artificial Intelligence program at De Montfort University, UK, and for the PGCE Information Communication Technology and Computing Course at Cardiff Metropolitan University, UK. His research focuses on cutting-edge areas such as Machine Learning, Data Science, Image Processing, Software-Defined Networking (SDN), and the Internet of Things (IoT). He has published over 30 Q1 journal papers with a cumulative impact factor exceeding 100, accumulating more than 2,800 citations and an h-index of over 24. He has served as an editor on special issues for journals such as Big Data and Cognitive Computing and IET Smart Cities, and has chaired sessions at top conferences (e.g., IEEE BigData 2023). His work has been presented at leading international conferences, further demonstrating his research impact. Dr. Shah's leadership as Principal Investigator (PI) on two major UK-funded projects highlights his success in securing funding (£100k total) and driving innovation. He is spearheading the Alan Turing Institute/UKRI DTNet+ project (£50,000), establishing AI-enabled digital twin frameworks to model and optimise Positive Energy Districts using real-time data and intelligent decision support. As PI on another EPSRC/UKRI/DfT project (£50,000) under the National Hub for Decarbonised, Adaptable, and Resilient Transport Infrastructures (DARe) Transport Hub, he applied multi-agent systems and federated learning to develop AI strategies enhancing climate resilience in UK transport infrastructure. He has also contributed to multiple funded research projects as Co-Principal Investigator and Project Lead. His research integrates interdisciplinary approaches to drive technological advancements, with a focus on shaping the digital future and adapting to emerging technological trends. Committed to excellence in teaching, research, and professional development, Dr. Shah continues to inspire students and colleagues alike while advancing the field of computer science through his scholarly contributions.

Research Performance Summary

63
Total Papers
3666
Total Citations
26
H-Index
2012-2026
Active Research Span

First Recorded Paper

Particle swarm optimization for N-queens problem

Year: 2012

Citations: 10

Venue: Journal of Advanced Computer Science and Technology 1 (2)

Latest Recorded Paper

SORA-ATMAS: Adaptive Trust Management and Multi-LLM Aligned Governance for Future Smart Cities

Year: 2026

Citations: 0

Venue: Knowledge-Based Systems

Last 10 Years Publication Activity

This timeline shows the professor's yearly publication activity.

2026
2
2025
6
2024
12
2023
9
2022
6
2021
16
2020
5
2019
2
2018
1
2017
1
2016
1

Publication Venues and Collaboration

Journal, Conference, and Book Publication Breakdown

Conference 20
Journal 8
Book 0

Top Coauthors

Shah Hameed Ahmed

Research Impact by Period

2025-2026

Period Stats
Papers 8
Citations 12
Avg. Citations / Paper 1.5
H-Index 2

2020-2024

Period Stats
Papers 48
Citations 3151
Avg. Citations / Paper 65.6
H-Index 25

2015-2019

Period Stats
Papers 5
Citations 482
Avg. Citations / Paper 96.4
H-Index 3

2010-2014

Period Stats
Papers 2
Citations 21
Avg. Citations / Paper 10.5
H-Index 2

Contact and Professional Links

Contact Information

syedattique.shah@bcu.ac.uk

Detected Research Keywords

Association Rule Mining Systematic Literature Review Big Data Analytics Ddos Attack Detection Software Defined Iot Defined Iot Sd Iot Sd Iot Adaptive Security Governance Security Governance Architecture Governance Architecture Smart