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Dr Saeid Pourroostaei Ardakani

Saeid

Senior Lecturer in Computer Science

Email: s.pourroostaeiardakani@qmul.ac.uk

Profile

Saeid is a Senior Lecturer (Associate Professor) in Computer Science in the School of Electronic Engineering and Computer Science. He obtained his PhD from the University of Bath in 2015 and has since held academic appointments at the University of Lincoln, the University of Nottingham (Ningbo Campus), and ATU. With nearly a decade of academic experience, he has collaborated extensively with academic and industrial partners, contributing significantly to high-quality teaching, interdisciplinary research, and academic leadership. Saeid expertise is positioned at the forefront of Applied AI, with a strategic emphasis on the design and engineering of smart, adaptive, and secure computing and communication solutions within IoT and cloud ecosystems. His research integrates theoretical innovation with practical implementation, advancing next-generation and high-impact smart systems that underpin connected and data-driven societies/cities. Saeid is keen to address key challenges in real-time learning and optimisation, complex data processing, and autonomous orchestration across large-scale distributed systems and networks.

Teaching

Saeid’s teaching philosophy is grounded in cognitive-constructivism, with a strong emphasis on active and experiential learning. As an FHEA, he is committed to creating inclusive learning environments that foster deep understanding, critical thinking, and sustained academic development. Saeid strategically integrates educational technologies alongside interactive and student-centred lectures to enhance motivation, participation, and knowledge retention while stimulating intellectual curiosity and meaningful engagement.

Undergraduate Teaching

ECS655U - Security Engineering This module provides comprehensive coverage of fundamental concepts and principles in cybersecurity. It introduces the core elements of applied cryptography, including symmetric and public-key encryption, message integrity and authentication mechanisms, digital signatures, public key certificates, and cryptographic protocols. Beyond cryptographic foundations, the module also explores critical non-cryptographic dimensions of security, such as access control models, software security practices, network security and firewall technologies, web security mechanisms, and the human factors that influence system vulnerabilities and resilience. Together, these topics equip students with a holistic understanding of modern cybersecurity challenges and strategies.

Research

Research Interests:

Saeid's research interests span the following: 
-    Resilient Networks and Cyber-security
-    Ubiquitous Internet of Things and Crowdsensing
-    Digital twins 
-    Distributed and Federated Learning 
-    Applied AI and Big Data Analytics 
-    Learning Analytic

Publications

Books

  • S. P. Ardakani and A. Cheshmehzangi (Feb 2026). Crowdsensing and Data: Intelligence for City Pulse. Springer. ISBN: 978-981-95-6357-9.
  • S. P. Ardakani and A. Cheshmehzangi (Dec 2024). Digital Twin Computing for Urban Intelligence. Springer. ISBN: 978-981-97-8483-7. DOI 
  • S. P. Ardakani and A. Cheshmehzangi (Dec 2023). Big Data Analytics for Smart Transport and Healthcare Systems. Springer. ISBN: 978-981-9966-19-6. DOI 
  • S. P. Ardakani and A. Cheshmehzangi (Sep 2023). Big Data Analytics for Smart Urban Systems. Springer. ISBN: 978-981-99-5542-8. DOI

Journal Articles

  • L. Gong et al., S. P. Ardakani (Sep 2025). “Innovative Spatial-Temporal Attention Network (STAN) for Skeleton-Based Timed-Up-and-Go Analysis to Stratify Lower Back Pain Severity with Monocular RGB Camera.” IEEE Access. DOI
  • M. Wu and S. P. Ardakani (May 2025). “Towards Scientific Knowledge Graphs: Dependency Graph Analysis Using Graph Neural Networks for Extracting Scientific Relations.” Electronics. DOI
  • L. Gong, M. Yu and S. P. Ardakani (Apr 2025). “Privacy-Preserving Human Motion Analysis for Lower Back Pain Stratification through Federated Learning.” EAI Endorsed Transactions of Pervasive Health and Technology. DOI
  • M. Devine et al., S. P. Ardakani (Mar 2025). “Federated Machine Learning to Enable Intrusion Detection Systems in IoT Networks.” Electronics. DOI
  • S. P. Ardakani et al. (Jan 2025). “Identifying Crowdfunding Storytellers who Deliver Successful Projects: A Machine Learning Approach.” Supercomputing. DOI - A. Cheshmehzangi et al.,
  • S. P. Ardakani (Oct 2024). “Growing Digital Divide for Expatriates Population in China: A User Perspective Analysis During the COVID-19 Pandemic.” SAGE open. DOI - S. McCall et al.,
  • S. P. Ardakani (Feb 2024). “Computer Vision Based Transfer Learning-Aided Transformer Model for Fall Detection and Prediction.” IEEE Access. DOI - D. Kong et al.,
  • S. P. Ardakani (Aug 2023). “Urban Building Energy Modelling (UBEM): A Systematic Review of Challenges and Opportunities.” Energy Efficiency. DOI - S. P. Ardakani et al. (Mar 2023). “Road Car Accident Prediction Using a Machine-Learning-Enabled Data Analysis.” Sustainability. DOI - A. Cheshmehzangi et al.,
  • S. P. Ardakani (Feb 2023). “Space and Social Distancing in Managing and Preventing COVID-19 Community Spread: An Overview.” HELIYON. DOI
  • S. P. Ardakani et al. (Feb 2023). “A Federated Learning‐Enabled Predictive Analysis to Forecast Stock Market Trends.” Journal of Ambient Intelligence and Humanized Computing. DOI
  • S. P. Ardakani et al. (Aug 2022). “An Urban-Level Prediction of Lockdown Measures Impact on the Prevalence of the COVID-19 Pandemic.” Genus. DOI - H. Li et al.,
  • S. P. Ardakani (Jun 2022). “The Correlation Analysis Between Air Quality and Construction Sites During COVID-19.” Sustainability. DOI - X. Liu and S. P. Ardakani (Apr 2022). “Machine Learning Enabled Affective E-learning System Model.” Education and Information Technologies. DOI
  • P. Kar et al., S. P. Ardakani (Mar 2022). “Are Fake Images Bothering You on Social Network? Let’s Detect Them Using Recurrent Neural Network.” IEEE Transactions on Computational Social Systems. DOI
  • X. Xie and S. P. Ardakani (Jan 2022). “A Machine Learning Enabled Mobile Application to Analyse Ambient-Body Correlations.” SN Computer Science. DOI
  • Z. Zhang et al., S. P. Ardakani (Dec 2021). “A Data-Driven Clustering Analysis for the Impact of COVID-19 on Electricity Consumption in Zhejiang Province, China.” Energies. DOI

Peer-reviewed Conferences

  • S. Ghosh, M. Al-khafajiy, S. P. Ardakani, and T. Baker (Nov 2025). “Personalised Federated Learning at Scale: Hierarchical Boosting with Bayesian Fusion.” 18th International Conference on Development in eSystem Engineering (DeSE), Bucharest, Romania.
  • N. B. Masood, S. P. Ardakani, and M. Yu (Aug 2025). “A Transformer-based Deep Learning Model to Enhance Hope Speech Detection.” 9th International Conference on Deep Learning Technologies (ICDLT), Chengdu, China.
  • L. Gong, S. Mccall, M. Yu, M. Thota, G. S. Kashyap, and S. P. Ardakani (Aug 2024). “Innovate Spatial-Temporal Attention Network (STAN) for Accurate 3D Mice Pose Estimation with a Single Monocular RGB Camera.” 32nd European Signal Processing Conference (EUSIPCO), Lyon, France.
  • K. Nan, S. Hu, H. Luo, P. Wong, and S. P. Ardakani (Dec 2022). “A Semi-supervised Learning Application for Hand Posture Classification.” 12th EAI International Conference on Big Data Technologies and Applications (BDTA 2022), Cairo, Egypt. 
  • S. P. Ardakani, C. Zhou, X. Wu, Y. Ma, and J. Che (Dec 2021). “A Data-driven Affective Text Classification Analysis.” 20th IEEE International Conference on Machine Learning and Applications (ICMLA), Pasadena, USA.
  • S. P. Ardakani, X. Liu, and H. Xie (Apr 2021). “A Data-driven Study to Highlight the Correlations Between Ambient Factors and Emotion.” 5th EAI International Conference on Computer Science and Engineering in Health Services (COMPSE 2021), Mexico.
  • S. P. Ardakani, X. Wu, S. Pan, and X. Gao (Apr 2021). “ARM: A Real-time Health Monitoring Mobile Application.” 5th EAI International Conference on Computer Science and Engineering in Health Services (COMPSE 2021), Mexico. 
  • A. Cheshmehzangi, F. Chan, M. Sedrez, S. P. Ardakani, J. Sun and L. Li (Apr 2020). “The Nexus between Sponge-City and Stormwater Management: A Comprehensive Scenario-based Analysis in Ningbo, China.” UNNC Symposium on Disruption vs Integration: Pathways to Urban Transformation, Ningbo, China. 
  • Z. Hashemi, S. P. Ardakani, M. S. Torkestani (Sep 2018). “Impact of Descriptive Text-boxes on Tourism using Eye-tracking.” First International Conference on Management and Engineering, Tehran, Iran.

Peer-reviewed Conferences

  • S. Ghosh, M. Al-khafajiy, S. P. Ardakani, and T. Baker (Nov 2025). “Personalised Federated Learning at Scale: Hierarchical Boosting with Bayesian Fusion.” 18th International Conference on Development in eSystem Engineering (DeSE), Bucharest, Romania.
  • N. B. Masood, S. P. Ardakani, and M. Yu (Aug 2025). “A Transformer-based Deep Learning Model to Enhance Hope Speech Detection.” 9th International Conference on Deep Learning Technologies (ICDLT), Chengdu, China.
  • L. Gong, S. Mccall, M. Yu, M. Thota, G. S. Kashyap, and S. P. Ardakani (Aug 2024). “Innovate Spatial-Temporal Attention Network (STAN) for Accurate 3D Mice Pose Estimation with a Single Monocular RGB Camera.” 32nd European Signal Processing Conference (EUSIPCO), Lyon, France.
  • K. Nan, S. Hu, H. Luo, P. Wong, and S. P. Ardakani (Dec 2022). “A Semi-supervised Learning Application for Hand Posture Classification.” 12th EAI International Conference on Big Data Technologies and Applications (BDTA 2022), Cairo, Egypt.
  • S. P. Ardakani, C. Zhou, X. Wu, Y. Ma, and J. Che (Dec 2021). “A Data-driven Affective Text Classification Analysis.” 20th IEEE International Conference on Machine Learning and Applications (ICMLA), Pasadena, USA. 
  • S. P. Ardakani, X. Liu, and H. Xie (Apr 2021). “A Data-driven Study to Highlight the Correlations Between Ambient Factors and Emotion.” 5th EAI International Conference on Computer Science and Engineering in Health Services (COMPSE 2021), Mexico.
  • S. P. Ardakani, X. Wu, S. Pan, and X. Gao (Apr 2021). “ARM: A Real-time Health Monitoring Mobile Application.” 5th EAI International Conference on Computer Science and Engineering in Health Services (COMPSE 2021), Mexico.
  • A. Cheshmehzangi, F. Chan, M. Sedrez, S. P. Ardakani, J. Sun and L. Li (Apr 2020). “The Nexus between Sponge-City and Stormwater Management: A Comprehensive Scenario-based Analysis in Ningbo, China.” UNNC Symposium on Disruption vs Integration: Pathways to Urban Transformation, Ningbo, China
  • Z. Hashemi, S. P. Ardakani, M. S. Torkestani (Sep 2018). “Impact of Descriptive Text-boxes on Tourism using Eye-tracking.” First International Conference on Management and Engineering, Tehran, Iran.

Editorials

S. P. Ardakani, G. Kapogiannis, M. Al-khafajiy, and M. Yu (Aug 2025). “Data Analytics in Sustainable City Planning.” Frontiers in Sustainable Cities, Vol. 7.

 

Supervision

I’d welcome enquiries from highly motivated students interested in pursuing a PhD/MRes in Computer Science. Prospective applicants are encouraged to email their CV along with a brief draft research proposal outlining their intended area of study and research interests.

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