News & Updates
Stay updated with my latest research, publications, talks, and other activities.
Upcoming Events
IEEE 5th International Conference on Computing and Machine Intelligence
King Faisal University, Saudi Arabia
Biometric Security in the Era of AI
University of Glasgow, Glasgow
Recent News
Presenting GAN-Based Medical Imaging Research at MICAD 2025
A team member presented PhD research at the International Conference on Medical Imaging and Computer-Aided Diagnosis in London. The work explores using generative adversarial networks to standardize ultrasound tongue images for speech disorder diagnosis.
Advance in Multilingual Voice Anti-Spoofing Research
MIMER project achieves major milestone with the acceptance of a significant MSS dataset paper at IEEE CBMI 2025 in Dublin. This first-of-its-kind multilingual spoofed speech dataset addresses critical challenges in deepfake detection and digital identity fraud.
Join Our Team: Generative AI Specialist Wanted
KTP project LEAP is hiring a Generative AI & Large Language Model Specialist for a London-based position. Exciting opportunity to work at the cutting edge of AI research with real-world applications.
Shaping the Future of Wireless Networks on Coursera
Proud to contribute to the new "6G for a Connected Future" specialization on Coursera, designing and delivering the module on multimodality-enabled smart wireless networks. From learner to contributor—completing the cycle of knowledge sharing.
Expanding Cybersecurity Research with New HEC Funding
MIMER project secures additional NRPU grant from HEC Pakistan to advance the fight against AI-generated audio deception in critical real-time scenarios. Strengthening UK-Pakistan research collaborations in deepfake detection beyond 2026.
Smart Grid Security Research Published in High-Impact Journal
A team member's research on fusion-enhanced federated learning for smart grid security has been published in Engineering Applications of Artificial Intelligence. The work introduces a defense framework to address adversarial attacks in federated learning systems for power networks.
Celebrating Academic Excellence: PhD Graduation Success
Graduation day at the University of Glasgow's James Watt School of Engineering marks the completion of a transformative PhD journey in Electrical Engineering. A milestone of gratitude, reflection, and pride, looking forward to the next chapter.
Mentorship Milestone: Dr. Fahad Ayaz's PhD Defense
Immensely proud to witness Fahad Ayaz's successful PhD defense on AI-driven radar-based human activity recognition. His research bridges technical innovation with real human impact—a testament to dedication, collaboration, and the privilege of mentorship.
Strategic Partnership with Pakistan's National CERT
MIMER team meets with Dr. Haider Abbas and National CERT Pakistan to present project progress on tackling deepfakes and digital identity fraud. A significant step toward bridging academic research with national cybersecurity initiatives for public digital safety.
Supporting Educators Through AI: New KTP Project LEAP
Grateful to receive Innovate UK funding for a 2-year Knowledge Transfer Partnership with AWTG Ltd to develop LEAP, an AI platform designed to support teachers and enhance student learning. The goal is to amplify educator expertise through adaptive pathways and dialogue-driven thinking.
New Publication on Federated Blockage Prediction in Wireless Networks
Our paper on Semantic-Aware Federated Blockage Prediction published in IEEE Transactions on Network and Service Management. The SFBP framework explores lightweight edge-based computer vision for next-generation wireless systems, showing encouraging results in reducing communication overhead.
Presenting MIMER Project at ASEAN-Pakistan Technology Expo
Grateful for the opportunity to share our EPSRC-funded research on mitigating presentation attacks in remote identity proofing at APTEX'25's Cybersecurity session. The event brought together 18 ASEAN delegates and over 600 participants to discuss AI-powered approaches for digital identity security in Pakistan's banking sector.
Demonstrating AI-Powered Identity Security at PINTECH'25
Showcased the MIMER project at the All Punjab Innovation and Technology Expo in Lahore, demonstrating our approach to tackling deepfakes and spoofing attacks in Pakistan's banking sector. A meaningful step in connecting academic research with practical industrial applications.
New Research on Adversarial Robustness in Federated Load Forecasting
Research examines the balance between global and local learning in federated systems, demonstrating how increased local training can enhance model robustness against adversarial attacks. The work offers new insights for securing distributed learning frameworks in energy forecasting applications.
Exploring AI and Dialogic Learning at EduCon2025
Valuable discussions at EduCon2025 about reimagining education in the age of AI. Rupert Wegerif's insights on combining AI with dialogic teaching approaches sparked important reflections on how we might think alongside these tools rather than simply using them.
New Publication on Adaptive Computation for Federated Learning
Our paper on Adaptive Computation Amount Allocation published in IEEE Transactions on Mobile Computing. The ACAA approach addresses computation challenges in federated learning for heterogeneous IoT devices, showing encouraging improvements in training efficiency while maintaining privacy.
Privacy-Preserving Load Forecasting for Smart Grids
Research from our group introduces federated SDTA for secure energy demand prediction in power systems. The mechanism enables utilities to collaborate on load forecasting while protecting sensitive data and defending against adversarial attacks.
Engaging with Research Community at IEEE INMIC 2024
Attended the 26th IEEE INMIC conference in Karachi, chairing a technical session and participating in a panel on digital transformation in engineering education. Valuable opportunity to present the MIMER project findings and connect with colleagues for future collaborations.
Celebrating PhD Success: UAV Communications Research
Proud to share that a team member successfully passed their PhD viva with research on leveraging machine learning and computer vision for advanced UAV communications. Grateful for the collaborative effort and looking forward to their continued contributions to the field.
Open-Access Survey on Federated Learning Security
Our team's open-access survey examines defense strategies against attacks in federated learning systems, covering data protection, model security, and privacy preservation. The analysis offers insights relevant for designing secure cyber-physical networks in critical national infrastructure.
Decentralized Federated Learning Enhances Smart Grid Security
New research published in Energy and Buildings explores adversarial robustness in federated load forecasting, comparing centralized and decentralized approaches. Findings suggest decentralized methods offer stronger resilience against model poisoning attacks in smart building energy systems.
Federated Learning Survey Recognized Among Top Journal Articles
Grateful that our 2023 paper on edge-native intelligence for 6G communications has been listed among the 50 most popular articles in IEEE Transactions on Emerging Topics in Computational Intelligence. The survey examines federated learning applications across next-generation wireless networks.
PhD Research Presented at BIOSTEC 2024 in Rome
A team member presented PhD research on automated phonetic classification at the International Conference of Bioimaging in Rome. The work explores AI and machine learning applications for advancements in linguistics and speech therapy.
UKRI Awards Funding for MIMER Project on Digital Identity Security
Honored to receive UKRI funding as Principal Investigator for a two-year project addressing presentation attacks in remote identity proofing, with focus on Pakistan's banking sector. Collaborating with UET Taxila and STech.ai to develop AI solutions against deepfakes and banking fraud.
Third IEEE Transactions Publication on Federated mmWave Networks
A team member completed their PhD research with publication of the RaDaR framework in IEEE Transactions on Mobile Computing. The work explores radar-aided dynamic blockage recognition to enhance reliability in federated mmWave networks while considering latency and quality metrics.
PhD Viva Success: Mohammad Al-Quraan
Proud moment as co-supervisor witnessing Mohammad Al-Quraan successfully pass his PhD examination. Grateful to have been part of his research journey and to see him reach this significant milestone.
External Examiner Role at University of Leeds
Grateful for the opportunity to serve as external examiner for a PhD thesis on Non-Intrusive Load Monitoring at the University of Leeds. The work explores important intersections between energy efficiency, privacy preservation, and AI-driven energy management.
Recognition in Stanford's Top 2% Most Cited Scientists List
Honored to be included in Stanford University's list of the top 2% most cited scientists globally. Grateful to all collaborators and colleagues who have contributed to this shared achievement through our research efforts.
External PhD Examiner at Tallinn University of Technology
Grateful for the opportunity to serve as external PhD examiner for Taavi Laadung at Taltech University in Tallinn, Estonia. The research represents important work in the field, and it was a privilege to contribute to the examination process.
Invited Paper on Blockchain-Assisted UAV Communications Published
Our team's invited paper in IEEE Open Journal of Vehicular Technology explores blockchain's role in securing UAV communication systems. The work examines how decentralized technologies can enhance data integrity, privacy, and coordination in unmanned aerial vehicle networks.
FedraTrees Framework Published in Engineering Applications of AI
Our paper introduces FedraTrees, a lightweight federated learning framework leveraging ensemble learning. The approach shows encouraging efficiency gains, requiring significantly reduced computation time and communication rounds compared to conventional methods.
Survey on Edge-Native Intelligence for 6G Published in IEEE
Our comprehensive survey on federated learning for 6G communications published in IEEE Transactions on Emerging Topics in Computational Intelligence. The work explores fundamentals, enabling technologies, and applications of FL in next-generation wireless networks.
FedBranch Framework for Anomaly-Aware Load Forecasting
Our research introduces FedBranch, a clustering-based federated learning approach for handling diverse client data in energy networks. The framework uses probabilistic methods to improve short-term load forecasting accuracy across substations while preserving privacy.
Presenting Vision-Aided Blockage Prediction at IEEE WCNC Glasgow
Grateful for the opportunity to present research on federated learning for reliable mmWave systems at IEEE WCNC in Glasgow. The work explores using camera sensors to predict beam blockages in B5G and 6G networks while maintaining quality of experience for users.
First IEEE Transactions Paper on Vision-Aided Wireless Networks
A team member published their first IEEE Transactions paper on intelligent beam blockage prediction in IEEE Transactions on Network and Service Management. The work explores the integration of computer vision and machine learning for future vehicular communication networks.
Collaborative Research Reaches 1,000 Citation Milestone
Grateful to see collaborative work with colleagues reaching 1,000 citations, reflecting the continued relevance of the research. A reminder of the value of teamwork and the lasting impact of well-executed research collaborations.
Showcasing 5G Healthcare Innovation at UK 5G Showcase
Our team demonstrated activity monitoring research from the 5G New Thinking Project at the UK 5G Showcase in Birmingham. The work explores how 5G technology can support healthcare systems and improve quality of life through advanced sensing capabilities.
Special Issue on Machine Learning for Energy-Efficient IoT Networks
Serving as editor for a special issue on machine learning techniques for energy-efficient IoT networks. The call for papers welcomes quality submissions exploring the intersection of ML and sustainable IoT systems.
5G-Enabled Remote Robotics Featured in National Media
Our team's work on 5G-enabled remote laboratory access was featured in national technology press. The project demonstrates how students can conduct experiments using robotic systems from anywhere in the world, marking a significant advancement in remote education capabilities.