Rate My Professor Ashiq Anjum

Anjum's research specializations encompass data-intensive distributed systems for high-performance analytics, distributed scalable and parallel machine learning models, self-adapting federated networks of digital twins, and physics-informed neural networks for trustworthy emulation of cyber-physical systems. His work addresses AI-driven digital twins for net zero emissions and clinical care, distributed clinical intelligence, iterative genome analytics for personalized medicine, real-time object tracking in video streams, and applications in telecoms, aerospace, earth observation, manufacturing, environmental degradation, and space missions. He has secured grants from EPSRC such as EP/Y00597X/1 for AI-driven digital twins for net zero and EP/Y018281/1 for clinical care, alongside funding from UKRI, STFC, Innovate UK, and the European Commission. These efforts have generated over £5 million in research income, produced two impact case studies, and fostered 15 knowledge transfer partnerships with regional SMEs. As AI lead for the £60 million METEOR flagship project at Space Park Leicester, his contributions extend to industrial and societal impact. Key publications include "Blockchain standards for compliance and trust" (IEEE Cloud Computing, 2017), "Towards cloud based big data analytics for smart future cities" (Journal of Cloud Computing, 2015), "Explaining deep neural networks: A survey on the global interpretation methods" (Neurocomputing, 2022), "Video stream analysis in clouds: An object detection and classification framework for high performance video analytics" (IEEE Transactions on Cloud Computing, 2016), and "Congestion prediction for smart sustainable cities using IoT and machine learning approaches" (Sustainable Cities and Society, 2021). His scholarship has amassed over 9,200 citations. Anjum has served as EPSRC Grant Panelist in 2023 and Science Foundation Ireland Panellist.