Rashid Mehmood
Papers
5
Total Citations
264
H-Index
5
About
Rashid Mehmood is a leading researcher at the intersection of artificial intelligence, high-performance computing, and smart cities. His work fundamentally explores how AI and machine learning can optimize complex systems, from urban planning to financial markets. Mehmood’s most cited paper, “Artificial Intelligence Technologies and Related Urban Planning and Development Concepts: How Are They Perceived and Utilized in Australia?” (2020, 200 citations), provides a critical analysis of AI adoption in urban contexts, establishing a foundation for smart city research. He is also the creator of the ZAKI and ZAKI+ tools (2019, over 40 combined citations), innovative machine learning-based methods for automatically optimizing parallel sparse matrix-vector multiplication (SpMV) on distributed memory architectures—a core challenge in scientific computing. Demonstrating the breadth of his expertise, Mehmood has applied deep transformer reinforcement learning to develop smart robotic trading strategies for stock markets (2022, 11 citations) and conducted a systematic survey on the use of big data analytics and AI for COVID-19 containment (2023, 10 citations). His work consistently bridges theoretical advances with practical, high-impact tools, making significant contributions to both foundational computing and applied AI for societal challenges.
Research Focus
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