Tariq Shahzad
Papers
3
Total Citations
17
H-Index
2
About
Tariq Shahzad is a forward-looking researcher working at the intersection of nanomedicine, artificial intelligence, and industrial automation. His work spans two transformative domains: the development of nanotechnology-based therapeutics and the application of computational intelligence to real-world systems. In his highly cited 2023 paper, Shahzad introduced the concept of the Gold Nano Thermo Robot (GNTR) for treating chronic diseases, a visionary approach that has already garnered 13 citations and demonstrates the potential of nanorobotics to revolutionize healthcare. He has also made significant contributions to practical AI, conducting a comparative study of Teachable Machine, MobileNet, and YOLO for object detection—work that provides actionable insights for deploying lightweight models in real-world applications. More recently, Shahzad has explored how deep learning architectures can enhance big data analytics within Industry 4.0 and 5.0 frameworks, highlighting the role of computational intelligence in enabling autonomous industrial systems. His research is characterized by a clear focus on translating cutting-edge technology into tangible solutions, from medical nanorobots to efficient object detection models, making his work highly relevant for students and researchers interested in the future of AI-driven healthcare and smart manufacturing.
Research Focus
Key Achievements
Top Papers
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