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About

Usman Tariq’s research sits at the intersection of artificial intelligence, healthcare, and robotics, where he develops intelligent systems that can perceive, predict, and act. His most impactful work, a 2022 study on Alzheimer’s disease prediction, has garnered 58 citations for its use of Long Short-Term Memory networks to create a biomarker-based framework for early diagnosis—a critical step in improving patient outcomes. In computer vision, his 2021 paper on multi-layered deep learning feature fusion for human action recognition (51 citations) advances how machines interpret complex human movements, with applications in surveillance and robotics. Tariq also pioneers rehabilitation robotics, employing fuzzy logic architectures to enable remote control of assistive devices, and addresses security in the Industrial Internet of Things with context-aware autonomous systems. His work extends to predicting human motion trajectories using generative adversarial networks and developing autonomous robots for recycling plastic bottles. Across these domains, Tariq consistently demonstrates a commitment to translating machine learning innovations into practical, socially beneficial technologies, making him a notable contributor to both theoretical and applied AI research.