I am an Assistant Professor specializing in the intersection of signal processing, compressive sensing, and artificial intelligence. My research is driven by solving practical problems in biomedical engineering and computer vision. A core focus is developing novel compressive sensing and sparse representation algorithms for efficient data classification, which I have applied to critical areas such as prostate cancer detection from mass spectrometry data and robust face recognition. Recent work includes COVID-19 detection using deep learning and point cloud clustering for autonomous driving applications. I have successfully published my findings in reputable journals and IEEE conferences, secured research grants, and actively contribute to the academic community as a reviewer for several prominent journals including IEEE Access and Springer Nature publications. My work aims to bridge advanced theoretical concepts with impactful real-world applications.