My research focuses on deep learning (DL), computational biomechanics, human factor and ergonomics (HFE), non-linear dynamics of biomedical signals, and time-series analysis in biomechanical systems and applications. Biomechanical systems, particularly motion capture (MoCap) systems, have been used in different applications to significantly improve treatment efficacy, patient care, and neuromuscular diagnostic techniques. My goal is to address the limitations of the traditional biomechanical approaches by developing the user-independent DL-based biomechanical gait analysis in MoCap systems while utilizing the DL algorithms, and non-linear time-series data analysis.

My research vision is to develop cost-efficient, portable, and user-friendly healthcare and manufacturing equipment and technologies. This contribution aims to advance the fields of HFE, manufacturing, and healthcare systems in response to societal needs, particularly for the undeserved and underrepresented populations. Given my extensive background in HFE, non-linear dynamics of biomedical signals, time-series analysis, DL applications, and computational biomechanics, I am committed to pursuing my research in the field of healthcare. Ultimately, my goal will be to harness emerging technologies that present significant potential in addressing the escalating challenges in healthcare problems.