Sharareh Taghipour

Toronto Metropolitan University, Metropolitan University

Papers

Total Citations

H-Index

About

Sharareh Taghipour is a researcher whose work spans the intersection of robotics, optimization, and public health engineering. Her scholarship has made meaningful contributions to autonomous systems and intelligent algorithms, with particular emphasis on real-world applications that address pressing societal challenges. Taghipour's most influential work focuses on UV disinfection robotics, with her 2022 comprehensive review of UV disinfection robots accumulating an impressive 76 citations in a short period, reflecting the urgency and relevance of autonomous sanitation solutions — especially in the wake of global health crises. This work has positioned her as a notable voice in the emerging field of health-oriented robotics. Beyond robotics applications, Taghipour has pursued research in computational intelligence and combinatorial optimization. Her work on the Pareto Frontier Approximation Network (PA-Net) tackles the classic Travelling Salesperson Problem through a bi-objective lens, developing neural network-driven approaches to multi-objective planning and scheduling challenges that are fundamental to robotic autonomy and resource allocation. Together, these contributions reveal a researcher who bridges theoretical algorithmic innovation with applied robotics, producing work that is both technically rigorous and practically impactful across healthcare, automation, and intelligent systems domains.