Maryam Gholinejad

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About

Dr. Maryam Gholinejad is a rising leader in surgical data science, whose work bridges machine learning and motion tracking to advance the precision of modern surgery. Her primary research focuses on non-optical motion tracking systems (NOMTS), where she investigates how artificial intelligence can interpret subtle surgical movements to improve outcomes. In her landmark 2025 systematic review—already garnering 14 citations—Dr. Gholinejad rigorously analyzed over 3,600 records to map the landscape of ML applications in surgical motion analysis. This work not only identified key objectives and experimental designs but also charted critical future directions for the field. By demonstrating how NOMTS can be used alone or alongside optical methods, she has provided a foundational framework for researchers and clinicians seeking to integrate intelligent motion tracking into the operating room. Her contributions are particularly notable for their methodological rigor and translational potential, offering a roadmap for safer, data-driven surgical training and real-time performance feedback. Dr. Gholinejad’s research stands at the intersection of computer vision, biomechanics, and clinical practice, making her a vital voice in the next generation of surgical innovation.