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About

Janice Glasgow is a multidisciplinary researcher whose work spans two distinct but equally impactful domains: robotic assessment of neurological impairment following stroke, and computational approaches to macromolecular crystallography. Her most influential contributions lie in revolutionizing how clinicians quantify sensorimotor deficits in stroke survivors, moving beyond subjective ordinal scales toward precise, robot-assisted measurement. Her 2009 study on limb position sense (380 citations) and her 2010 work on visually guided reaching using robotic technology (284 citations) established foundational methodologies for objective upper-limb assessment, directly improving the sensitivity and reliability of stroke rehabilitation evaluations. Her subsequent development of robotic object-hitting tasks and machine learning-based classification approaches further advanced this field, enabling clinicians to better predict patient outcomes and tailor interventions. In parallel, Glasgow made notable contributions to structural biology, applying intelligent decision-support systems and high-throughput laboratory methods to protein crystallization—work that supports the broader goal of accelerating protein structure determination. With over 960 citations across her body of work, Glasgow has demonstrably shaped modern stroke assessment practices while bridging computer science, clinical neuroscience, and structural biology in ways that continue to benefit both researchers and patients.