Sina David

Dr. Sina David is an Assistant Professor at Vrije Universiteit Amsterdam, holding dual affiliations in the Faculty of Behavioural and Movement Sciences (Biomechanics department) and AMS - Rehabilitation & Development. Their research focuses on biomechanical applications of machine learning in healthcare, particularly stroke rehabilitation, injury prevention, and gait analysis. David has led projects like the Rethinking risk of falls in stroke survivors using machine learning approaches and contributed to initiatives like Snowboard TeamExtreme, applying biomechanics to sports performance.

Current academic roles include teaching Data in Sport and Health, Movement Analysis, and collaborating on courses like Klinische Bewegingsanalyse. David is actively involved in developing open-source tools for gait recognition and has pioneered methods like the RYSEN body weight supported gait training system. Their work integrates unsupervised learning techniques to extract clinical biomarkers from motion data, advancing personalized rehabilitation strategies.

Key contributions span 62 research outputs, emphasizing neural network applications in biomechanics. Media engagements include discussions on stroke rehabilitation advancements and AI-driven sports technology. David’s research bridges computational methods with clinical outcomes, aiming to improve mobility recovery and athletic performance through data-driven approaches.