Hamed Darbandi

Hamed Darbandi is a researcher at the University of Twente's Mathematics of Operations Research department, specializing in wearable sensor integration with machine learning for equine health monitoring. His 2024 PhD thesis focused on non-invasive fitness assessment in horses, combining biomechanical data with AI techniques.

• Key research areas: Artificial Intelligence, Wearable Sensors, and Biomechanics
• Primary application domain: Equine health and performance assessment

Research trends show strong focus on inertial measurement units (IMUs) for gait analysis, with applications in fatigue detection, lactate estimation, and rider-horse interaction studies. His work applies stochastic modeling and computer vision techniques to sensor data streams.

Recent publications (2021-2024) demonstrate expertise in:

• Edge AI implementations for real-time monitoring
• Deep learning for physiological parameter prediction
• Statistical modeling of biomechanical movement patterns
• Multi-sensor fusion for equine performance assessment