Madi Babaiasl
Papers
2
Total Citations
4
H-Index
2
About
Dr. Madi Babaiasl is a rising leader at the intersection of artificial intelligence, neuroengineering, and assistive robotics. Her research focuses on decoding human motor intent by fusing multimodal neurophysiological signals—primarily electroencephalography (EEG) and electromyography (EMG)—to create more intuitive and responsive human-machine interfaces. Dr. Babaiasl’s major contributions include pioneering transformer-based architectures for intent recognition, notably through her work on **NeuroFusion-Trans**, a novel model that integrates EEG and EMG data for enhanced user intent detection in assistive robotics. She also developed **EMG-TransNN-MHA**, a transformer-based model leveraging multi-head attention mechanisms to improve motor intent recognition from muscle activity alone. These innovations address critical challenges in real-time control of prosthetic limbs and rehabilitation robots. Though her most-cited papers are recent (2024–2025), they have already garnered citations, signaling strong early impact. Her work is foundational for next-generation co-robots that can seamlessly anticipate and adapt to human movement, promising to restore mobility and independence for individuals with motor impairments.
Research Focus
Key Achievements
Top Papers
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