Mohammad Reza Keshtkaran

This paper introduces NoMAD, a method that stabilizes brain-computer interfaces by aligning latent dynamics, achieving stable decoding without supervised recalibration over long periods.

This paper introduces AutoLFADS, an automated framework for estimating neural population dynamics from neural data without supervisory information, validated on multiple datasets.

This paper uses a deep learning model to estimate muscle activation from EMG signals, showing improved performance over traditional methods in predicting joint kinematics and force.