Brain- and AI-Based Neuroprosthetic Controls
Funded by NSF HCC award ID 2516235 (2026-Present)
The project will develop an immersive multimodal Brain-Computer Interface (BCI) framework and deep learning models to decode neural activity, grip types, and movement kinematics during natural plan-to-grasp tasks. It will also create and validate a personalized, real-time closed-loop virtual robotic system to advance both neuroscience understanding and BCI-based prosthetic control.
Shared Human-AI Autonomy Paradigms
Funded by NSF CAREER award ID 2441496 (2025-Present)
The project aims to build multimodal shared human-AI autonomy paradigms to amplify the motor control aspects of patients with upper-limb disabilities. It will create a framework for interaction and teaming between humans and robots to collaboratively complete complex daily tasks such as object manipulation. Our first Demo: https://arxiv.org/abs/2505.11366
Biosignal– and AI-Driven Motor Rehabilitation
Funded by NSF DARE award ID 2245558 & URI Foundation on Medical Research (2023-Present)
The project develops upper-limb assistive robotic systems to enhance human mobility and recover motor control after stroke. It will integrate multimodal biosignals in shared control paradigms to advance motor training for upper limbs using planar robotic systems. Our first Demo: https://arxiv.org/abs/2404.01441
Collaborative Projects
Funded by NIH R01 (2026-Present; PI: Dr. Yalda Shahriari)
The project will develop a multimodal VR-based rhythmic audio-visual stimulation framework to investigate the neural mechanisms underlying rhythmic motor entrainment. It will also model auditory–motor neural interactions and develop a customizable closed-loop system to characterize and enhance neural synchronization with rhythmic stimuli.
Completed Projects
Funded by NIH / RI-INBRE (2022-2024; Single PI: Dr. Reza Abiri)
Can we help patients to modulate their brain activity from abnormal status to normal one? This could be a potential answer to many cognitive disorders such as attention deficit and even help to change the behavioral in patients with obesity and addictions. Demo: https://arxiv.org/abs/2405.02422