Mohammad Abu-Alqumsan

About

Mohammad Abu-Alqumsan is a pioneering researcher at the intersection of brain-computer interfaces (BCIs), robotics, and assistive technology. His work centers on developing intelligent systems that allow humans—particularly individuals with motor impairments—to control and embody robotic avatars using neural signals. A key contribution is his demonstration of how P300-based BCIs can enable both local and remote cooperation with virtual and robotic agents, a breakthrough validated in studies involving people living with spinal cord injury (56 citations). He has also advanced continuous control of mobile robots using visual evoked potentials (VEP), achieving high information transfer rates (37 citations). Beyond single-modality control, Abu-Alqumsan introduced the concept of a "Brain-and-Body-Computer Interface" for robotic re-embodiment, integrating neural and physiological signals to perform daily tasks (11 citations). His most recent work tackles the critical bandwidth bottleneck in BCI systems by proposing goal-recognition-based adaptive interfaces that self-adjust to enable fluent, intuitive navigation of immersive robotic platforms (10 citations). Through these innovations, Abu-Alqumsan is shaping a future where thought alone can bridge the gap between human intent and robotic action, offering transformative possibilities for rehabilitation and human augmentation.

Research Focus

Key Achievements

Top Papers

1. 1
   Local and Remote Cooperation With Virtual and Robotic Agents: A P300 BCI Study in Healthy and People Living With Spinal Cord Injury

   56 citations · 2016
2. 2
   A BCI using VEP for continuous control of a mobile robot

   37 citations · 2013
3. 3
   Towards robotic re-embodiment using a Brain-and-Body-Computer Interface

   11 citations · 2012
4. 4
   Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems

   10 citations · 2017

Key Collaborators

Contact & Links