Berdakh Abibullaev

School of Engineering and Digital Sciences, Robotics and Mechatronics
Assistant Professor
+7 (7172) 706664


Dr. Berdakh Abibullaev earned his Ph.D. in Electronic Engineering from Yeungnam University in 2010, South Korea. He held research positions at Daegu-Gyeongbuk Institute of Science and Technology (DGIST) and in the Neurology Department of Samsung Medical Center, Seoul, Korea. He was also appointed as a research professor at Sungkyunkwan University, Seoul. In 2014, he was awarded NIH (National Institute of Health, USA) postdoctoral research fellowship to join a multi-institutional research project between the University of Houston Brain-Machine Interface Systems Team and various clinical institutions at Texas Medical Center in developing novel neural interfaces for neurorehabilitation in post-stroke patients. Currently, he is an assistant professor at the School of Science and Technology, Robotics and Mechatronics Department, Nazarbayev University.

Dr. Abibullaev has considerable research and clinical experience working with patient populations and physicians in applying scientific and technical skills to advance the development of treatments for neurological disorders. His research focuses on developing new non-invasive Brain-Computer/Machine Interfaces for communication and rehabilitation of patients with severe motor impairment. 
Reseach Area
The BMI research aims to restore or substitute lost motor function in patients with neurological conditions such as stroke, spinal cord injury, amyotrophic lateral sclerosis or in patients with amputated limbs. This technology, which is also known as a thought-translation device, is based on building a direct communication and control channel between human and an external device without involving any peripheral and muscular activity [1] (see Fig. 1).

Fig.1. A brain-machine interface system decodes different brain activity patterns produced by a user and translates into appropriate control and communication commands.

BMI systems have already been employed to control external devices, e.g. computer cursors [2] and robotic prostheses [3], using invasive methods.  Moreover, in recent studies, BCIs have been used to control lower-body and upper-body exoskeletons for stroke and paraplegic recovery and rehabilitation via non-invasive approaches [4].

Our research at NU focuses on the development and cross-validation of new neurotechnologies in Kazakhstan to improve the quality of life for disabled people, at the interface between engineering, robotics, and neuroscience.  Currently, we are working on the following research topics:

  • to enable communication capability between brains and computers,
  • to develop neural interfaces to restore human motor functions after stroke.
  • to develop brain-actuated assistive robotic systems for disabled persons

Design and optimization of a Brain-Computer Interface speller in the Kazakh language.

Recently, we have finished the design and optimization of the Kazakh language based BCI speller on healthy subjects and plan to conduct clinical trials with patients suffering amyotrophic lateral sclerosis (ALS). This research will be conducted in collaboration with the National Center for Neurosurgery in Astana, and it should enable patients to communicate with their relatives, and caregivers via our BCI technology.  

Fig.2. The Kazakh language speller. The BCI decodes electrical brain activities time-locked to visual sensory stimulus associated with the selection of a specific character and thus allowing mental typing (see the demo at

Opportunity for students

The undergraduate and graduate students at NU  have an opportunity to actively participate in the projects related to BMI/BCI systems with the investigator. Our lab is equipped with high-density 64-channel scalp electroencephalography system (Guger Technologies, Austria) with active electrode caps.  The research mentioned is wide enough to create many strong thesis topics for any students who are interested in the research to  build novel neural interfaces for different applications. If interested please contact me at 

  1. Wolpaw, Jonathan R., et al. “Brain–computer interfaces for communication and control.” Clinical neurophysiology 113.6 (2002): 767-791.
  2. Kim, Sung-Phil, et al. “Point-and-click cursor control with an intracortical neural interface system by humans with tetraplegia.” IEEE Transactions on Neural Systems and Rehabilitation Engineering 19.2 (2011): 193-203.
  3. Hochberg, Leigh R., et al. “Reach and grasp by people with tetraplegia using a neurally controlled robotic arm.” Nature 485.7398 (2012): 372-375.
  4. Venkatakrishnan, Anusha, Gerard E. Francisco, and Jose L. Contreras-Vidal. “Applications of brain–machine interface systems in stroke recovery and rehabilitation.” Current physical medicine and rehabilitation reports 2.2 (2014): 93-105.