Berdakh Abibullaev, PhD

Assistant Professor

Accepting PhD Students

PhD projects

Brain-Computer/Machine Interfaces (BCI/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 humans and an external device without involving any peripheral and muscular activity. Our research 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 work on the following research topics: (i) to enable communication capability between brains and computers; (ii) to develop neural interfaces to restore human motor functions after stroke; (iii) to develop brain-actuated assistive robotic systems for disabled persons; (iv) to advance machine learning research on decoding the human mental state from data.

  • 360 Citations
  • 10 h-Index
20082019

Research output per year

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Personal profile

Personal profile

Dr. Berdakh Abibullaev received his M.Sc. and Ph.D. degrees in electronic engineering from Yeungnam University, South Korea in 2006, and 2010,  respectively. He held research scientist positions at Daegu-Gyeongbuk Institute of Science and Technology (2010-2013) and at Samsung Medical Center,  Seoul,  South Korea (2013-2014). In 2014,  he received the National Institute of Health postdoctoral research fellowship II to join a multi-institutional research project between the University of Houston Brain-Machine Interface Systems Team and Texas Medical Center in developing neural interfaces for rehabilitation in post-stroke patients. He is currently an Assistant Professor at Robotics Department, Nazarbayev University,  Kazakhstan. His research focuses on developing robust Brain-Machine Interfaces for people with severe motor impairments.

External positions

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Research Output

  • 360 Citations
  • 10 h-Index
  • 21 Conference contribution
  • 15 Article
  • 1 Chapter
  • 1 Comment/debate
  • Deep Learning Models for Subject-Independent ERP-based Brain-Computer Interfaces

    Tuleuov, A. & Abibullaev, B., May 16 2019, 9th International IEEE EMBS Conference on Neural Engineering, NER 2019. IEEE Computer Society, p. 945-948 4 p. 8717088. (International IEEE/EMBS Conference on Neural Engineering, NER; vol. 2019-March).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Design and Optimization of a BCI-Driven Telepresence Robot Through Programming by Demonstration

    Abibullaev, B., Zollanvari, A., Saduanov, B. & Alizadeh, T., Aug 5 2019, In : IEEE Access. 7, p. 111625 111636 p.

    Research output: Contribution to journalArticle

    Open Access
  • Novel Spatiospectral Features of ERPs Enhances Brain-Computer Interfaces

    Orazayev, Y., Zollanvari, A. & Abibullaev, B., Feb 2019, 7th International Winter Conference on Brain-Computer Interface, BCI 2019. Institute of Electrical and Electronics Engineers Inc., 8737344. (7th International Winter Conference on Brain-Computer Interface, BCI 2019).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Brain-Computer Interface Humanoid Pre-trained for Interaction with People

    Saduanov, B., Tokmurzina, D., Alizadeh, T. & Abibullaev, B., Mar 1 2018, HRI 2018 - Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction. IEEE Computer Society, p. 229-230 2 p. (ACM/IEEE International Conference on Human-Robot Interaction).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution