Berdakh Abibullaev, PhD

Department: Robotics and Mechatronics
Position: Assistant Professor
Office: 7e.318
Phone: +7 (7172) 706664


2010 – Ph.D. Yeungnam University, South Korea

2006 – M.Sc. Yeungnam University, South Korea

2004 – B.Sc. Tashkent University of Information Technologies, Uzbekistan 




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 on developing novel neural interfaces for neurorehabilitation in poststroke 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 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 and Neuroprosthetics to restore motor function in patients with stroke. 


Keywords:  Brain-Computer/Machine Interfaces; Machine Learning; Epilepsy Research; Stroke Rehabilitation. 



  1. Abibullaev, B., An, J., Lee, S. H., & Moon, J. I. (2016). Design and evaluation of action observation and motor imagery based BCIs using Near-Infrared Spectroscopy. Measurement, 98, 250–261 
  2. N.A. Bhagat, A. Venkatakrishnan, B. Abibullaev, E.J. Artz, N. Yozbatiran, A. Blank, J. French, C. Karmonik, R.G.Grossman, M.K O’Malley, G. Francisco, J.L. Contreras-Vidal. Design and optimization of an EEG-based brain machine interface (BMI) to an upper-limb exoskeleton for stroke survivors. Frontiers in Neuroscience, 2016.
  3. Cruz-Garza JG, Hernandez ZR, Tse T, Caducoy E, Abibullaev B, Contreras-Vidal JL. A novel experimental and analytical approach to the multimodal neural decoding of intent during social interaction in freely-behaving human infants. Journal of Visualized Experiments, 2015.
  4. Park, C.H., Seo, J.H, Kim, D., Abibullaev, B., Kwon, H., Lee, Y.H., Kim, M.Y., Kim, K. Kim, J.S. Joo, E.Y., Hong, S.B. (2015, Feb). EEG Source Imaging in Partial Epilepsy in Comparison with Presurgical Evaluation and Magnetoencephalography, J. Clin Neurol.
  5. Abibullaev, B., An, J., Jin, S. H., Lee, S. H., & Moon, J. I. (2013). Minimizing inter-subject variability in fNIRS-based brain–computer interfaces via multiple-kernel support vector learning. Medical engineering & physics, 35(12), 1811-1818.