Berdakh Abibullaev, PhD

Associate Professor

Accepting PhD Students

PhD projects

Our primary research objective is to develop advanced machine learning algorithms that can analyze and interpret neural signals to gain a deeper understanding of neural activity and its implications. This will enable the development of innovative techniques for capturing and interpreting brain activity in a non-invasive way. Our focus is on contributing to the brain-computer/machine interfaces field, which can assist individuals with disabilities, enhance human capabilities, and revolutionize human-machine interaction.

Our multidisciplinary approach combines expertise from computer science, neuroscience, engineering, and psychology. We employ advanced supervised and unsupervised machine learning algorithms, including state-of-the-art deep learning models and non-invasive technologies such as EEG, EMG, and fNIRS for data collection. We also develop real-time data analysis and feedback systems and conduct user experience tests and clinical trials. Our work has potential applications in a variety of fields including assistive technologies, virtual reality and gaming interfaces, medical diagnostics and therapeutics, and cognitive enhancement tools.

If you are interested in our work or would like to join our team, please feel free to contact us at [](

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Personal profile

Personal profile

Dr. Berdakh Abibullaev received his M.Sc. and Ph.D. in electronic engineering from Yeungnam University, South Korea in 2006 and 2010. He worked at Daegu Gyeongbuk Institute of Science and Technology (2010-2013) and Samsung Medical Center (2013-2014), and in 2014 he joined the University of Houston, TX, USA, as a Postdoctoral Research Fellow II supported by the National Institute of Health. He is currently an Associate Professor at the Robotics Department, Nazarbayev University, Kazakhstan. His research is centered around developing machine learning techniques to solve inference problems in Brain-Computer Interfaces. 

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