B. Abibullaev


Berdakh Abibullaev, Ph.D.

 

IEEE Senior Member
PhD in Electronic Engineering

Associate Professor @ Nazarbayev University

Machine Learning, Pattern Recognition
Brain-Computer Interfaces

Email: berdakho@gmail.com
[ LinkedIn | Google Scholar | Github | Youtube | Courses ] 

Research Interests

My research interests center on developing sophisticated machine learning and deep learning algorithms to advance biomedical signal processing and brain-computer interface technologies for novel applications in healthcare and beyond.

Machine Learning & Deep Learning 

Dedicated to advancing the capabilities of artificial intelligence, I specialize in machine learning and deep learning with a focus on creating predictive models and intelligent systems that improve decision-making processes across various sectors.

Brain-Computer Interfaces

With a rich background in neurotechnology, I develop interfaces that enable the brain to directly communicate with external devices, enhancing the potential for medical advancements and the creation of assistive technologies.

Signal Processing & Time Series Data Analysis 

My expertise lies in the extraction of meaningful information from complex signals and time series data, employing advanced signal processing techniques to inform and elevate research and development across disciplines.

About Me

Dr. Berdakh Abibullaev, received MSc and Ph.D. in Electronic Engineering from Yeungnam University, South Korea. He has held researcher positions at Daegu-Gyeongbuk Institute of Science and Technology and Samsung Medical Center. He also served as a research professor at Sungkyunkwan University, Seoul. Dr. Abibullaev was a NIH postdoctoral fellow focusing on neural interface development for post-stroke rehabilitation at the University of Houston and Texas Medical Center. Currently an Associate Professor at Nazarbayev University, Kazakhstan, his expertise lies in developing machine learning algorithms for Brain-Computer Interface inference problems.
 

Education

  • Ph.D. in Electronic and Electrical Engineering, Yeungnam University, South Korea (2010)
  • M.Sc. in Electronic and Electrical Engineering, Yeungnam University, South Korea (2006).
  • B.Sc. in Information Technology, Tashkent University of Information Technologies, Uzbekistan (2004).

Professional Experience

  • [08/2022-present] Associate Professor, Robotics & Mechatronics Department, School of Engineering and Digital Sciences, Nazarbayev University, Kazakhstan . 

  • [09/2015-07/2022] Assistant Professor, Robotics & Mechatronics Department, School of Engineering and Digital Sciences, Nazarbayev University, Kazakhstan.  

  • [05/2018 - 07/2018] Visiting Professor, Department of Electrical Engineering & Computer Science, University of Houston, Houston, Texas, USA.  

  • [05/2014 - 09/2015] NIH Postdoctoral Research Fellow II, Department of Electrical Engineering & Computer Science, University of Houston, Houston, Texas, USA. 

  • [01/2014 - 05/2014] Research Scientist, Department of Neurology, Samsung Medical Center, Sungkyunkwan University, Seoul, South Korea. 

  • [02/2010 - 12/2013]  Research Scientist, Robotics Research Division, Daegu Gyeongbuk Institute of Science and Technology, South Korea. 

Academic Service

  • Associate Editor 
  • IEEE Access
  • PeerJ Computer Science

  • Program Committee Member
  • International Workshop on Artificial Intelligence for Healthcare Applications at the International Conference on Pattern Recognition 2020, Italy.
  • The 7th International Conference on New Trends in Information Science, Service Science, and Data Mining, June 18-20, 2013, Jeju Island, South Korea.
  • The 8th International Conference on Information Processing, Management, and Intelligent Information Technology, April 1-3, 2013, Seoul, South Korea.
  • The 16th North-East Asia Symposium on Nano, Information Technology, and Reliability, Oct. 24-26, 2011, South Macao.

  • Session Chair
  • The 6th International Conference on Brain-Computer Interface (BCI), IEEE, 2018, South Korea.
  • IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2017, Daegu, South Korea.
  • The 6th International Conference on Networked Computing, May 11-13, 2010, Gyeongju, South Korea.
  • International Conference on Control Automation and Systems, Oct. 27-30, 2010, Seoul, South Korea.

  • Occasional Reviewer
  • IEEE Transactions on Neural Networks and Learning Systems.
  • IEEE Journal of Biomedical and Health Informatics.
  • IEEE Transactions on Systems, Man, and Cybernetics: Systems.
  • Brain Research, Elsevier.
  • Neuroimage, Elsevier.
  • Medical Engineering and Physics, Elsevier.
  • Medical & Biological Engineering & Computing, Springer.

Technical Skills

  • Software: Expert in Python and libraries such as Cython. Good knowledge of C and C++. Experience with various tools and languages, including bash, LaTeX, HTML, Git, and database query languages.
  • Data Science: Expert in NumPy, Scipy, Scikit-learn, PyTorch, TensorFlow, and Azure DevOps.
  • Neural Data acquisition: Experienced user of Nicolet EEG Amplifiers, Blackrock Microsystems for intracranial recording, Functional Near-Infrared Spectroscopy FOIRE3000, BIOPAC fNIR200 Optical Brain Imaging, BioSemi Active-Two EEG system, Brain Products EEG amp., BIOPAC MP100 EEG amp., and G.tec g.USBamp systems.
  • Productivity applications: LaTeX, BibTeX, PSTricks, Beamer.
  • System Environments: Linux (Ubuntu and Pop!_OS), Windows.

Publications

B. Abibullaev, A. Keutayeva, and A. Zollanvari, “Deep Learning in BCIs: A Comprehensive Review of Transformer Models, Advantages, Challenges, and Applications”  IEEE Access, 10.1109/ACCESS.2023.3329678, 2023 (Link).

A. Keutayeva and B. Abibullaev, "Exploring the Potential of Attention Mechanism-Based Deep Learning for Robust Subject-Independent Motor-Imagery based BCIs," IEEE Access, doi: 10.1109/ACCESS.2023.3320561, 2023 (Link).

B. Abibullaev, Kassymzhomart Kunanbayev, and A. Zollanvari. "Subject-Independent Classification of P300 Event-Related Potentials Using a Small Number of Training Subjects." IEEE Transactions on Human-Machine Systems, DOI: 10.1109/THMS.2022.3189576, 2022 (Link).  

I. Dolzhikova, B. Abibullaev, R. Sameni, A. Zollanvari. "Subject-Independent Classification of Motor Imagery Tasks in EEG using Multi-Subject Ensemble CNN." IEEE Access, DOI:10.1109/ACCESS.2022.3195513, 2022 (Link).  

A. Zollanvari and B. Abibullaev. "Bias correction for linear discriminant analysis." Pattern Recognition Letters, Vol: 151, Pages: 41-47, 2021 (Link).  

B. Abibullaev and A. Zollanvari. "A Systematic Deep Learning Model Selection for P300-Based Brain-Computer Interfaces." IEEE Transactions on Systems, Man, and Cybernetics: Systems, DOI: 10.1109/TSMC.2021.3051136, 2021 (Link).  

B. Abibullaev, I. Dolzhikova, and A. Zollanvari. "A Brute-force CNN Model Selection for Accurate Classification of Sensorimotor Rhythms in BCIs." IEEE Access, DOI: 10.1109/ACCESS.2020.2997681, 2020 (Link).  

A. Zollanvari, M. Abdirash, A. Dadlani, and B. Abibullaev. "Asymptotically Bias-Corrected Regularized Linear Discriminant Analysis for Cost-Sensitive Binary Classification." IEEE Signal Processing Letters, 2019 (Link).

B. Abibullaev and A. Zollanvari. "Learning Discriminative Spatiospectral Features of ERPs for Accurate Brain-Computer Interfaces." IEEE Journal of Biomedical and Health Informatics, vol. 98, pp.1-12, 2019 (Link).  

B. Abibullaev, A. Zollanvari, B. Saduanov, and T. Alizadeh. "Design and Optimization of a BCI-Driven Telepresence Robot Through Programming by Demonstration." IEEE Access, 2019, vol. 7 (Link). 

B Abibullaev, J An, SH Lee, JI Moon. "Design and Evaluation of Action Observation and Motor Imagery-based BCIs using NIRS." Measurement, vol. 98, pp. 250-261, 2017, Elsevier (Link).  

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." Front. Neurosci., vol. 10, March, 2016 (Link).  

J.G. Cruz-Garza, Z.R. Hernandez, T. Tse, E. Caducoy, B. Abibullaev, J.L. Contreras-Vidal. "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, doi:10.3791/53406, October 2015 (Link). 

C.H. Park, J.H Seo, D. Kim, B. Abibullaev, H. Kwon, Y.H. Lee, M.Y. Kim, K. Kim, J.S. Kim, E.Y. Joo, S.B. Hong. "Source Imaging in Partial Epilepsy in Comparison with Presurgical Evaluation and Magnetoencephalography." Journal of Clinical Neurology, 2015 February 17, 11:e12 (Link). 

B. Abibullaev, J An, SH Lee, JI Moon. "Classification of brain hemodynamic signals arising from visual action observation tasks for brain-computer interfaces: An fNIRS study." Measurement, 2014. Elsevier (Link). 

B. Abibullaev, J An, SH Lee, SH Jin, JI Moon. "Minimizing inter-subject variability in fNIRS-based brain-computer interfaces via multiple-kernel support vector learning." Medical Engineering Physics, 2013. Elsevier (Link). 

B. Abibullaev and J. An. "Classification of frontal cortex hemodynamic response during cognitive tasks using wavelet transforms and machine learning algorithm." Medical Engineering Physics, 34(10):1394–410, 2012. Elsevier (Link). 

B. Abibullaev and J. An. "Decision support algorithm for diagnosis of ADHD disorder using electroencephalograms." Journal of Medical Systems, 36(4):2675–2688, 2011. Springer (Link). 

B. Abibullaev, J. An, and J.I. Moon. "Neural network classification of brain hemodynamic responses from four mental tasks." International Journal of Optomechatronics, 5(4):340–359, 2011. Taylor & Francis (Link). 

B. Abibullaev and H.D. Seo. "A new QRS detection method using wavelets and artificial neural networks." Journal of Medical Systems, 35(4):683–691, 2011. Springer (Link). 

B. Abibullaev, M.S. Kim, and H.D. Seo. "Epileptic spike detection using continuous wavelet transforms and artificial neural networks." 8(1):33–48, 2010. International Journal of wavelets, multiresolution and information processing, Worldscientific (Link).  

B. Abibullaev, M.S. Kim, and H.D. Seo. "Seizure detection in temporal lobe epileptic EEGs using the best basis wavelet functions." Journal of Medical Systems, 34(4):755–765, 2010. Springer (Link). 

M.S. Kim, Y.C. Cho, B. Abibullaev, and H.D. Seo. "Analysis of brain functions and Classification of sleep stage EEG using Daubechies wavelet." Sensors and Materials, 20(1):1–15, 2008. MYU, Japan (Link). 

V. Vladislav and B. Abibullaev. "Explainable Deep Learning for Brain-Computer Interfaces through Layerwise Relevance Propagation." In 2023 11th International Winter Conference on Brain-Computer Interface (BCI), pp. 1-5. IEEE, 2023.

I. Dolzhikova, B. Abibullaev, R. Sameni, A. Zollanvari, “An Ensemble CNN for Subject-Independent Classification of Motor Imagery-based EEG,” the 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), October 31 – November 4, 2021

Y. Kainolda, B. Abibullaev, R. Sameni, A. Zollanvari, “Is Riemannian Geometry Better than Euclidean in Averaging Covariance Matrices for CSP-based Subject-Independent Classification of Motor Imagery?”, the 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), October 31 – November 4, 2021

M. Nurpeiissov, B. Abibullaev, T. Alizadeh, “A novel human-robot interaction framework based on Telegram and programming by demonstration,” 9th International Conference on Robot Intelligence Technology and Applications (RITA 2021), on Dec 16 - 17, 2021 at KAIST Daejeon, Korea.

S. Abilkassov, M. Kairgaliyev, B. Zhakanov, B. Abibullaev, “A System For Drivers’ Cognitive Load Estimation Based On Deep Convolutional Neural Networks and Facial Feature Analysis,” in 22nd IEEE International Conference on Industrial Technology, Virtual 10-12, 2021, Spain.

K. Kunanbayev, B. Abibullaev, A. Zollanvari, “Data Augmentation for P300-based Brain-Computer Interfaces Using Generative Adversarial Networks”, in 2021 9th International Winter Conference on Brain-Computer Interface (BCI), 2020, GangWon, South Korea.

K. Kunanbayev, D. Azhigulov, B. Abibullaev, A. Zollanvari, “Deep Transfer Learning for Subject-Independent ERP-based BCIs,” in 2021 9th International Winter Conference on Brain-Computer Interface (BCI), 2020, GangWon, South Korea.

A. Oleinikov, B. Abibullaev, M. Folgheraiter, “On the Classification of Electromyography Signals to Control a Four Degree-Of-Freedom Prosthetic Device,” in 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), July 20-24, Montreal, Canada.

B. Saduanov, D. Tokmurzina, K. Kunanbayev, and B. Abibullaev, “Design and Optimization of a Real-Time Asynchronous BCI Control Strategy for Robotic Manipulator Assistance”, in 2020 8th International Winter Conference on Brain-Computer Interface. (BCI), 2020, GangWon, South Korea.

A. Tuleuov and B. Abibullaev, “Deep Learning Models for Subject-Independent ERP-based Brain-Computer Interfaces,” in 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), March 20-23, 2019, San Francisco, CA, USA.

B. Abibullaev, Y. Orazayev, and A. Zollanvari, “Novel Spatiospectral Features of ERPs Enhances Brain-Computer Interfaces,” in *Brain-Computer Interface (BCI), 2019 7th International Conference IEEE, 2019, GangWon, South Korea.

B. Saduanov, D. Tokmurzina, T. Alizadeh, and B. Abibullaev, “Brain-computer interface humanoid pre-trained for interaction with people,” in 2018 ACM/IEEE International Conference on Human-Robot Interaction.1em plus 0.5em minus 0.4emACM, March 5-8, 2018, pp. 229–230, Chicago, IL, USA.

A. Oleinikov, B. Abibullaev, A. Shintemirov, and M. Folgheraiter, “Feature extraction and real-time Recognition of hand motion intentions from EMGs via artificial neural networks,” in Brain-Computer Interface (BCI), 2018 6th International Conference on.1em plus 0.5em minus 0.4em IEEE, 2018, pp. 1-5, GangWon, South Korea.

G. Lee, S. H. Jin, S. T. Yang, J. An, and B. Abibullaev, “Cross-correlation between HbO and HbR as an effective feature of motion artifact in fNIRS signal,” 2018 6th International Conference on Brain-Computer Interface (BCI), pp. 1-3, 2018, IEEE, GangWon, South Korea.

B. Saduanov, T. Alizadeh, J. An, and B. Abibullaev, “Trained by demonstration of humanoid robot controlled via a BCI system for telepresence,” in Brain-Computer Interface (BCI), 2018 6th International Conference on. IEEE, 2018, pp. 1–4, January, GangWon, South Korea.

G. Lee, S. H. Jin, S. H. Lee, B. Abibullaev, and J. An, “fNIRS motion artifact correction for overground walking using entropy-based unbalanced optode decision and wavelet regression neural network,” in Multisensor Fusion and Integration for Intelligent Systems (MFI), 2017 IEEE International Conference on.IEEE, 2017, pp. 186–193, Daegu, South Korea.

A. Zhumadilova, D. Tokmurzina, A. Kuderbekov and and B. Abibullaev. Design and Evaluation of a P300 Visual Brain-Computer Interface Speller in Cyrillic Characters. In the 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), IEEE, 2017, August 28 - September 1, Lisbon, Portugal.

B. Abibullaev. Learning Suite of Kernel Feature Spaces Enhances SMR-Based EEG-BCI Classification. In the 5th International Winter Conference on Brain-Computer Interface, IEEE, 2017, January 9-11, GangWon, South Korea.

D. Nurseitov, A. Serekov, A. Shintemirov and B. Abibullaev. Design and Evaluation of a P300-ERP-based BCI System for Real-Time Control of a Mobile Robot. In the 5th International Winter Conference on Brain-Computer Interface, IEEE, 2017, January 9-11, Gangwon, South Korea.

B. Abibullaev and J An. On Robust Classification of Hemodynamic Signals for BCIs via Multiple Kernel ν-SVMs. Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference, 2016, Oct10-15, Daejeon, South Korea.

J.G. Cruz-Garza, Z.R. Hernandez, M. Megjhani, B. Abibullaev, T. Tse, E. Caducoy, and JL Contreras-Vidal. Neural development of social cognition in the first two years of life - Early findings. In Society for Neuroscience 2015 Oct 17-21; Chicago, USA.

Z.R. Hernandez, A.J. Arenas-Castellanos, J.G. Cruz-Garza, M. Megjhani, B. Abibullaev, Sri. R.P. Maddi, T. Tse, C. Armstrong, W. Long, J.L. Contreras-Vidal, Decoding Intent From Non-invasive EEG in Freely Behaving Infants, In Ninth Biennial Meeting of the Cognitive Development Society 2015 Oct 9-10; Ohio, USA.

A.J. Arenas-Castellanos, Z.R. Hernandez, J.G. Cruz-Garza, M. Megjhani, B. Abibullaev, Sri. R.P. Maddi, T. Tse, C. Armstrong, W. Long, J.L. Contreras-Vidal, A developmental Analysis of Behaviors Related to the Mirror Neuron System in 6-24 Months Infants, In Ninth Biennial Meeting of the Cognitive Development Society 2015 Oct 9-10; Ohio, USA.

Z.R. Hernandez, J.G. Cruz-Garza, T. Tse, E. Caducoy, B. Abibullaev, J.L. Contreras-Vidal. Supervised Classification of Intended Behaviors Using Electroencephalography (EEG) from Freely-Behaving Infants: Early Findings. In 12th Annual GCC Conference on Theoretical and Computational Neuroscience, Rice University, Houston, TX, United States, February 6-7, 2015.

N. A. Bhagat, A Venkatakrishnan, B. Abibullaev, E. J. Artz, A.A. Blank, J. A. French, N. Yozbatiran, and R. G. Grossman, M. K. O’Malley, J. L. Contreras-Vidal, G. E. Francisco, Control of a Therapeutic Exoskeleton to Facilitate Personalized Robotic Rehabilitation of the Upper Limb. , Westin Arlington, Nov. 19-20, 2014, United States.

C.H.Park, B. Abibullaev, E.Y. Joo, S.C. Hong, and S.B. Hong. The evaluation of accuracy and clinical usefulness of 3D EEG source localization analysis. In the 19th Korean Epilepsy Congress, Seoul, The Republic of Korea, June 12-14, 2014.

S.H. Lee, J. An, G. Jang, S.H. Jin, B. Abibullaev, and J.I. Moon. Neural activity during observation, imagery, and execution of eating: An fNIRS pilot study. In the 19th Annual Meeting of the Organization for Human Brain Mapping, Seattle, WA, United States, June 16-20, 2013.

J. An, S.H. Jin, S.H. Lee, G. Jang, B. Abibullaev, J. Ahn, H. Lee, and J.I. Moon. Cortical activation pattern for grasping during observation, imagery, execution, FES, and observation-FES integrated BCI: An fNIRS pilot study. In the 35th Annual Int. Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan, July 3-7, 2013.

J. An, S.H. Lee, S.H. Jin, B. Abibullaev, G. Jang, J. Ahn, H. Lee, and J.I. Moon. The beginning of neurohaptics: Controlling cognitive interaction via brain haptic interface. In the 2013 IEEE International Winter Workshop on Brain-Computer Interface, Gangwon Province, Korea, Feb. 18-20, 2013.

B. Abibullaev, J. An, J.I. Moon, S.H. Lee, and S.H. Jin. A study on the BCI-Robot assisted stroke rehabilitation framework using brain hemodynamic signals in the 9th Int Conference on Ubiquitous Robots and Ambient Intelligence, IEEE proceedings, Daejeon, Korea, November 26-29,2012.

B. Abibullaev, J. An, S.H.Lee, S.H. Jin, J.I Moon, H.J. Lee. Decoding Hemodynamic Brain Responses for Brain-Computer Interfaces via Ensemble Support Vector Learning. In the Human-Computer Interaction Conference, Gangwon-Do, Korea, January 11-13,2012.

B. Abibullaev, W.S. Kang, S.H. Lee, J. An, and H.D. Seo. Near-infrared spectroscopy in the Analysis of functional brain activity during cognitive tasks. In 2010 IEEE Sensors Conference, Hawaii, The United States, November 1-4, 2010.

B. Abibullaev, W.S. Kang, S.H. Lee, and J. An. Recognition of brain hemodynamic mental response for brain-computer interface. In International Conference on Control Automation and Systems, IEEE proceedings, Gyeonggi-do, Korea, October 27-30, 2010.

S.H. Lee, B. Abibullaev, W.S. Kang, and J. An. Analysis of attention deficit hyperactivity disorder in EEG using wavelet transform and self-organizing maps. In International Conference on Control Automation and Systems, IEEE proceedings, Gyeonggi-do, Korea, October 27-30, 2010.

W.S. Kang, B. Abibullaev, S.H. Lee, and J. An. Path planning algorithm using the values clustered by K-means. In the 15th Int. Symposium on Artificial Life and Robotics, Japan, February 4-6, 2010.

B. Abibullaev, H.D. Seo, W.S. Kang, and J. An. A wavelet-based method for detecting and localizing epileptic neural spikes in EEG signals. In the 2nd Int. Conf. on Interaction Sciences: Information Technology, Culture, and Human. ACM, Seoul, Korea, Nov. 24- 26, 2009.

B. Abibullaev and H.D. Seo. Epileptic seizure detection using continuous time wavelet-based neural networks. In the 6th International Conference on Information Technology: New Generations, IEEE Computer Society, Las Vegas, Nevada, United States, April 27-29, 2009.

W.S. Kang, B. Abibullaev, S.H. Lee, and J. An. A study on brain activation during playing a computer game using fNIRS. In the 32nd conference of Korean Info. Proc. Soc., Seoul Korea, November 22-24,2009.

B. Abibullaev, H.D. Seo, and M.S. Kim. Classification system of EEG during cognitive mental tasks. In Int. Conference on Engineering and ICT, Melaka, Malaysia, November 27-29, 2007.

H.D. Seo and B. Abibullaev. Analysis of EEG signals by the continuous wavelet transforms. In the 5th Int. Joint Conference on Global Academic Networking, Vladivostok, Russia, June 7-9, 2007. 

J. An, S.H. Jin, S.H. Lee, J.I. Moon, B. Abibullaev, J.H. Ahn and G.H. Jang. Rehabilitation Training System and Method. : 9,081,890, Washington, DC: United States. Patent and Trademark Office, 2015.

J. An, S.H. Jin, S.H. Lee, J.I. Moon, B. Abibullaev, J.H. Ahn and G.H. Jang. Self-directed Rehabilitation Training Method Combining Brain Signals and Functional Electrostimulation. : 17077057, Application number: 14049302, 09-OCT-2013, United States.

J. An, S.H. Jin, S.H. Lee, B. Abibullaev, J.I. Moon , J.H. Ahn and G.H. Jang. Combining Brain Signals and Functional Electrostimulation Self-Directed Rehabilitation Method, Patent Registration Number: 101501524000, 05.03.2015. South Korea. 

 

© Copyright 2024 - All Rights Reserved

‌

AI Website Generator