Bakul Gohel

Bakul Gohel
PhD (Bio and Brain Engineering), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
079-68261672 # 2201, FB-2, DA-IICT, Gandhinagar, Gujarat, India – 382007 bakul_gohel[at]daiict[dot]ac[dot]in

Bakul Gohel is an assistant professor at Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT), Gandhinagar, since 2018. He completed his Ph.D. in the field of bio and brain engineering at Korea Advanced Institute of Technology and Science (KAIST), South Korea, in 2015. He received his master (M.Tech.) degree in the field of information technology (Spec. Bio-Informatics) from IIIT-Allahabad and his MBBS (Bachelor of Medicine and Bachelor of Surgery) degree from government medical college, Surat, India. Prior to joining DA-IICT, he was a researcher at Korea Research Institute of Science and Standards, South Korea, from 2015. His current research interest lies in the field of biomedical signal processing and analysis, brain-computer interaction/interface, cognitive computing and data analysis with the machine learning approach.

Bio and Brain Engineering, Information Technology, Medicine

  • An, K.-M., Lim, S., Lee, H. J., Kwon, H., Kim, M.-Y., Gohel, B., & Kim, K*. (2018). Magnetoencephalographic study of event-related fields and cortical oscillatory changes during cutaneous warmth processing. Human Brain Mapping, 39(5), 1972-1981.
  • Gohel, B.*, Lim, S., Kim, M.-Y., Kwon, H., & Kim, K*. (2018). Dynamic pattern decoding of source-reconstructed MEG or EEG data: Perspective of multivariate pattern analysis and signal leakage. Computers in Biology and Medicine, 93, 106-116.
  • Kang, M., Lee, Y.-B., Gohel, B., Yoo, K., Lee, P., Chung, J., & Jeong, Y. (2017). Momentary level of slow default mode network activity is associated with distinct propagation and connectivity patterns in the anesthetized mouse cortex. Journal of Neurophysiology, jn.00163.2017.
  • Gohel, B.*, Lim, S., Kim, M.-Y., Kwon, H., & Kim, K.* (2017). Approximate subject specific pseudo MRI from an available MRI dataset for MEG source imaging. Frontiers in Neuroinformatics, 11(August), 1-12.
  • Gohel, B.*, Lee, P., Kim, M.-Y., Kim, K., & Jeong, Y.* (2017). MEG Based Functional Connectivity: Application of ICA to Alleviate Signal Leakage. Innovation and Research in Biomedical Engineering (IRBM) , 38(3), 127-137.
  • Gohel, B.*, Lim, S., Kim, M.-Y., An, K., Kim, J.-E., Kwon, H., & Kim, K.* (2016). Evaluation of phase-amplitude coupling in resting state magnetoencephalographic signals: effect of surrogates and evaluation approach. Frontiers in Computational Neuroscience, 10 (November), 120.
  • Gohel, B., Lee, P., & Jeong, Y.* (2016). Modality-specific spectral dynamics in response to visual and tactile sequential shape information processing tasks: An MEG study using multivariate pattern classification analysis. Brain Research, 1644, 39-52.
  • Gohel, B., & Jeong, Y.* (2014). Sensory modality-specific spatio-temporal dynamics in response to counting tasks. Neuroscience Letters, 581.
  • Gohel, B., & Tiwary, U. S. (2010). Automated Risk Identification of Myocardial Infarction Using Relative Frequency Band Coefficient (RFBC) Features from ECG. The Open Biomedical Engineering Journal, 4(SPEC. ISSUE 2), 217-22.
  • Machine learning for Data Mining
  • Cognitive and Brain Science
  • Data Structure Lab
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