Neuroscientist, Qneuro India Pvt. Ltd., Chennai, Tamil Nadu, India 

PhD (Electrical Engineering), Indian Institute of Technology (IIT) Indore, Indore, India

About me:

I have received my Bachelor of Engineering degree in Electrical and Electronics Engineering from Rajiv Gandhi Technological University, Bhopal, India, and Master of Engineering degree in Electrical Engineering from Shri Govindram Seksaria Institute of Technology and Science, Indore, India in 2010 and 2012, respectively. Afterwards, I have served as a Research Associate for a Council of Scientific and Industrial Research funded project in the Department of Electrical Engineering, Indian Institute of Technology Indore, Indore, India. I have completed my Doctor of Philosophy degree under the supervision of Dr. Ram Bilas Pachori who is a Professor in the Department of Electrical Engineering, Indian Institute of Technology Indore, Indore, India. Post PhD, I have also served as an Assistant Professor, Military College of Telecommunication Engineering (MCTE), Mhow, India. My research interests are Non-stationary Signal Processing, Biomedical Signal Processing, and Machine Learning. 

Research interests: 

Publications:

  • V. Gupta, T. Priya, A. K. Yadav, R. B. Pachori, and U. R. Acharya, "Automated detection of focal EEG signals using features extracted from flexible analytic wavelet transform," Pattern Recognition Letters, 94, pp. 180-188, 2017.

  • V. Gupta, A. Bhattacharyya, and R. B. Pachori, "Classification of seizure and non-seizure EEG signals based on EMD-TQWT method," 22nd IEEE International Conference on Digital Signal Processing (DSP), London, pp. 1-5, 2017.

  • A. Bhattacharyya, V. Gupta, and R. B. Pachori, “Automated identification of epileptic seizure EEG signals using empirical wavelet transform based Hilbert marginal spectrum,” 22nd IEEE International Conference on Digital Signal Processing (DSP), London, pp. 1-5, 2017.

  • V. Gupta and R. B. Pachori, “A new method for classification of focal and non-focal EEG signals,” In: M. Tanveer and R. Pachori (Eds.) Machine Intelligence and Signal Analysis. Advances in Intelligent Systems and Computing, 748, Springer, Singapore, 2019.

  • V. Gupta, A. Nishad, and R. B. Pachori, “Focal EEG signal detection based on constant-bandwidth TQWT filter-banks,” 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Madrid, Spain, pp. 2597-2604 , 2018.

  • V. Gupta, M. D. Chopda, and R. B. Pachori, “Cross-subject emotion recognition using flexible analytic wavelet transform from EEG signals,” IEEE Sensors Journal, 19 (6), pp. 2266-74, 2018.

  • R. Katiyar, V. Gupta, and R.B. Pachori, ”FBSE-EWT based approach for the determination of respiratory rate from PPG signals”, IEEE Sensors Letters, 3 (7), pp. 1-4 2019.

  • V. Gupta and R. B. Pachori, “Epileptic seizure identification using entropy of FBSE based EEG rhythms,” Biomedical Signal Processing and Control, 53, 101569, 2019.

  • V. Gupta, A. Bhattacharyya, and R. B. Pachori, “Automated identification of epileptic seizures from EEG signals using FBSE-EWT method,” In: G.R. Naik (Ed.) Biomedical Signal Processing-Advances in Theory, Algorithms and Applications, Springer, 2020.

  • R. B. Pachori and V. Gupta, “Biomedical engineering fundamentals,” In: F. Firouzi, K. Chakrabarty, and S. Nassif (Eds.) Intelligent Internet of Things, Springer, 2020.

  • V. Gupta and R. B. Pachori, “Classification of focal EEG signals using FBSE based flexible time-frequency coverage wavelet transform,” Biomedical Signal Processing and Control, 62, 102124, 2020.

  • V. Gupta and R. B. Pachori, "FBDM based time-frequency representation for sleep stages classification using EEG signals,” Biomedical Signal Processing and Control, 64, 102265, 2021.
  • V. Gupta and R. B. Pachori, "FB dictionary based SSBL-EM and its application for multi-class SSVEP classification using eight-channel EEG signals,” IEEE Transactions on Instrumentation & Measurement, 2022.
  • P. K. Chaudhary, V. Gupta, R. B. Pachori, "Fourier-Bessel representation for signal processing: A review," Digital Signal Processing, p.103938, 2023.