Dr. Abhay Upadhyay

Back to Faculty Dr. Abhay Upadhyay Department of ECE Guest Faculty [email protected] 918319420696 Indian Institute of Information Technology, Kota SPL-269, RIICO Industrial Area, Kuber Extension, Ranpur, Kota – 325003, (Rajasthan, India) LinkedIn Google Scholar Qualifications Ph.D. (IIT Indore) M.Tech. (MANIT Bhopal) B.Tech. (UPTU Lucknow) Teaching & Research Experience 7 Years Research Interests Machine Learning for Signal Processing Speech Signal Processing Biomedical Signal Processing Non-stationary Signal Processing Brain-Computer Interface Artificial Intelligence (AI) and Internet of Things (IoT) in Healthcare Roles & Responsibilities Member of Health and Wellness committee at IIIT Kota Funded Projects A multi-class computer-aided system for diagnosis of cardiovascular disease using non-invasively measured cardiac signals. Role: Principle Investigator Agency: National Project Implementation Unit (A Unit of Ministry of Human Resource Development India) Scheme: Collaborative Research Scheme. Electroencephalogram based sleep stages detection using advance wavelet techniques. Role: Co-Principle Investigator Agency: National Project Implementation Unit (A Unit of Ministry of Human Resource Development India) Other Notable Information Published two book chapters. Clear GATE 2007, GATE 2012 and GATE 2013. Best research paper award at IIT Indore in 2016. Publications Journals R. Dubey, R. R. Sharma, A. Upadhyay, and R. B. Pachori, “Automated variational nonlinear chirp mode decomposition for bearing fault diagnosis,” IEEE Transactions on Industrial Informatics, vol. 19, no. 11,pp. 10 873–10 882, 2023 R. Dubey, M. Kumar, A. Upadhyay, and R. B. Pachori, “Automated diagnosis of muscle diseases from EMG signals using empirical mode decomposition based method,” Biomedical Signal Processing and Control, vol. 71, p. 103 098, 2022 S. Khare, A. Nishad, A. Upadhyay, and V. Bajaj, “Classification of emotions from EEG signals using time-order representation based on the S-transform and convolutional neural network,” Electronics Letters, vol. 56, no. 25, pp. 1359–1361, 2020 A. Nishad, A. Upadhyay, G. Ravi Shankar Reddy, and V. Bajaj, “Classification of epileptic EEG signals using sparse spectrum based empirical wavelet transform,” Electronics Letters, vol. 56, no. 25, pp. 1370–1372, 2020 A. Upadhyay, M. Sharma, R. B. Pachori, and R. Sharma, “A nonparametric approach for multicomponent AM–FM signal analysis,” Circuits, Systems, and Signal Processing, vol. 39, no. 12, pp. 6316–6357, 2020 A. Nishad, A. Upadhyay, R. B. Pachori, and U. R. Acharya, “Automated classification of hand movements using tunable-Q wavelet transform based filter-bank with surface electromyogram signals,” Future Generation Computer Systems, vol. 93, pp. 96–110, 2019 A. Sharma, S. Patidar, A. Upadhyay, and U. R. Acharya, “Accurate tunable-Q wavelet transform based method for QRS complex detection,” Computers Electrical Engineering, vol. 75, pp. 101–111, 2019 A. Bhattacharyya, R. B. Pachori, A. Upadhyay, and U. R. Acharya, “Tunable-Q wavelet transform based multiscale entropy measure for automated classification of epileptic EEG signals,” Applied Sciences, vol. 7, no. 4, p. 385, 2017 S. Patidar, R. B. Pachori, A. Upadhyay, and U. R. Acharya, “An integrated alcoholic index using tunable-Q wavelet transform based features extracted from EEG signals for diagnosis of alcoholism,” Applied Soft Computing, vol. 50, pp. 71–78, 2017 R. Sharma, R. B. Pachori, and A. Upadhyay, “Automatic sleep stages classification based on iterative filtering of electroencephalogram signals,” Neural Computing and Applications, vol. 28, pp. 2959–2978, 2017 A. Upadhyay and R. Pachori, “Speech enhancement based on mEMD-VMD method,” Electronics Letters, vol. 53, no. 7, pp. 502–504, 2017 A. Upadhyay, M. Sharma, and R. B. Pachori, “Determination of instantaneous fundamental frequency of speech signals using variational mode decomposition,” Computers & Electrical Engineering, vol. 62, pp. 630–647, 2017 A. Upadhyay and R. B. Pachori, “Instantaneous voiced/non-voiced detection in speech signals based on variational mode decomposition,” Journal of the Franklin Institute, vol. 352, no. 7, pp. 2679–2707, 2015. Conferences A. Mathur, N. Choudhary, A. Upadhyay, and R. B. Pachori, “Detection of glottal closure instants from voiced speech signals using the Fourier-bessel series expansion,” in 2015 International Conference on Communications and Signal Processing (ICCSP), IEEE, 2015, pp. 0474–0478 A. Upadhyay and R. B. Pachori, “A new method for determination of instantaneous pitch frequency from speech signals,” in 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE), IEEE, 2015, pp. 325–330.

  • Dr. Abhay Upadhyay
  • Qualifications
  • Teaching & Research Experience
  • Research Interests
  • Roles & Responsibilities
  • Funded Projects
  • A multi-class computer-aided system for diagnosis of cardiovascular disease using non-invasively measured cardiac signals.
  • Electroencephalogram based sleep stages detection using advance wavelet techniques.
  • Other Notable Information
  • Publications
  • Journals
  • Conferences

Back to Faculty Dr. Abhay Upadhyay Department of ECE Guest Faculty [email protected] 918319420696 Indian Institute of Information Technology, Kota SPL-269, RIICO Industrial Area, Kuber Extension, Ranpur, Kota – 325003, (Rajasthan, India) LinkedIn Google Scholar Qualifications Ph.D. (IIT Indore) M.Tech. (MANIT Bhopal) B.Tech. (UPTU Lucknow) Teaching & Research Experience 7 Years Research Interests Machine Learning for Signal Processing Speech Signal Processing Biomedical Signal Processing Non-stationary Signal Processing Brain-Computer Interface Artificial Intelligence (AI) and Internet of Things (IoT) in Healthcare Roles & Responsibilities Member of Health and Wellness committee at IIIT Kota Funded Projects A multi-class computer-aided system for diagnosis of cardiovascular disease using non-invasively measured cardiac signals. Role: Principle Investigator Agency: National Project Implementation Unit (A Unit of Ministry of Human Resource Development India) Scheme: Collaborative Research Scheme. Electroencephalogram based sleep stages detection using advance wavelet techniques. Role: Co-Principle Investigator Agency: National Project Implementation Unit (A Unit of Ministry of Human Resource Development India) Other Notable Information Published two book chapters. Clear GATE 2007, GATE 2012 and GATE 2013. Best research paper award at IIT Indore in 2016. Publications Journals R. Dubey, R. R. Sharma, A. Upadhyay, and R. B. Pachori, “Automated variational nonlinear chirp mode decomposition for bearing fault diagnosis,” IEEE Transactions on Industrial Informatics, vol. 19, no. 11,pp. 10 873–10 882, 2023 R. Dubey, M. Kumar, A. Upadhyay, and R. B. Pachori, “Automated diagnosis of muscle diseases from EMG signals using empirical mode decomposition based method,” Biomedical Signal Processing and Control, vol. 71, p. 103 098, 2022 S. Khare, A. Nishad, A. Upadhyay, and V. Bajaj, “Classification of emotions from EEG signals using time-order representation based on the S-transform and convolutional neural network,” Electronics Letters, vol. 56, no. 25, pp. 1359–1361, 2020 A. Nishad, A. Upadhyay, G. Ravi Shankar Reddy, and V. Bajaj, “Classification of epileptic EEG signals using sparse spectrum based empirical wavelet transform,” Electronics Letters, vol. 56, no. 25, pp. 1370–1372, 2020 A. Upadhyay, M. Sharma, R. B. Pachori, and R. Sharma, “A nonparametric approach for multicomponent AM–FM signal analysis,” Circuits, Systems, and Signal Processing, vol. 39, no. 12, pp. 6316–6357, 2020 A. Nishad, A. Upadhyay, R. B. Pachori, and U. R. Acharya, “Automated classification of hand movements using tunable-Q wavelet transform based filter-bank with surface electromyogram signals,” Future Generation Computer Systems, vol. 93, pp. 96–110, 2019 A. Sharma, S. Patidar, A. Upadhyay, and U. R. Acharya, “Accurate tunable-Q wavelet transform based method for QRS complex detection,” Computers Electrical Engineering, vol. 75, pp. 101–111, 2019 A. Bhattacharyya, R. B. Pachori, A. Upadhyay, and U. R. Acharya, “Tunable-Q wavelet transform based multiscale entropy measure for automated classification of epileptic EEG signals,” Applied Sciences, vol. 7, no. 4, p. 385, 2017 S. Patidar, R. B. Pachori, A. Upadhyay, and U. R. Acharya, “An integrated alcoholic index using tunable-Q wavelet transform based features extracted from EEG signals for diagnosis of alcoholism,” Applied Soft Computing, vol. 50, pp. 71–78, 2017 R. Sharma, R. B. Pachori, and A. Upadhyay, “Automatic sleep stages classification based on iterative filtering of electroencephalogram signals,” Neural Computing and Applications, vol. 28, pp. 2959–2978, 2017 A. Upadhyay and R. Pachori, “Speech enhancement based on mEMD-VMD method,” Electronics Letters, vol. 53, no. 7, pp. 502–504, 2017 A. Upadhyay, M. Sharma, and R. B. Pachori, “Determination of instantaneous fundamental frequency of speech signals using variational mode decomposition,” Computers & Electrical Engineering, vol. 62, pp. 630–647, 2017 A. Upadhyay and R. B. Pachori, “Instantaneous voiced/non-voiced detection in speech signals based on variational mode decomposition,” Journal of the Franklin Institute, vol. 352, no. 7, pp. 2679–2707, 2015. Conferences A. Mathur, N. Choudhary, A. Upadhyay, and R. B. Pachori, “Detection of glottal closure instants from voiced speech signals using the Fourier-bessel series expansion,” in 2015 International Conference on Communications and Signal Processing (ICCSP), IEEE, 2015, pp. 0474–0478 A. Upadhyay and R. B. Pachori, “A new method for determination of instantaneous pitch frequency from speech signals,” in 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE), IEEE, 2015, pp. 325–330.