Qualification

• 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 and Responsibilities

• Member of Health and Wellness committee at IIIT Kota

Funded Projects

1.  Title of Project: A multi-class computer-aided system for diagnosis of cardiovascular disease using non-invasively measured cardiac signals. Principle Investigator: Dr Abhay Upadhyay
   • Role: Sponsoring Agency: National Project Implementation Unit (A Unit of Ministry of Human Resource Development
   • Amount: India)
   • Funded By: Scheme: Collaborative Research Scheme.
   • Status:
   
   
2.  Title of Project: Electroencephalogram based sleep stages detection using advance wavelet techniques. Co-Principle Investigator: Dr Abhay Upadhyay
   • Role: Sponsoring Agency: National Project Implementation Unit (A Unit of Ministry of Human
   • Amount: Resource Development
   • Funded By: India)
   • Status: Scheme: Collaborative Research Scheme.
   
   

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

1. 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
2. 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
3. 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
4. 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
5. 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
6. 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
7. 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
8. 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
9. 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
10. 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
11. A. Upadhyay and R. Pachori, “Speech enhancement based on mEMD-VMD method,” Electronics Letters, vol. 53, no. 7, pp. 502–504, 2017
12. 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
13. 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

1. 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
2. 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.