Ram Bilas Pachori

Ram Bilas Pachori
Born1979 (age 46–47)
Morena, Madhya Pradesh
Alma materIndian Institute of Technology Kanpur, Rajiv Gandhi Proudyogiki Vishwavidyalaya
HonoursFellow of IEEE, INAE, IET, IETE, IEI, AAIA
Scientific career
FieldsSignal processing, machine learning
InstitutionsIndian Institute of Technology Indore, International Institute of Information Technology, Hyderabad, University of Technology of Troyes
WebsiteWebpage

Ram Bilas Pachori (born 1979) is Institute Chair Professor and Professor (HAG) in the Department of Electrical Engineering at the Indian Institute of Technology Indore, India.[1][2][3] He is also Adjunct Professor in the Department of Electronics & Communication Engineering at Dr. B. R. Ambedkar National Institute of Technology Jalandhar, India.[3] His research focuses on signal processing, image processing, biomedical signal processing, non-stationary signal processing, speech processing, brain–computer interface, machine learning, and artificial intelligence and internet of things in healthcare.[2][4]

Recognitions

He was named a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2025,[5][6] "for contributions to application of signal decomposition methods to biomedical engineering".[6][7] He was also elected as a fellow of Indian National Academy of Engineering (INAE),[8] [9] Institution of Engineering and Technology (IET), Institution of Electronics and Telecommunication Engineers (IETE), Institution of Engineers (India) (IEI), and Asia-Pacific Artificial Intelligence Association (AAIA). [10] He is an elected member of National Academy of Artificial Intelligence (NAAI).[11] He was awarded IETE-Prof SVC Aiya Memorial Award in 2021[12][13] and IETE-Ram Lal Wadhwa Award in 2025.[14] He has been appointed as IEEE EMBS Distinguished Lecturer[15] and Academy Mentor for EURASIP Academy.[16] Pachori was awarded IET Journals Premium Award for Best Paper in IET Science, Measurement & Technology for consecutive two years (2019 and 2020).[17] He has also received the Best Paper Award in XXIV International Conference on Digital Signal Processing and Its Applications (DSPA 2022) held at Moscow, Russia.[18] He has been recognized as a Top Cited Scholar for three consecutive years, from 2023 to 2025, on the Scilit website.[19]

Scientific contributions

Pachori pioneered the development of the relation between frequency domain and order of the Fourier-Bessel series expansion (FBSE) coefficients. This led to applicability of the FBSE for analyzing nonstationary signals. He has also extended the FBSE based methods for the analysis and processing of biomedical images. He has also proposed multiresolution analysis tools based on FBSE for biomedical signals and images.[20] He has proposed non-stationary signal analysis method based on eigenvalue decomposition of Hankel matrix (EVDHM) for the first time in literature.[21]

Pachori has also developed EVDHM-based methods resulting the time-frequency representation to get better insight of the signal being analysed.[22] He has developed a sifting-based signal decomposition method with EVDHM, in a way similar to empirical mode decomposition method, for non-stationary signal processing.[23] He has developed a new way of obtaining the time-frequency representation of a signal based on time-varying eigenvalues.[24] Pachori has extended several univariate signal decomposition methods, including empirical wavelet transform to decompose multichannel signals.[25]

He studied the effect of mantra meditation like listening to Shri Rudram Mantra and chanting of Hare Krishna Maha Mantra on human brain activity.[26][27][28][29]

He authored the textbook Time-Frequency Analysis Techniques and their Applications (CRC Press, 2023).[30]

References

  1. ^ "Wigner-Specific Research". Wigner Initiative. Retrieved 27 January 2025.
  2. ^ a b "Neural Dynamics of Visual Cognition". Freie Universität Berlin. 18 July 2022. Retrieved 27 January 2025.
  3. ^ a b "Faculty - Electrical Engineering". Indian Institute of Technology Indore. Retrieved 10 April 2025.
  4. ^ "Ram Bilas Pachori". IEEE Engineering and Medicine Biology Society. Retrieved 10 April 2025.
  5. ^ "IEEE Fellow Class of 2025" (PDF). Institute of Electrical and Electronics Engineers. Retrieved 10 April 2025.
  6. ^ a b "IEEE Fellow Directory". Institute of Electrical and Electronics Engineers. Retrieved 10 April 2025.
  7. ^ "Chapter of the Year and New IEEE Fellows". IEEE Signal Processing Magazine. 42 (1): 12–14. 2025. doi:10.1109/MSP.2025.3531196.
  8. ^ "Nomination Information". Indian National Academy of Engineering. INAE. Retrieved 3 September 2025.
  9. ^ "Pachori Profile". Indian National Academy of Engineering. INAE. Retrieved 15 October 2025.
  10. ^ "AAIA Fellows". Asia-Pacific Artificial Intelligence Association. Retrieved 10 April 2025.
  11. ^ "NAAI". National Academy of Artificial Intelligence. Retrieved 10 July 2025.
  12. ^ "IETE Awards 2021: List of the Winners" (PDF). COEMPT. Retrieved 12 May 2025.
  13. ^ "IETE Awardees (Main Awards)- 2021" (PDF). IETE. Retrieved 25 July 2025.
  14. ^ "IETE AWARDS 2025 WINNERS" (PDF). IETE. Retrieved 26 August 2025.
  15. ^ "Current Distinguished Lecturers". IEEE Engineering and Medicine Biology Society. Retrieved 10 April 2025.
  16. ^ "Academy Mentors". EURASIP Academy. Retrieved 24 September 2025.
  17. ^ "IET Research Journal Prizes". IET Research Journals. Retrieved 18 May 2025.
  18. ^ "Work in Progress – DSPA Conference". Data Science and Predictive Analytics Conference. Retrieved 18 May 2025.
  19. ^ "Dr. Ram Bilas Pachori". Scilit. Retrieved 4 August 2025.
  20. ^ Chaudhary, Pradeep Kumar; Gupta, Vipin; Pachori, Ram Bilas (30 April 2023). "Fourier-Bessel representation for signal processing: A review". Digital Signal Processing. 135 103938. doi:10.1016/j.dsp.2023.103938.
  21. ^ Jain, Pooja; Pachori, Ram Bilas (October 2015). "An iterative approach for decomposition of multi-component non-stationary signals based on eigenvalue decomposition of the Hankel matrix". Journal of the Franklin Institute. 352 (10): 4017–4044. doi:10.1016/j.jfranklin.2015.05.038.
  22. ^ Sharma, Rishi Raj; Pachori, Ram Bilas (2018). "Time–frequency representation using IEVDHM–HT with application to classification of epileptic EEG signals". IET Science, Measurement & Technology. 12 (1): 34–42. doi:10.1049/iet-smt.2017.0058.
  23. ^ Singh, Vivek Kumar; Pachori, Ram Bilas (September 2025). "Iterative eigenvalue decomposition of Hankel matrix: An EMD like tool". Journal of the Franklin Institute. doi:10.1016/j.jfranklin.2025.108104. Retrieved 29 September 2025.
  24. ^ Singh, Vivek Kumar; Pachori, Ram Bilas (March 2026). "Eigenvalues-based time-frequency analysis". Journal of the Franklin Institute. doi:10.1016/j.jfranklin.2026.108561. Retrieved 7 March 2026.
  25. ^ Bhattacharyya, Abhijit; Pachori, Ram Bilas (September 2017). "A Multivariate Approach for Patient-Specific EEG Seizure Detection Using Empirical Wavelet Transform". IEEE Transactions on Biomedical Engineering. 64 (9). IEEE: 2003–2015. doi:10.1109/TBME.2017.2650259. PMID 28092514.
  26. ^ Mahato, Ashok; Bhalerao, Shailesh Vitthalrao; Pachori, Ram Bilas; Gadre, Vikram M.; Mahapatra, Dipika Das (20–22 February 2025). "Neurological Responses to Meditation with EEG Analysis Using Novel Empirical Fourier-Bessel Decomposition Approach". Proceedings of the 2025 10th International Conference on Signal Processing and Communication (ICSC). Noida, India: IEEE. doi:10.1109/ICSC64553.2025.10968250.
  27. ^ Das, Kritiprasanna; Verma, Pankaj; Pachori, Ram Bilas (30 March – 1 April 2022). "Assessment of Chanting Effects Using EEG Signals". Proceedings of the 2022 24th International Conference on Digital Signal Processing and its Applications (DSPA). Moscow, Russian Federation: IEEE. doi:10.1109/DSPA53304.2022.9790754.
  28. ^ Hare Krsna TV (20 November 2022). Chanting of the Hare Krishna Mahamantra brings peace of mind Research | HKTV NEWS #shorts (Video) (Online video). YouTube. Retrieved 24 May 2025.
  29. ^ TIMES NOW Navbharat (15 November 2022). Hare Krishna मंत्र के जाप से मिलता है गजब का फायदा, जानिए क्या? | Hindi News (Video) (Online video) (in Hindi). YouTube. Retrieved 24 May 2025.
  30. ^ Pachori, Ram Bilas (2023). Time-Frequency Analysis Techniques and their Applications. doi:10.1201/9781003367987. ISBN 978-1-003-36798-7. Retrieved 12 May 2025.
This article is issued from Wikipedia. The text is available under Creative Commons Attribution-Share Alike 4.0 unless otherwise noted. Additional terms may apply for the media files.