Shakti Prasad Sethi, Ph.D.

About

Dr. Shakti Prasad Sethi is an Assistant Professor at the School of Computer Engineering, Manipal Institute of Technology, Manipal. He completed his Ph.D. in signal processing, instrumentation, and machine learning from the Academy of Scientific and Innovative Research (AcSIR), India. His research interests include quantum computing, QML, machine learning, deep learning, signal processing, computer vision instrumentation, data-driven modeling, and industrial process fault diagnostics.

He has held academic and research positions at the School of Artificial Intelligence, Amrita Vishwa Vidyapeetham; the Department of Physics at the University of Liverpool, U.K.; and collaborated with international research teams, including work associated with CERN, Switzerland. His work spans industrial plasma monitoring, beam diagnostics of LHC, statistical machine learning, and intelligent sensing systems.

Dr. Sethi has published research articles in reputed international journals, including IEEE and AIP publications, and presented papers in international conferences in the U.K. and China and actively contributes as a reviewer and academic speaker. He is also a recipient of CSIR fellowships and has qualified GATE and CSIR-NET-JRF examinations.

Employment

• Manipal Academy of Higher Education
  2026 - Present
• Amrita Vishwa Vidyapeetham Assistant Professor
  2025 - 2026
• University of Liverpool Hononary Research Fellow
  2025 - 2025
• University of Liverpool Post-Doctoral Research Associate
  2024 - 2025

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (6)

• CrowdSentry: An Intelligent Cloud-Integrated Framework for Crowd Density Monitoring and Adaptive Safety Alerting via Multi-Object Tracking
  2026 DOI: 10.2139/ssrn.6836274
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• Techniques for Monitoring and Fault Diagnostics of Industrial Plasma Processes and Applications
  IEEE Transactions on Plasma Science 2026 DOI: 10.1109/TPS.2026.3662493
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• Cell Counting Based on Image Processing for the Detection of Cancer Clumps
  2023 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) 2023 DOI: 10.1109/icccis60361.2023.10425279
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• Cathode Position Detection in a Transferred Arc Plasma Using Artificial Neural Network
  IEEE Transactions on Plasma Science 2023 DOI: 10.1109/TPS.2022.3229199
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• Instability and fault analysis of arc plasma using advanced signal processing methods
  Review of Scientific Instruments 2023 DOI: 10.1063/5.0161187
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• Monitoring of Arc Plasma Process Parameter Using CNN-Based Deep Learning Algorithm to Accommodate Sensor Failure
  IEEE Transactions on Plasma Science 2023 DOI: 10.1109/TPS.2023.3274788
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