Ankit Gupta

Employment

• VSB - Technical University of Ostrava
  2024 - Present
• Universidade da Madeira Madeira Interactive Technologies Institute Research Assistant
  2019 - 2024
• Shoolini University Assistant Professor
  2016 - 2019
• Central Scientific Instruments Organisation CSIR Senior Project Fellow
  2016 - 2016
• VSB - Technical University of Ostrava

Education

• Universidade da Madeira Ph.D.
  2020 - 2024
• Maharishi Markandeshwar University M. Tech
  2013 - 2015
• Jaypee University of Information Technology Bachelor of Technology
  2008 - 2012

Projects & Funding

Projects & funding information is unavailable.

Publications (28)

• SiViS: Simulated multi-patient physiological clinical states for advanced vital sign radar monitoring research
  Scientific Data 2026 DOI: 10.1038/s41597-025-06449-9
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• MARS Lander: Georeferencing Landing and Pop Points of Untethered Ocean Monitoring Systems using Fundamental Physics
  Deep Sea Research Part I: Oceanographic Research Papers 2026 DOI: 10.1016/j.dsr.2026.104650
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• Radar Placement Effects on Multi-patient Heart and Respiration Monitoring, SiViS Dataset Validation
  2026 DOI: 10.1007/978-3-032-13312-0_11
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• RGB, a Surrogate of Infrared Facial Videos for Physiological Signs Estimations in Dark
  IEEE Transactions on Circuits and Systems for Video Technology 2026 DOI: 10.1109/TCSVT.2026.3651846
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• Multi-Objective Undercomplete Independent Component Analysis for Radar Signals based Heart Rate and Interbeat Interval Estimations
  2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2025 DOI: 10.1109/embc58623.2025.11253136
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• SiVis - Simulated multi-patient physiological clinical states
  2025 DOI: 10.7910/DVN/S9SNAK
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• System and Method for Estimating at least One Physiological Sign of a Subject in Dark Environments
  WIPO 2024
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• Facial video based physiological variables estimation in dark environments
  2024
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• Recent advancements in deep learning-based remote photoplethysmography methods
  2024 DOI: 10.1016/B978-0-44-313233-9.00012-6
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• Review of deep learning techniques for power generation prediction of industrial solar photovoltaic plants
  Solar Compass 2023 DOI: 10.1016/j.solcom.2023.100061
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