Ravindra Keskar

Employment

• Visvesvaraya National Institute of Technology Associate Professor
  2009 - Present

Education

• Visvesvaraya National Institute of Technology Ph.D.
  2009 - 2015
• Indian Institute of Technology Bombay M.Tech.
  1997 - 1999
• Visvesvaraya National Institute of Technology B.E.
  1993 - 1997

Projects & Funding

Projects & funding information is unavailable.

Publications (34)

• Simultaneous speech and background sound recognition in diverse acoustic environments with branched neural networks
  Computer Speech & Language 2026 DOI: 10.1016/j.csl.2025.101868
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• M-CBAF: A Multimodal Classroom Behaviour Analytics Framework for Learning Analytics Using Multimodal Feature Fusion and Behaviour-to-Engagement Mapping
  2026 DOI: 10.2139/ssrn.7265787
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• Prediction of seismic amplification factors in India using machine learning models
  Proceedings of the Institution of Civil Engineers - Geotechnical Engineering 2026 DOI: 10.1680/jgeen.25.00070
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• Artificial Neural Network Generated Responses of Laterally Loaded Concrete Piles on Various Soil Conditions
  Lecture Notes in Civil Engineering 2025 DOI: 10.1007/978-981-97-6067-1_52
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• Fine-scale mapping of heat-hazard risk and vulnerability using geo-spatial techniques: Insights from a tropical Indian city
  Geographica Pannonica 2025 DOI: 10.5937/gp29-56164
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• Seismic Risk Assessment of Nagpur City Using GIS and Machine Learning Algorithms
  Lecture Notes in Civil Engineering 2025 DOI: 10.1007/978-981-97-7043-4_16
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• Seismic Zone Clustering and Risk Prediction Using AI/ML and GIS Techniques
  Lecture Notes in Civil Engineering 2025 DOI: 10.1007/978-981-97-7043-4_53
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• Self-supervised random forests for robust voice activity detection with limited labeled data
  Applied Acoustics 2025 DOI: 10.1016/j.apacoust.2025.110636
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• WUDAPT based LCZ mapping of medium-sized Indian cities located on flat terrain: Its assessment and application
  Urban Climate 2025 DOI: 10.1016/j.uclim.2025.102626
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• Simultaneous Speech and Background Sound Recognition in Diverse Acoustic Environments with Branched Neural Networks
  Ssrn 2024 DOI: 10.2139/ssrn.5049919
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