Ripul Ghosh

About

Ripul Ghosh is working as Principal Scientist at CSIR-Central Scientific Instruments Organisation, Chandigarh, a national laboratory of India with a vision to meet the unmet need for the design and development of scientific and strategic instruments. He joined CSIR-CSIO in the year 2011 after completing a Master's in Advanced Instrumentation from the Academy of Scientific and Innovative Research (AcSIR) with the "CSIR Quick Hire Scientist Trainee” fellowship. He completed his B.Tech in Instrumentation and Control Engineering from Haldia Institute of Technology, West Bengal in the year 2009. Subsequently working with different R&D projects and gaining experience, he also completed his PhD from AcSIR in 'Time-Frequency Signal Processing and Machine Learning' in 2020. He has been actively working in the area of seismic and acoustic sensing applications, earthquake early warning systems, thermal imaging, tech for wildlife conservation, and digital displays for aerospace sectors. He is an active member of professional scientific societies such as IEEE, SPIE, and IUPRAI. He is a recipient of the National Research Development Corporation (NRDC) Meritorious Invention Award 2017 and Skoch-order of Merit Award 2018 for D&D of Seismic Detection System for Target Recognition, Transformation Innovation Gold Medal Award for the design and development of Earthquake Warning System. He is a recipient of the SERB ITS Grant 2016 and SERB International Research Experience (SIRE) fellowship 2023 and is currently working at Syracuse University, New York, United States. Dr. Ghosh is an active reviewer of IEEE Transactions on Instrumentation and Measurement, Electronics Letters, MDPI journals, Ecological Informatics, Engineering Applications of AI etc.

Employment

• Syracuse University SIRE Fellow Sponsored Associate
  2023 - 2024
• CSIR Central Scientific Instruments Organisation Principal Scientist

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (21)

• Masked-Aware Directional Attention Network for DOA Estimation Under Sensor Failure Conditions
  IEEE Sensors Letters 2026 DOI: 10.1109/LSENS.2025.3646924
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• Low resource multi-head self-attention based transformer for airborne acoustic classification system
  Journal on Audio, Speech, and Music Processing 2026 DOI: 10.1186/s13636-026-00467-0
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• A Hybrid CNN–BiLSTM Approach for Wildlife Detection Nearby Railway Track in a Forest
  IEEE Sensors Journal 2025 DOI: 10.1109/JSEN.2025.3622306
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• Adaptive Noise Suppression for Low-Resource Airborne Acoustic Source Monitoring
  2025 DOI: 10.36227/techrxiv.176288035.57614541/v1
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• Numerical analysis of dual spherical buffer resonant cell for photoacoustic spectroscopy based trace gas sensing
  Physica Scripta 2025 DOI: 10.1088/1402-4896/adde94
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• A Hybrid CNN-BiLSTM Model for Seismic Signal Based Wildlife Detection Nearby Railway Tracks
  2025 DOI: 10.36227/techrxiv.174285634.46750467/v1
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• Seismic Instrumentation and Its Application
  Handbook of Vibroacoustics, Noise and Harshness 2024 DOI: 10.1007/978-981-99-4638-9_45-1
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• Preliminary Response of Transient Electromagnetic Survey System for Buried Metal Detection from Aerial Platform
  2024 DOI: 10.1007/978-981-99-6855-8_42
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• A Parallel Signal Detector Approach for Detection of Human Activities Using Multiple Seismic Sensors
  2024 DOI: 10.1007/978-981-99-6855-8_43
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• Investigations on One Dimensional and Two Dimensional Enhanced Spectro-Temporal Feature Based Deep Learning Framework for Airborne Acoustic Source Classification
  2024 IEEE 9th International Conference for Convergence in Technology (I2CT) 2024 DOI: 10.1109/i2ct61223.2024.10544174
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