Pawan Kumar Singh

About

Pawan Kumar Singh received his B. Tech degree in Information Technology from West Bengal University of Technology in 2010. He received his M. Tech in Computer Science and Engineering and Ph.D. (Engineering) degrees from Jadavpur University (J.U.) in 2013 and 2018 respectively. He also received the RUSA 2.0 fellowship for pursuing his post-doctoral research in J.U. in 2019. He is currently working as an Assistant Professor in the Department of Information Technology in J.U. He has published more than 150 research papers in peer-reviewed journals and international conferences. He also serves as Editorial Board Member, Reviewer, and Technical Program Committee Member for a number of IEEE and Springer journals and conferences. His areas of current research interest are Computer Vision, Pattern Recognition, Handwritten Document Analysis, Image & Video Processing, Feature Optimization, Machine Learning, Deep Learning and Artificial Intelligence. He is a senior member of the IEEE (U.S.A.), member of The Institution of Engineers (India) and Association for Computing Machinery (ACM) as well as a life member of the Indian Society for Technical Education (ISTE, New Delhi) and Computer Society of India (CSI).

Employment

• Jadavpur University - Second Campus Assistant Professor
  2019 - Present

Education

• Jadavpur University Ph D.
  2010 - Present

Projects & Funding

Projects & funding information is unavailable.

Publications (149)

• SZAtt-Net: A unified deep learning model with different attention mechanisms for schizophrenia classification from multimodal data
  Medicine in Novel Technology and Devices 2026 DOI: 10.1016/j.medntd.2026.100428
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• A Systematic Review of Brain Tumor Classification from MRI Scans Through the Last Decade
  2026 DOI: 10.1007/978-981-95-8938-8_2
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• Accurate and Early Detection of Dysarthria Using a Multimodal Deep Learning Methodology
  2026 DOI: 10.1007/978-981-95-8938-8_12
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• Advancing Lung Cancer Detection Using Optimized Fine Tuning Data-Efficient Image Transformers
  2026 DOI: 10.1007/978-981-95-8938-8_13
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• Deep Learning for Depression Detection Using EEG Signals: A RNN Based Approach
  2026 DOI: 10.1007/978-3-032-09153-6_1
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• DeepPark-Net: A Multimodal Deep Learning Framework for Parkinson’s Disease Detection
  2026 DOI: 10.1007/978-3-032-17181-8_26
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• Dynamic Weighted Deep Learning Ensemble Model for Accurate Cervical Cancer Classification from Pap Smear Images
  2026 DOI: 10.1007/978-3-032-09153-6_4
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• Leveraging a Hybrid CNN-BiLSTM Approach for Mental Stress Detection Using Wearable Physiological Sensors
  2026 DOI: 10.1007/978-3-032-13497-4_20
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• MER_Net: Hybrid Deep Learning Approach for Music Emotion Recognition from Audio Signals
  2026 DOI: 10.1007/978-981-96-6537-2_16
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• Performance Comparison of Different Attention-Based Transfer Learning Models for Automatic Leaf Disease Classification
  2026 DOI: 10.1007/978-981-95-3163-9_8
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