Subrata Pain

About

I have been a Ph.D. research scholar at the Department of Advanced Technology Development Center at the Indian Institute of Technology, Kharagpur, India since July 2019. The broad scope of my research is the application of machine learning to biomedical signal processing. I have been involved in teaching and practical research in the fields related to Pattern Recognition, Deep Learning, and Machine Learning. I have served as a teaching assistant for the courses Data Analytics, Programming and Data Structure, Machine Learning, Deep Learning, Probability & Statistical Learning, and Soft Computing during my tenure as Ph.D.

Currently, my research area is the analysis of human brain connectivity networks through the use of Electroencephalogram (EEG) recordings. Deep Learning, Graph Signal Processing, and Machine Learning techniques have been used for the analysis of human brain connectome networks.

Current status: I submitted my Ph.D. thesis on November 28, 2024.

Employment

• Alliance University Assistant Professor
  2025 - Present
• Tata Consultancy Services (India) System Engineer
  2013 - 2016

Education

• Indian Institute of Technology Kharagpur PhD
  2019 - 2024
• Jadavpur University ME
  2017 - 2019
• Jadavpur University BE
  2009 - 2013

Projects & Funding

Projects & funding information is unavailable.

Publications (8)

• MSSTNet: A multi-stream time-distributed spatio-temporal deep learning model to detect mind wandering from electroencephalogram signals
  Computers and Electrical Engineering 2025 DOI: 10.1016/j.compeleceng.2024.110005
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• Graph signal processing and graph learning approaches to Schizophrenia pattern identification in brain Electroencephalogram
  Biomedical Signal Processing and Control 2025 DOI: 10.1016/j.bspc.2024.106954
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• A Novel Framework for Cognitive Load Estimation from Electroencephalogram Signals Utilizing Sparse Representation of Brain Connectivity
  Communications in Computer and Information Science 2024 DOI: 10.1007/978-3-031-58181-6_42
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• Parametric Sparse Coding of Brain Connectivity Graph Signals for Schizophrenic EEG data
  2024 15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024 2024 DOI: 10.1109/ICCCNT61001.2024.10725230
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• A Novel Brain Connectivity-Powered Graph Signal Processing Approach for Automated Detection of Schizophrenia from Electroencephalogram Signals
  Lecture Notes in Computer Science 2023 DOI: 10.1007/978-3-031-45170-6_81
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• A Novel Graph Representation Learning Approach for Visual Modeling Using Neural Combinatorial Optimization
  Lecture Notes in Computer Science 2023 DOI: 10.1007/978-3-031-45170-6_24
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• An Efficient Motor Imagery Classification Framework using Sparse Brain Connectivity and Class-consistent Dictionary Learning from Electroencephalogram Signals
  ACM International Conference Proceeding Series 2023 DOI: 10.1145/3627631.3627641
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• Detection of alcoholism by combining EEG local activations with brain connectivity features and Graph Neural Network
  Biomedical Signal Processing and Control 2023 DOI: 10.1016/J.BSPC.2023.104851
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