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Dr. Gopal Chandra Jana

Dr. Gopal Chandra Jana

Assistant Professor , Computer Science & Engineering (CSE)

gopal.jana@sharda.ac.in

About

Dr. Gopal Chandra Jana is an Assistant Professor in the Department of Computer Science & Engineering (CSE) at the Sharda School of Computing Science and Engineering, Sharda University, Greater Noida. He completed his full-time PhD under the supervision of Prof. Anupam Agrawal in the Department of Information Technology, IIIT Allahabad (Prayagraj) — one of India's premier Centrally Funded Technical Institutions (CFTIs). He holds a Bachelor of Engineering (B.E.) in Information Technology from The University of Burdwan (2015) and a Master of Technology (M.Tech.) in Computer Science and Engineering from the School of Computer Engineering, KIIT University (2017).

His teaching expertise spans Artificial Intelligence, Machine Learning, Deep Learning, Brain Computer Interface, and Data Structures & Algorithms, and he has extensive experience mentoring UG, PG, and PhD students in their academic and research endeavours.

His research interests lie at the intersection of neuroscience and computing, encompassing Brain-Computer Interface (BCI), EEG Signal Analysis, Biomedical Signal and Image Processing, Vision and Signal Processing, Machine Learning, Deep Learning, Explainable AI, Reinforcement Learning, AI in Healthcare, Portable Real-time Healthcare Systems, and Assistive Technology for Health and Wellness.

Dr. Jana has authored 15+ research publications and holds a registered Copyright for the EEG VMAC Toolbox, a software tool developed as part of his research contributions. He is a Member of IEEE (USA) and an Associate Member of the Institution of Engineers India (IEI), reflecting his active engagement with the global engineering community.

He serves as a reviewer for several prestigious internationally indexed journals, including IEEE Transactions and Elsevier's Biomedical Signal Processing and Control (BSPC).

Dr. Jana holds professional certifications in Signals and Image Processing (GAIN), Advanced Algorithmic Problem Solving (GeeksforGeeks), Deep Learning, and MATLAB, underscoring his commitment to continuous learning and technical excellence. He has also earned HackerRank Five-Star Badges in both Problem Solving and Python, demonstrating strong competitive programming and coding proficiency.

 

Experience
  • 3+ Years
Qualification
  • PhD (Full-Time, Dept. IT, IIIT Allahabad)
  • M.Tech CSE (KIIT)
  • B.E IT (The University of Burdwan, WB)
Award & Recognition

  • IEEE Senior Member
  • Associate Member, IEI India
  • HackerRank Five-Star Badges achiever in both Problem Solving and Python

Research

Patent (Published):

  • AI-ENABLED MULTIMODAL EEG–VIDEO FUSION SYSTEM FOR REAL-TIME AUTISM SPECTRUM DISORDER SCREENING AND ADAPTIVE COGNITIVE BEHAVIOURAL THERAPY TO IMPROVE MENTAL HEALTH (Application Number- 202611052308)
  • EEG VMAC Toolbox (Software Copyright)

Research Article:

  • Gopal Chandra Jana, Anshuman Sabath and Anupam Agrawal, “Capsule neural networks on spatio-temporal EEG frames for cross-subject emotion recognition” Biomedical Signal Processing and Control, Vol. 72, Issue. B, pp. 103361, 2022.
  • Gopal Chandra Jana et. al., “Capsule neural network based approach for subject specific and cross-subjects seizure detection from EEG signals” Multimedia Tools and Applications , Vol. 82, pp. 35221–35252, 2023.
  • Gopal Chandra Jana, Anupam Agrawal et. al., “DWT-EMD Feature Level Fusion Based Approach over Multi and Single Channel EEG Signals for Seizure Detection” Diagnostics, Vol. 12, Issue. 2, pp. 324, 2022.
  • Gopal Chandra Jana, Mogullapally Sai Praneeth and Anupam Agrawal, “A Multi-View SVM Approach for Seizure Detection from Single Channel EEG Signals” IETE Journal of Research, Vol. 69, Issue. 06, pp. 3120-3131, 2021.

Total publication: 15+

Certifications

  • Signals and Image Processing (GAIN)
  • Advanced Algorithmic Problem Solving (GeeksforGeeks)
  • Training Certification on “Artificial Intelligence, ML, & deep Learning Applications” by Edux Labs.
  • eLearning Content Creation by CDAC Mumbai.

Area of Interest

  • EEG Signal Analysis and Brain Computer Interface (BCI)
  • Biomedical Signal and Image Processing,
  • Human and Brain Computer Interface,
  • Vision and Signal Processing,
  • Machine Learning and Deep Learning,
  • Explainable Machine Learning,
  • Reinforcement Learning,
  • Artificial Intelligence (AI) in healthcare
  • Health Informatics