Bibekananda Panda

About

Dr. Bibekananda Panda has completed his PhD in the Department of Electronics and Communication Engineering (ECE) at the National Institute of Technology Rourkela, Odisha, India, with a research focus on deep learning and machine learning applications for wireless communication techniques. He received his B.Tech degree in ECE from the Institute of Technical Education & Research (ITER), Bhubaneswar, Odisha, India, and his M.Tech degree in ECE from the National Institute of Science and Technology (NIST), Berhampur, Odisha. Before pursuing his PhD, Dr. Panda gained teaching experience as a faculty member at Maharaja Polytechnic, Bhubaneswar, Odisha and Gandhi Institute for Education and Technology, Bhubaneswar, Odisha. A passion for research and innovation in wireless communication and deep learning drives his academic journey. He aspires to secure a suitable educational or industry position where he can leverage his knowledge and experience to contribute meaningfully to research, teaching, and technological advancements.

Employment

• International Institute of Information Technology Faculty
  2025 - Present
• Gandhi Institute for Education and Technology Faculty
  2018 - 2020
• Maharaja Polytechnic, Bhubaneswar Faculty
  2016 - 2018

Education

• National Institute of Science and Technology M. Tech
  2014 - 2016
• Siksha O Anusandhan University Institute of Technical Education and Research B. Tech
  2010 - 2014

Projects & Funding

Projects & funding information is unavailable.

Publications (16)

• A Deep Convolutional-GRU-SVM-based Hybrid Approach for Signal Detection of Uplink NOMA System
  Wireless Personal Communications 2024 DOI: 10.1007/s11277-024-11529-x
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• A Machine Learning Approach with Decision Tree-based Signal Detection for MIMO-NOMA Systems
  2024 3rd International Conference on Artificial Intelligence for Internet of Things, AIIoT 2024 2024 DOI: 10.1109/AIIoT58432.2024.10574572
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• A Survey of Non-orthogonal Multiple Access for Internet of Things and Future Wireless Networks
  Signals and Communication Technology 2024 DOI: 10.1007/978-3-031-47942-7_18
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• Deep learning-based sequential models for multi-user detection with M-PSK for downlink NOMA wireless communication systems
  Annales des Telecommunications/Annals of Telecommunications 2024 DOI: 10.1007/s12243-023-00990-7
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• Deep learning-based sequential models for multi-user detection with M-PSK for downlink NOMA wireless communication systems
  Annals of Telecommunications 2023
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• A deep convolutional-LSTM neural network for signal detection of downlink NOMA system
  AEU - International Journal of Electronics and Communications 2023
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• A deep convolutional-LSTM neural network for signal detection of downlink NOMA system
  AEU - International Journal of Electronics and Communications 2023 DOI: 10.1016/j.aeue.2023.154797
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• A DEEP LEARNING FRAMEWORK FOR PREDICTING SIGNALS IN OFDM-NOMA WITH VARIOUS ALGORITHMS
  International Conference on Signal Processing and Vision 2022
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• Signal Detection in NOMA Systems using DNN with Bidirectional LSTM
  2022 2nd Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology (ODICON) 2022
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• Signal Detection in NOMA Systems using DNN with Bidirectional LSTM
  2nd Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology, ODICON 2022 2022 DOI: 10.1109/ODICON54453.2022.10010277
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