Abhinav Kumar

About

Dr. Abhinav Kumar is working as an Assistant Professor in the Department of Computer Science and Engineering at Motilal Nehru National Institute of Technology Allahabad (MNNIT Allahabad), India. He earned his Ph.D. in Computer Science and Engineering from the National Institute of Technology Patna, India. Before joining MNNIT Allahabad, he held academic positions as an Assistant Professor at the Indian Institute of Information Technology Surat (IIIT Surat), Gujarat, and Siksha ‘O’ Anusandhan, Bhubaneswar, Odisha, India. His research interests span machine learning, deep learning, crisis informatics, natural language processing, and social network analysis. He has published extensively in leading journals, including IEEE Transactions on Computational Social Systems, IEEE Transactions on Consumer Electronics, Applied Soft Computing, Annals of Operations Research, Sustainable Cities and Society, Information Systems Frontiers, and the International Journal of Disaster Risk Reduction. Dr. Kumar has also contributed to the academic community as a Guest Editor for prestigious journals such as IEEE Transactions on Industrial Informatics, IEEE Transactions on Consumer Electronics, and Neural Computing and Applications.

Employment

• Motilal Nehru National Institute of Technology Allahabad Assistant Professor
  2023 - Present
• Indian Institute of Information Technology Surat Assistant Professor
  2022 - 2023
• Siksha O Anusandhan University Institute of Technical Education and Research Assistant Professor
  2021 - 2022

Education

• National Institute of Technology Patna Ph.D
  2016 - 2022
• Central University of Bihar M. Tech.
  2013 - 2015
• Gaya College of Engineering, Gaya B. Tech.
  2009 - 2013

Projects & Funding

Projects & funding information is unavailable.

Publications (41)

• A Blockchain-Assisted Holographic Counterparts for Secure Consumer Electronics in Healthcare 4.0
  IEEE Transactions on Consumer Electronics 2026 DOI: 10.1109/TCE.2026.3679034
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• SP-DTH5: Consumer-Centric Secure Digital Twins for Healthcare 5.0
  IEEE Transactions on Consumer Electronics 2026 DOI: 10.1109/TCE.2026.3678731
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• Privacy-Preserving Federated Learning With Blockchain Auditing for Consumer Electronics Applications
  IEEE Transactions on Consumer Electronics 2026 DOI: 10.1109/TCE.2026.3657426
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• Explainable BERT-LSTM Stacking for Sentiment Analysis of COVID-19 Vaccination
  IEEE Transactions on Computational Social Systems 2025 DOI: 10.1109/TCSS.2023.3329664
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• Ensuring safety in digital spaces: Detecting code-mixed hate speech in social media posts
  Data & Knowledge Engineering 2025 DOI: 10.1016/j.datak.2025.102409
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• Forecasting Bitcoin Prices Using Deep Learning for Consumer-Centric Industrial Applications
  IEEE Transactions on Consumer Electronics 2024 DOI: 10.1109/TCE.2023.3321653
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• Advanced Learning for Phishing URLs Detection to Secure Consumer-Centric Applications
  IEEE Transactions on Consumer Electronics 2024 DOI: 10.1109/TCE.2024.3404459
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• Deep Neural Networks for Location Reference Identification From Bilingual Disaster-Related Tweets
  IEEE Transactions on Computational Social Systems 2024 DOI: 10.1109/TCSS.2022.3213702
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• An evolutionary supply chain management service model based on deep learning features for automated glaucoma detection using fundus images
  Engineering Applications of Artificial Intelligence 2024 DOI: 10.1016/j.engappai.2023.107449
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• A Blockchain-Based Framework to Resolve the Oligopoly Issue in Cloud Computing
  IEEE Transactions on Cloud Computing 2024 DOI: 10.1109/TCC.2024.3390933
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