Dr Abhishek Hazra

About

Dr Abhishek Hazra (Member, IEEE) works as an Assistant Professor in the Department of Computer Science and Engineering at Indian Institute of Information Technology Sri City. He was a Research Fellow at the Communications and Networks Lab, Department of Electrical and Computer Engineering, National University of Singapore. He has defended his PhD at IIT(ISM) Dhanbad, India. He completed his master’s degree in Computer Science and Engineering from NIT Manipur, India, and his bachelor’s degree from NIT Agartala, India. He is an Editor/Guest Editor for FGCS, Physical Communication, Computer Communications, Contemporary Mathematics, IET Networks, SN Computer Science, Measurement: Sensors. He has authored and co-authored various national and international journal and conference articles. His research area of interest is in the field of IoT, Fog/Edge Computing, 6G, Machine Learning, and Industry 4.0/5.0.

Employment

• National University of Singapore Postdoctoral Research Fellow
  2022 - Present
• Iswar Chandra Vidyasagar College, Tripura Guest Lecturer
  2016 - 2017

Education

• Indian Institute of Technology (Indian School of Mines), Dhanbad Ph.D.
  2018 - Present
• National Institute of Technology Agartala B.TEch
  2010 - 2014

Projects & Funding

Projects & funding information is unavailable.

Publications (57)

• Unleashing the Potential of Industrial IoT and Industry 5.0
  IEEE Engineering Management Review 2026 DOI: 10.1109/EMR.2025.3644409
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• FedCSL: Cyclic Sequential Federated Learning for Mitigating Distributional Shifts in Consumer Healthcare IoT Systems
  IEEE Transactions on Consumer Electronics 2026 DOI: 10.1109/TCE.2025.3643908
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• MAPPO-Driven Task Quality Optimization With Wireless Energy Transfer in Multi-UAV MEC-Enabled IoT Networks
  IEEE Transactions on Sustainable Computing 2026 DOI: 10.1109/TSUSC.2026.3688744
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• An efficient master head selection for multi-EEG to multi-fog IoT network using 6G-driven FaaS
  Computer Communications 2026 DOI: 10.1016/j.comcom.2026.108429
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• Nanorobot-Based Intelligent Symptoms Analysis and Recommendation Framework in Edge Networks
  IEEE Journal of Biomedical and Health Informatics 2026 DOI: 10.1109/JBHI.2023.3278991
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• Joint Service Caching, Task Offloading, and Service Delivery in Mobile Edge Computing for Latency Critical UAV Networks
  IEEE Transactions on Computational Social Systems 2026 DOI: 10.1109/TCSS.2025.3643164
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• Millimeter Wave and Terahertz Communication: An Overview
  2026 DOI: 10.1007/978-3-032-19042-0_2
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• Quantum machine learning for industry 5.0: Fundamental, applications and research challenges
  Computer Science Review 2026 DOI: 10.1016/j.cosrev.2026.100976
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• Cognitive Computing and Machine Intelligence in Fog–Cloud Infrastructure for Industry 5.0
  IEEE Consumer Electronics Magazine 2025 DOI: 10.1109/MCE.2024.3405109
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• Machine Learning for Industry 5.0: A Survey
  IEEE Internet of Things Journal 2025 DOI: 10.1109/JIOT.2025.3604413
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