Rajeev Tiwari | Next generation communication networks | Editorial Member

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Prof. Dr. Rajeev Tiwari  | Next generation communication networks | Editorial Member

Prof. Dr. Rajeev Tiwari  | University of Petroluem and Energy Studies  | India

Prof. Dr. Rajeev Tiwari i has established a strong academic presence in artificial intelligence, deep learning, next-generation networks, fogedge computing, healthcare informatics, and smart agriculture, supported by 2327 citations, an h-index of 25, and an i10-index of 50. Their contributions span intelligent systems for agriculture, medical diagnostics, cybersecurity, vehicular analytics, and IoT-integrated environments. Notable works include hybrid CNN frameworks for leaf disease recognition, ensemble-based lung cancer diagnosis, Alzheimer’s disease detection models, and deep learning architectures for traffic density estimation and fake review identification. They have also advanced efficient routing in wireless sensor networks, content-centric networking optimization, and IoT-enabled automation in irrigation, parking, and toll management. Their research demonstrates a consistent focus on practical, high-impact solutions that bridge machine learning with real-world applications, contributing significantly to modern AI-driven systems across healthcare, agriculture, smart cities, and cloud-edge ecosystems.

Profile: Google Scholar

Featured Publications: 

Kaur, P., Harnal, S., Tiwari, R., Upadhyay, S., Bhatia, S., Mashat, A., & Alabdali, A. M. (2022). Recognition of leaf disease using hybrid convolutional neural network by applying feature reduction. Sensors, 22(2), 575.

Mittal, U., Chawla, P., & Tiwari, R. (2023). EnsembleNet: A hybrid approach for vehicle detection and estimation of traffic density based on faster R-CNN and YOLO models. Neural Computing and Applications, 35(6), 4755–4774.

Bathla, G., Singh, P., Singh, R. K., Cambria, E., & Tiwari, R. (2022). Intelligent fake reviews detection based on aspect extraction and analysis using deep learning. Neural Computing and Applications, 34(22), 20213–20229.

Verma, P., Tiwari, R., Hong, W. C., Upadhyay, S., & Yeh, Y. H. (2022). FETCH: A deep learning-based fog computing and IoT integrated environment for healthcare monitoring and diagnosis. IEEE Access, 10, 12548–12563.

Mishra, D., Khan, A., Tiwari, R., & Upadhay, S. (2018). Automated irrigation system—IoT based approach. 2018 3rd International Conference on Internet of Things: Smart Innovation, (pages not provided).

Subhas Mukhopadhyay | Internet of Things | Best Researcher Award

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Prof. Dr. Subhas Mukhopadhyay | Internet of Things | Best Researcher Award 

Prof. Dr. Subhas Mukhopadhyay | Macquarie University | Australia

Prof. Dr. Subhas Mukhopadhyay of globally recognized researcher in smart sensors, wireless sensor networks, Internet of Things (IoT), mechatronics, and intelligent instrumentation systems, with over 18,376 citations, 694 publications, and an h-index of 70. His research encompasses the design, modeling, and implementation of sensor-based systems for environmental, healthcare, and industrial applications. He leads cutting-edge projects including ant-inspired swarm robotics for cooperative transport, drone architectures for mid-air item transfers, AI-enabled surgical systems for live tumor detection, and IoT-enabled intelligent sensing for smart cities and agriculture. His innovations also extend to wearable e-skin force sensors, nitrate detection for groundwater monitoring, and low-cost molecularly imprinted polymer MEMS sensors for point-of-care diagnostics. A prolific mentor, he supervises numerous doctoral, master’s, and undergraduate projects, advancing interdisciplinary research at the intersection of electronics, AI, and mechatronics. A Fellow of IEEE, IET, and IETE, Prof. Mukhopadhyay is acclaimed for his extensive contributions to sensor technology, robotics, and intelligent systems, earning multiple international awards and recognition for his editorial and research excellence.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Gooneratne, C. P., Mukhopadhyay, S. C., Li, B., Zhan, G., Magana-Mora, A., & Moellindick, T. E. (Patent No. US11639647B2). SELF-POWERED ACTIVE VIBRATION AND ROTATIONAL SPEED SENSORS. Publication No. US20220034174A1.

Gooneratne, C. P., Mukhopadhyay, S. C., Li, B., Zhan, G., Magana-Mora, A., & Moellindick, T. E. (Patent No. US11557985B2). PIEZOELECTRIC AND MAGNETOSTRICTIVE ENERGY HARVESTING WITH PIPE-IN-PIPE STRUCTURE. Publication No. US20220034173A1.

Gooneratne, C. P., Mukhopadhyay, S. C., Li, B., Zhan, G., Magana-Mora, A., & Moellindick, T. E. (Patent No. US11480018B2). SELF-POWERED SENSORS FOR DETECTING DOWNHOLE PARAMETERS. Publication No. US20220034174A1.

Gooneratne, C. P., Mukhopadhyay, S. C., Li, B., Zhan, G., Magana-Mora, A., & Moellindick, T. E. (Patent No. US11421513B2). TRIBOELECTRIC ENERGY HARVESTING WITH PIPE-IN-PIPE STRUCTURE. Publication No. US20220038031A1.

Gooneratne, C. P., Mukhopadhyay, S. C., Li, B., Zhan, G., Magana-Mora, A., & Moellindick, T. E. (Patent No. US11428075B2). SYSTEM AND METHOD OF DISTRIBUTED SENSING IN DOWNHOLE DRILLING ENVIRONMENTS. Publication No. US20220034198A1.