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2025

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Computer Science

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70
Citations
14746
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1907
National Ranking
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  • 2025 - Research.com Rising Stars Award

Overview

Gunasekaran Manogaran is affiliated with the University of California, Davis in the United States. Their research spans multiple fields, primarily focusing on computer science and engineering. Within these broader disciplines, Manogaran has contributed extensively to subfields such as computer networks and communications, artificial intelligence, information systems, electrical and electronic engineering, and computer vision and pattern recognition.

Their main topics of research address areas including IoT and edge/fog computing, blockchain technology applications and security, vehicular ad hoc networks (VANETs), COVID-19 diagnosis using AI, privacy-preserving technologies in data, cloud computing and resource management, as well as retinal imaging and analysis.

Manogaran has published recent papers relevant to these subjects, including:

  • "A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic" (2020, Measurement)
  • "Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection" (2020, Sustainable Cities and Society)
  • "Trustworthiness in Industrial IoT Systems Based on Artificial Intelligence" (2020, IEEE Transactions on Industrial Informatics)
  • "A deep transfer learning model with classical data augmentation and CGAN to detect COVID-19 from chest CT radiography digital images" (2020, Neural Computing and Applications)
  • "IOT based wearable sensor for diseases prediction and symptom analysis in healthcare sector" (2020, Peer-to-Peer Networking and Applications)

Their frequent coauthors include Ching-Hsien Hsu, Priyan Malarvizhi Kumar, Bharat S. Rawal, P. Mohamed Shakeel, and Seifedine Kadry.

Manogaran's work appears regularly in several publication venues with multiple contributions, including:

  • IEEE Transactions on Intelligent Transportation Systems
  • Future Generation Computer Systems
  • IEEE Transactions on Industrial Informatics
  • Neural Computing and Applications
  • IEEE Internet of Things Journal

Additionally, Manogaran has published books through Springer Nature. Among these are "Implementing and Leveraging Blockchain Programming" (2022) and "Proceedings of International Conference on Deep Learning, Computing and Intelligence" (2022).

Best Publications

  • A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic

    Mohamed Loey;Gunasekaran Manogaran;Gunasekaran Manogaran;Mohamed Hamed N. Taha;Nour Eldeen M. Khalifa

  • A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system

    Gunasekaran Manogaran;R. Varatharajan;Daphne Lopez;Priyan Malarvizhi Kumar

  • RETRACTED: Internet of Things (IoT) and its impact on supply chain: A framework for building smart, secure and efficient systems

    Mohamed Abdel-Basset;Gunasekaran Manogaran;Mai Mohamed

  • Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection.

    Mohamed Loey;Gunasekaran Manogaran;Gunasekaran Manogaran;Mohamed Hamed N. Taha;Nour Eldeen M. Khalifa

  • A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria

    Mohamed Abdel-Basset;Gunasekaran Manogaran;Abduallah Gamal;Florentin Smarandache

  • Internet of things in smart education environment: Supportive framework in the decision-making process

    Mohamed Abdel-Basset;Gunasekaran Manogaran;Mai Mohamed;Ehab Rushdy

  • Trustworthiness in Industrial IoT Systems Based on Artificial Intelligence

    Zhihan Lv;Yang Han;Amit Kumar Singh;Gunasekaran Manogaran

  • Wearable sensor devices for early detection of Alzheimer disease using dynamic time warping algorithm

    R. Varatharajan;Gunasekaran Manogaran;M. K. Priyan;Revathi Sundarasekar

  • A Novel Intelligent Medical Decision Support Model Based on Soft Computing and IoT

    Mohamed Abdel-Basset;Gunasekaran Manogaran;Abduallah Gamal;Victor Chang

  • A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem

    Mohamed Abdel-Basset;Gunasekaran Manogaran;Doaa El-Shahat;Seyedali Mirjalili

  • A deep transfer learning model with classical data augmentation and CGAN to detect COVID-19 from chest CT radiography digital images.

    Mohamed Loey;Gunasekaran Manogaran;Gunasekaran Manogaran;Nour Eldeen M. Khalifa

  • A Group Decision Making Framework Based on Neutrosophic TOPSIS Approach for Smart Medical Device Selection

    Mohamed Abdel-Basset;Gunasekaran Manogaran;Abduallah Gamal;Florentin Smarandache

  • Hybrid Recommendation System for Heart Disease Diagnosis based on Multiple Kernel Learning with Adaptive Neuro-Fuzzy Inference System

    Gunasekaran Manogaran;R. Varatharajan;M. K. Priyan

  • IOT based wearable sensor for diseases prediction and symptom analysis in healthcare sector

    BalaAnand Muthu;C. B. Sivaparthipan;Gunasekaran Manogaran;Revathi Sundarasekar

  • Machine Learning Based Big Data Processing Framework for Cancer Diagnosis Using Hidden Markov Model and GM Clustering

    Gunasekaran Manogaran;V. Vijayakumar;R. Varatharajan;Priyan Malarvizhi Kumar

  • An ontology-driven personalized food recommendation in IoT-based healthcare system

    V. Subramaniyaswamy;Gunasekaran Manogaran;R. Logesh;V. Vijayakumar

  • A big data classification approach using LDA with an enhanced SVM method for ECG signals in cloud computing

    R. Varatharajan;Gunasekaran Manogaran;M. K. Priyan

  • Neural Network Based Brain Tumor Detection Using Wireless Infrared Imaging Sensor

    P. Mohamed Shakeel;Tarek E. El. Tobely;Haytham Al-Feel;Gunasekaran Manogaran

  • Intelligent decision-making of online shopping behavior based on internet of things

    Hanliang Fu;Gunasekaran Manogaran;Kuang Wu;Ming Cao

  • Wearable IoT Smart-Log Patch: An Edge Computing-Based Bayesian Deep Learning Network System for Multi Access Physical Monitoring System.

    Gunasekaran Manogaran;P. Mohamed Shakeel;Hassan Fouad;Yunyoung Nam

Frequent Co-Authors

Ching-Hsien Hsu
Ching-Hsien Hsu Asia University Taiwan
Naveen Chilamkurti
Naveen Chilamkurti La Trobe University
Priyan Malarvizhi Kumar
Priyan Malarvizhi Kumar University of North Texas
Seifedine Kadry
Seifedine Kadry Lebanese American University
Mamoun Alazab
Mamoun Alazab Charles Darwin University
Le Hoang Son
Le Hoang Son Vietnam National University, Hanoi
Florentin Smarandache
Florentin Smarandache University of New Mexico
Seyedali Mirjalili
Seyedali Mirjalili Torrens University Australia
Gautam Srivastava
Gautam Srivastava Brandon University
Shahid Mumtaz
Shahid Mumtaz Nottingham Trent University

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