Manivannan Karunakaran

About

Dr. Manivannan Karunakaran is a distinguished Professor and Head in the Department of Information Science and Engineering at Jain University, Bangalore. With over 19 years of teaching experience, he specializes in Machine Learning and Medical Image Processing. Dr. Manivannan completed his B.E. and M.E. in Computer Science and Engineering from Anna University, Chennai, and earned his Ph.D. from the same institution in February 2015. Throughout his career, Dr. Manivannan has demonstrated a strong commitment to academic excellence, research, and leadership. He has published over 44+ research papers in reputable international journals, 16+ papers in conferences, and authored 9 books and book chapters. His contributions to academia include serving as a reviewer for esteemed journals such as Elsevier and Springer, and as a coordinator for various academic and administrative committees. Dr. Manivannan has successfully guided 5 Ph.D. scholars and received several grants for his research projects, including funding from the Indian Council of Medical Research and AICTE. His professional affiliations include memberships in ISTE, IACSIT, and IAENG. Recognized for his teaching excellence and research contributions, Dr. Manivannan continues to inspire students and advance the field of Computer Science and Engineering through his innovative work and dedication.

Employment

• Jain University Professor & Head
  2023 - Present
• PSNA College of Engineering and Technology Professor
  2021 - Present
• PSNA COLLEGE OF ENGINEERING AND TECHNOLOGY ASSOCIATE PROFESSOR
  2018 - 2021
• PSNA College of Engineering and Technology ASSISTANT PROFESSOR
  2008 - 2018

Education

• RVS College of Engineering and Technology M.E Computer Science & Engineering
  2006 - 2008
• KLN College of Information and Technology B.E Computer Science and Engineering
  2002 - 2005

Projects & Funding

Projects & funding information is unavailable.

Publications (49)

• Simulation-driven dual-band Graphene–Silver terahertz metasurface biosensor integrated with machine learning for mode-resolved hemoglobin detection
  Sensors International 2026 DOI: 10.1016/j.sintl.2025.100357
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• Intrusion Detection in Wireless Sensor Networks Using a Machine Learning-Driven Cyber Security Framework
  SN Computer Science 2026 DOI: 10.1007/s42979-026-04860-6
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• Chapter 5 Machine learning for twinning the human body
  Digital Transformation in Healthcare 5.0 2024 DOI: 10.1515/9783111398549-005
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• Blockchain Technology in Cloud Security
  2024 DOI: 10.4018/979-8-3693-2081-5.ch003
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• Efficient Guided Grad-CAM Tuned Patch Neural Network for Accurate Anomaly Detection in Full Images
  Information Technology and Control 2024 DOI: 10.5755/j01.itc.53.2.34525
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• Role of data visualization and big data analytics in smart agriculture
  AI Applications for Business, Medical, and Agricultural Sustainability 2024 DOI: 10.4018/979-8-3693-5266-3.ch007
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• The Deciding Divide: A Comparative Study on Exploring the Parallels and Contrasts in Decision-Making between Humans and Artificial Intelligence
  3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023 2023 DOI: 10.1109/ICTBIG59752.2023.10456325
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• Securing Data in the Cloud: The Application of Fuzzy Identity Biometric Encryption for Enhanced Privacy and Authentication
  Lecture Notes in Networks and Systems 2023 DOI: 10.1007/978-981-99-7093-3_14
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• Retraction Note to: Effective segmentation and classification of brain tumor using rough K means algorithm and multi kernel SVM in MR images (Journal of Ambient Intelligence and Humanized Computing, (2021), 12, (6751–6760), 10.1007/s12652-020-02300-8)
  Journal of Ambient Intelligence and Humanized Computing 2023 DOI: 10.1007/s12652-022-04163-7
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• Detection of meningioma tumor images using Modified Empirical Mode Decomposition (MEMD) and convolutional neural networks
  Journal of Intelligent and Fuzzy Systems 2023 DOI: 10.3233/JIFS-222172
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