Dr. Rajendran Thavasimuthu

About

Dr. Rajendran Thavasimuthu holds a B.E., M.E., and Ph.D. in Electronics and Communication Engineering from Karpagam Academy of Higher Education, Coimbatore (2013, 2015, 2021), and a second Masters M.Tech. in Computing Systems and Infrastructure from BITS Pilani (2025). He has served as R&D Head at Makeit Technologies, Coimbatore (2015–2020), Vice Principal (i/c) of MM Polytechnic College, Trichy (2020–2023), and Assistant Professor at Rajalakshmi Institute of Technology, Chennai (2023-2025). He is currently associated with JCT College of Engineering and Technology, Coimbatore as an Associate Professor of Computer Science and Engineering. With over 45 indexed publications and 3 patents, he is a member of IEEE Young Professionals. His research interests span Biomedical Image/Signal Processing, Machine Learning, Artificial Intelligence, IoT, and Network Security.

Employment

• JCT College Of Engineering And Technology Associate Professor & Research Coordinator
  2025 - Present
• Rajalakshmi Institute of Technology Assistant Professor
  2023 - 2025
• MM Polytechnic College Head of the Electronics and Communication Engineering Department and Vice Principal in Charge
  2020 - 2023
• Makeit Technologies Head
  2015 - 2020

Education

• Birla Institute of Technology and Science, Pilani M.Tech Computing Systems and Infrastructure
  2023 - 2025
• Karpagam Academy of Higher Education (Deemed to be University) Ph.D.,
  2015 - 2020
• Karpagam Academy of Higher Education (Deemed to be University) M.E., (VLSI DESIGN)
  2013 - 2015
• Karpagam Academy of Higher Education B.E.,
  2010 - 2013

Projects & Funding

Projects & funding information is unavailable.

Publications (60)

• A Multi-Axis Vision Transformer (MaxViT) for Classifying Alzheimer's via MRI Imaging
  2026 DOI: 10.1109/ICMSCI67830.2026.11469218
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• Automated weld defect detection using an optimized AlexNet–GRU model with Greylag Goose optimization algorithm
  Advances in Mechanical Engineering 2026 DOI: 10.1177/16878132261466632
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• Sentiment analysis based on deep features through textual tweets classification using optimal hierarchical CLSTM network model
  Knowledge and Information Systems 2026 DOI: 10.1007/s10115-026-02751-z
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• MogaNet Classification Model to Classify Alzheimer's Disease from MRI
  Proceedings of the 6th International Conference on Pervasive Computing and Social Networking Icpcsn 2026 2026 DOI: 10.1109/ICPCSN68523.2026.11543619
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• Edge-AI Driven Smart Crop Protection and Management: Integrating Vision Transformers, Graph Neural Networks, and Federated Learning for Real-Time, Sustainable, and Scalable Precision Agriculture
  Proceedings of 3rd International Conference on Machine Learning and Autonomous Systems Icmlas 2026 2026 DOI: 10.1109/ICMLAS67792.2026.11483902
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• EMG-based hand gesture recognition using multi-scale deep residual network with SE-module
  Scientific Reports 2026 DOI: 10.1038/s41598-026-54525-w
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• Causal Retrieval-Augmented Generation: ModifyingFake Correlations in AI-Driven Knowledge Systems through Algorithmic Nudging
  Research Square 2026 DOI: 10.21203/rs.3.rs-10218278/v1
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• Applying the MOAT Deep Learning Model to Identify Alzheimer's Disease from Brain MRI
  Proceedings of 6th International Conference on Expert Clouds and Applications Icoeca 2026 2026 DOI: 10.1109/ICOECA68095.2026.11485586
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• An MRI-based Alzheimer's Disease Classification Model with Swin Transformer
  Proceedings of the 6th International Conference on Pervasive Computing and Social Networking Icpcsn 2026 2026 DOI: 10.1109/ICPCSN68523.2026.11543651
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• An MRI-based Alzheimer's Disease Classification Model with DiNAT
  Proceedings of 9th International Conference on Inventive Computation Technologies Icict 2026 2026 DOI: 10.1109/ICICT68280.2026.11510774
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