Academic Profile

• Ph.D in Information and Communication Engineering, Anna University, Chennai

• M.E (Computer Science and Engineering) from Nandha Engineering College, Perundurai with first class 8.2 CGPA

• B.E (Computer Science and Engineering) from Velalar College of Engineering

Professional Experience

• Professor in Computer Science and Engineering, Nandha Engineering College, Erode (June 2024 - Till Date)

• Assistant Professor (Selection Grade) in Computer Science and Engineering, KPR Institute of  Engineering and Technology, Coimbatore (May 2022 - May 2024)

• Senior Assistant Professor in Computer Science and Engineering, KPR Institute of Engineering and Technology, Coimbatore (July 2016 – April 2022)

• Assistant Professor in Computer Science and Engineering, KPR Institute of Engineering and Technology, Coimbatore (June 2012 - July 2016)

• Lecturer in Computer Science and Engineering, Sasurie College of Engineering, Tirupur (August 2011 – May 2012)

Anna University Supervisorship

• Supervisor Recognition ID: 4140133

• Number of Scholars Pursuing Ph.D.: 8 

SCI Indexed Research Articles

• M Thanjaivadivel, Rajasekaran Thangaraj, Edge computing based deep learning framework for biodegradable waste classification in smart waste management systems,  International Journal of Environmental Science and Technology.

• S. Sadesh , Rajasekaran Thangaraj, P. Pandiyan , R. Devi Priya , Palanichamy Naveen, Identification of Monkeypox Disease Based on MpoxNet and Swin Transformer Models Using Mobile Application, International Journal of Interactive Multimedia and Artificial Intelligence.

• Chandrasekaran, G., Rajasekaran Thangaraj, & Kumar, N. S. (2024). Test scheduling of network-on-chip using hybrid WOA-GWO algorithm. Intelligent Data Analysis, 1-20.

• Munirathinam, R., Tamilnidhi, M., Rajasekaran Thangaraj, Eswaran, S., Chandrasekaran, G., & Kumar, N. S. (2024). Automatic multiclass classification of laryngeal cancer using deep convolution neural networks. Electronics Letters, 60(1), e13070.

• Rajasekaran Thangaraj, Pandiyan P, S. Anandamurugan , Sivaramakrishnan Rajendar, A Deep Convolution Neural Network Model Based on Feature Concatenation Approach for Classification of Tomato Leaf Disease, Multimedia Tools and Applications, Springer,2023, IF:3.6.

• Vishnu Kumar Kaliappan, Rajasekaran Thangaraj, Pandiyan P, Mohanasundaram K, Anandamurugan S, Dugki Min, Real-Time Face Mask Position Recognition System using YOLO models for Preventing COVID-19 Disease Spread in Public places, International Journal of Ad Hoc and Ubiquitous Computing, Inderscience, IF:0.773.

• Pandiyan P, Rajasekaran Thangaraj, Subramanian M, Rahul R, Nishanth M, Indupriya Palanisamy, Real-Time monitoring of Social Distancing with Person Marking and Tracking System using YOLO V3 model, International Journal of Sensor Networks, 38(3), 154-165, Inderscience, IF:1.3.

• Rajasekaran Thangaraj, Anandamurugan.S, Pandiyan. P & Vishnu Kumar Kaliappan, Artificial intelligence in tomato leaf disease detection: a comprehensive review and discussion. Journal of Plant Disease and Protection, IF:1.9, Springer,2021.

• Rajasekaran Thangaraj, Anandamurugan, S. & Vishnu Kumar Kaliappan, Automated tomato leaf disease classification using transfer learning-based deep convolution   neural   network. Journal   of    Plant    Disease    and    Protection, IF:1.9, Springer,2021.

Scopus Indexed Research Articles

• • M Jayasree, Gokul Chandrasekaran, M Saranya, S Gopinath, T Rajasekaran. Wn-Based Skin Cancer Lesion Segmentation of Melanoma Using Deep Learning Methods. Indonesian Journal of Electrical Engineering and Informatics,2025.

  • Pandiyan, P, Rajasekaran Thangaraj, Balasubramanian V, & Manavalasundaram V. K (2025). Monitoring COVID-19 environment: a real-time facial mask detection using YOLO models. Research on Biomedical Engineering, 41(1), 1-18.(Scopus)

  • Rajasekaran Thangaraj, Pandiyan, P., Ramakrishnan, J., Nallakumar, R., & Eswaran, S. A deep convolution neural network for automated Covid-19 disease detection using chest X-ray images. Healthcare Analytics, 100278, Elesiver,2023(Scopus).

  • Naveen, P., Rajasekaran Thangaraj, R., & Maragatharjan, M. (2023). Contextual Reinforcement Learning for Enhanced Machine Translation using Transformers, 2023(Scopus).

  • Rajasekaran Thangaraj, Sivaramakrishnan Rajendar, Premkumar Murugiah, Vidhya Kandasamy, Rahul R, Reinforcement Learning Based Autonomous Path Finding Robot for Dynamic Environments, International Journal of Future Generation Communication and Networking,Vol.13.No.2,(2020).(WoS)

  • Mega Varsha Ramasami, Rajasekaran Thangaraj, S Manoj Kumar, Analysis of Bigmart Outlets sales using Big Data Analytics Method, 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), pp.1143-1146. IEEE Xplore, 2023(Scopus).

  • Rajasekaran Thangaraj, M Mohan, M Moulik, A Logeshwari, T Loganathan, P Koushika, A Comparative Study of Deep Learning Models for Guava Leaf Disease Detection, 2023 Third International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), pp.1-5. IEEE Xplore, 2023(Scopus).

  • Rajasekaran Thangaraj, Sivaramakrishnan Rajendar, M Sanjith, Sudev Sasikumar, L Chandhru, Automated Recognition of Wild Animal Species in Camera Trap Images Using Deep Learning Models, 2023 Third International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), pp.1-5. IEEE Xplore, 2023(Scopus).

  • Vadivel, Balasubramaniam, Rajasekaran Thangaraj, P. Pandiyan, T. Aravind, K. Harish, and E. Sivaraman,Deep Learning Models for Potato Leaf Disease Identification: A Comparative Analysis, In 2022 International Conference on Green Energy, Computing and Sustainable Technology (GECOST), pp. 58-62. IEEE Xplore, 2022(WoS,Scopus).

  • T Pavithra, Rajasekaran Thangaraj, P Pandiyan, Balasubramaniam Vadivelu,Real-Time Handgun Detection in Surveillance Videos based on Deep Learning Approach,IEEE Xplore,2022(Scopus).

  • Rajasekaran Thangaraj, Vishnu Kumar Kaliappan, M Pradheep, M Nishanth & Dugki Min, Real-Time Automatic License Plate and Helmet Detection of Urban Motorcyclist based on Deep Learning Approach for Surveillance Systems, Springer Lecture Series(Scopus).

  • Rajasekaran Thangaraj, P Pandiyan, T Pavithra, V.K Manavalasundaram, R Sivaramakrishnan & Vishnu Kumar Kaliappan,Deep Learning based Real-Time Face Detection and Gender Classification using OpenCV and Inception V3,IEEE Xplore,2022, DOI: 10.1109/ICAECA52838.2021.9675635.(Scopus)

  • Vishnu Kumar Kaliappan, Gnanamurthy, S, Kumar C. S, Rajasekaran Thangaraj, & Mohanasundaram, K. Reduced power consumption by resource scheduling in mobile cloud using optimized neural network. Materials Today: Proceedings, Elesiver,2021.(Scopus)

  • Sivaramakrishnan Rajendar, Rajasekaran Thangaraj, Jayasheelan Palanisamy, Vishnu   Kumar Kaliappan, Comparative Analysis of Classifier Models for the Early Prediction of Type 2 Diabetes, International Journal of Advanced Science and Technology,2020.(Scopus)

  • Rajasekaran Thangarasu, Kaliappan, V. K., Surendran, R., Sellamuthu, K., & Palanisamy, J. (2019). Recognition of animal species on camera trap images using machine learning and deep learning models. International Journal of Scientific and Technology Research, 8(10), 2613-2622.(Scopus)

  • T.Rajasekaran, Data Analysis On Diet Management And Disease Prediction, International Journal of Applied Engineering Research,2016.(Scopus)

  • Jayasheelan Palanisamy, S.Devaraju & Rajasekaran Thangaraj, Smart Irrigation System for Tomato Plants Using Arduino,International Journal of Life Science Pharma Research,pp.141-148.(WoS)

  • Rajasekaran Thangaraj, Dinesh D, Hariharan S, Rajendar S, Gokul, D, & Hariskarthi, T. R. (2020). Automatic Recognition of Avocado Fruit Diseases using Modified Deep Convolutional Neural Network. International Journal of Grid and Distributed Computing, 13(1), 1550-1559.(WoS)

  • Rajasekaran T, Jayasheelan P, & Preethaa K. S. (2016). Predictive analysis in agriculture to improve the crop productivity using zeroR algorithm. International Journal of Computer Science and Engineering Communications, 4(2), 1397-1401.

  • J. Sruthi, T. Rajasekaran, N. Raveena, S. Revathi, Social Network Based Disaster Analysis Using Naive Bayesian Classification Algorithm, International Journal of Advanced Research in Computer Science and Software Engineering,2016.

  • T. Pavithra, T.Rajasekaran, S.Prem Akshaya, N. Venkatesh Brabhu, Internet of Things in Various Scenarios: A Survey, International Journal on Recent and Innovation Trends in Computing and Communication,2016

  • T.Rajasekaran, V.Sowmeya, S.Suha, S.V.Vinodhini ,Abnormality Detection from Blood Report using Hierarchical Clustering Algorithm, International Journal of Latest Technology in Engineering, Management & Applied Science,2016

  • T Rajasekaran, R Tharani priya, V Pavithra, P Sudharshanam,Heart Attack Prediction for Diabetic’s Patient using Data Analytics, South Asian Journal of Engineering and Technology,2015.

  • T.Rajasekaran, V.Sowmeya, S.Suha, S.V.Vinodhini, Predictive Analysis of Blood Test Report, SS International Journal of Multidisciplinary Research,2015.

  • T.Rajasekaran,Data Analysis Classifier Model for Prediction of Human Ailments Using Artificial Neural Network, International Journal of Computer Science and Engineering Communication,2015.

  • T.Rajasekaran, P.Barathkumar, M.Guruprasath, S.Santhosh,Keyword Conscious Provision Endorsement Method,International Journal of Latest Technology in Engineering, Management & Applied Science,2015.

Book Chapter Publication

• Rajasekaran Thangaraj, Pandiyan, P., Naveen, P., Vadivel, B., Prakash, P., & Kumar, S. M. (2026). Automatic Detection of Tropical Cyclones from Satellite Images Using YOLO Models. Integrating AI for Sustainable Disaster Management: Building Resilience and Preventing Catastrophes, 79-98.

• Rajasekaran Thangaraj, Naveen, P., Maheswar, R., Mohanasundaram, K., Arivazhagan, S., & Prakash, K. B. (2026). Introduction to Sustainable Development and Disaster Management. Integrating AI for Sustainable Disaster Management: Building Resilience and Preventing Catastrophes, 1-23

• Geetha, S. K., Kiruthika, J. K., Sathya, S., Srisathya, K. B., Rajasekaran Thangaraj, & Priya, R. D. (2026). Intelligent Transportation Systems in Cyclone‐Prone Areas: A Study and Future Perspectives. Integrating AI for Sustainable Disaster Management: Building Resilience and Preventing Catastrophes, 99-120.

• Pandiyan P, Rajasekaran Thangaraj, Subramanian M, Vivekanandan S, Arivazhagan S, Geetha S K,A Comprehensive Review on Internet of Agro Drones for Precision Agriculture, Internet of Drones: Applications, Opportunities and Challenges,2022,CRC Press,Taylor & Francis Group(Scopus).

• Pandiyan P, Rajasekaran Thangaraj, Srinivasulu Raju S and Vishnu Kumar Kaliappan,White Blood Cells classification using Conventional and Deep Learning Techniques: A Comparative Study, Advances in Deep Learning for Medical Image Analysis, 2022,CRC Press,Taylor & Francis Group(Scopus).

• S.Sarvanan, P Pandiyan, T Rajasekaran,N Prabaharan,T Chinnadurai and Ramji Tiwari, Machine Learning-Based Predictive Maintenance for Solar Plants for Early Fault Detection and Diagnostics, Photovoltaic Sytems-Artificial Intelligence based Fault Diagnosis and Predictive Maintenance,2022,CRC Press, Taylor & Francis Group(Scopus).

• Rajasekaran Thangaraj, Internet of Things in Healthcare: An Extensive Review on Recent Advances, Challenges, and Opportunities, Book:Incorporating the Internet of Things in Healthcare Applications and Wearable Devices, IGI Global ,23-39, 2020(Scopus).

• Rajasekaran Thangaraj, Futuristic Adoption of Blockchain Technology in Smart Agriculture and Food Industry: Basic Concepts, Structure, Characteristics, Applicabilties, IGI Global,2023(Scopus).

Conference Publication

•  Rajasekaran Thangaraj, P Sindhu, P Kavineswaran, S Karuppusamy, C Mani, D Kavin Kumar, Explainable Deep Learning for Computer-Aided Diagnosis of Diabetic Foot Ulcers, IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN), 2025.

• Rajasekaran Thangaraj, D Preethishri, B Deepa, S Geetha, V Mythily, Sivaraman Eswaran, Automatic Detection of Corneal Ulcers Using Convolution Neural Network, IEEE International Conference on Green Energy, Computing and Sustainable Technology (GECOST), 2025.

• P Prakash, Rajasekaran Thangaraj, N Hasin, S Karthikadevi, P Kannan, Dinesh Kumar SB, Consensus-Based Ensemble Learning for Secure Fingerprint Authentication in E-Voting Systems, IEEE International Conference on Communication and Electronics Systems (ICCES), 2025.

• P Prakash, Rajasekaran Thangaraj, N Hasin, S Karthikadevi, P Kannan, SB Dinesh Kumar, Detection of Melanoma from Dermoscopic Images Using Visual Geometry Group (VGG16) Model Based Convolutional Neural Networks (CNN), IEEE International Conference on Inventive Computing and Informatics (ICICI), 2025.

• Rajasekaran Thangaraj, Balasubramaniam Vadivel, S Manoj Kumar, S Sadesh, P Karunakaran, Monkeypox Disease Classification from Skin Lesion Images using Deep Convolution Neural Network, IEEE International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC), 2025.

• Rajasekaran Thangaraj, P Jaisankar, S Lakshana, G Devadharshini, P Jeyabharathi, Bird Species Detection Using Deep Learning Techniques, IEEE International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC), 2025.

• M. Siva Sangari & T. Rajasekaran T. Shanmugapriya, R. Devipriya, Effective Heart Disease Prediction Using Machine Learning Algorithm with Cardiovascular Health Monitoring System, International Conference on Soft Computing and Pattern Recognition, 2025.

• S. M. Nandhagopal & G. Kaushik R.Devi Priya, R. Sivaraj, T. Rajasekaran, M. Sivasankari, T. Shanmuga Priya, Deep Learning Based Early Diagnosis of Malnutrition Among Tribal Pregnant Women in Tamil Nadu, International Conference on Innovations in Bio-Inspired Computing and Applications, 2025.

• R Devi Priya, P Kirupa, T Rajasekaran, S Manoj Kumar, Bi-Staged Attendance Automation System with Face and Voice Detection Using Viola-Jones Recognition Algorithm, Digital Geography: Proceedings of the International Conference on Internet and Modern Society (IMS 2023).

• R Devi Priya, L Tharunika, S Shreya, T Rajasekaran, M Sivasankari, T Shanmuga Priya, R Sivaraj, Large Language Models Based Framework for Finding Cloth Quality, International Conference on Soft Computing and Pattern Recognition, 2023.

• Rajasekaran Thangaraj, Balasubramaniam Vadivel, T Aravind, L Chandhru, K Harish, Sivaraman Eswaran, Tea Leaf Disease Identification using Improved Convolution Neural Network, International Conference on Digital Applications, Transformation & Economy (ICDATE), 2023.

• Mega Varsha Ramasami, Rajasekaran Thangaraj, S Manoj Kumar, Analysis of Bigmart Outlets sales using Big Data Analytics Method, 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), pp.1143-1146. IEEE Xplore, 2023(Scopus).

• Rajasekaran Thangaraj, M Mohan, M Moulik, A Logeshwari, T Loganathan, P Koushika, A Comparative Study of Deep Learning Models for Guava Leaf Disease Detection, 2023 Third International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), pp.1-5. IEEE Xplore, 2023(Scopus).

• Rajasekaran Thangaraj, Sivaramakrishnan Rajendar, M Sanjith, Sudev Sasikumar, L Chandhru, Automated Recognition of Wild Animal Species in Camera Trap Images Using Deep Learning Models, 2023 Third International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), pp.1-5. IEEE Xplore, 2023(Scopus).

• C Sasikala, Rajasekaran Thangaraj, Devipriya R, S RajeshKumar, Ramachandramoorthy K B, S Ramya, K Umapathi, Fake Review Prediction Using Machine Learning, International Conference on Intelligent Systems Design and Applications, 2022.

• Vadivel, Balasubramaniam, Rajasekaran Thangaraj, P. Pandiyan, T. Aravind, K. Harish, and E. Sivaraman,Deep Learning Models for Potato Leaf Disease Identification: A Comparative Analysis, In 2022 International Conference on Green Energy, Computing and Sustainable Technology (GECOST), pp. 58-62. IEEE Xplore, 2022(WoS,Scopus).

• T Pavithra, Rajasekaran Thangaraj, P Pandiyan, Balasubramaniam Vadivelu, Real-Time Handgun Detection in Surveillance Videos based on Deep Learning Approach,IEEE Xplore,2022(Scopus).

• Rajasekaran Thangaraj, Vishnu Kumar Kaliappan, M Pradheep, M Nishanth & Dugki Min, Real-Time Automatic License Plate and Helmet Detection of Urban Motorcyclist based on Deep Learning Approach for Surveillance Systems, Springer Lecture Series(Scopus).

• Rajasekaran Thangaraj, P Pandiyan, T Pavithra, V.K Manavalasundaram, R Sivaramakrishnan & Vishnu Kumar Kaliappan,Deep Learning based Real-Time Face Detection and Gender Classification using OpenCV and Inception V3,IEEE Xplore,2022, DOI: 10.1109/ICAECA52838.2021.9675635.(Scopus).

• Rajasekaran T, Pandiyan P, & Vishnu Kumar K Potato Leaf Disease Classification using Transfer Learning based Modified-Xception Model, Advances in Computing, Communication, Automation and Biomedical Technology, ICACCBT-2020,

• Pandiyan P, Rajasekaran T, Vishnu Kumar K, Sivaramakrishnan R and Thiagarajan T ,Fish Species Classification using Kernels in Support Vector Machine, Advances in Computing, Communication, Automation and Biomedical Technology, https://doi.org/10.46532/978-81-950008-1-4_102, ICACCBT-2020,

• Rajasekaran T, & Anandamurugan, S, Challenges and applications of wireless sensor networks in smart farming—a survey. In Advances in big data and cloud computing (pp. 353-361). 2019, Springer, Singapore.

• Rajasekaran, T, Sruthi, J, Revathi S, & Raveena N,Forest fire prediction and alert system using big data technology. In Proceedings of the International Conference on Information Engineering, Management and Security, ICIEMS (pp. 23-26),2015.

Dataset Published

• P, Naveen; T Rajasekaran (2024), “Underwater Species Dataset (NR) from Video: Seals, Dolphins, Sea Turtles, Octopus, Seahorse, Sharks, Whales”, Mendeley Data, V1, doi: 10.17632/4tp83br92z.1(Mendeley)

• T Rajasekaran; P, Naveen; Vadivel, Balasubramaniam (2024), “K-Kotagiri (NRB) Avocado Leaf DataSet”, Mendeley Data, V1, doi: 10.17632/6zy6wxhf2v.1(Mendeley).

• T Rajasekaran; P, Naveen; R, Devi Priya; Vadivel, Balasubramaniam; Ravi, Vinayakumar (2024), “K-Kotagiri Tea Leaf Dataset”, Mendeley Data, V1, doi: 10.17632/68yy284sh9.1(Mendeley).

Patent Published

Title: Enhanced Automatic Detection and Warning System for Wild Animal Movements.     

Indian Patent Application No.: 202041004755

Title: Methane Gas Measuring device in Food wastage using Raspberry Pi, MQ-4 sensor.

Indian Patent Application No:202041036326

Title: Monitoring of People Social Distancing to Prevent Pandemic Disease Spread.

Indian Patent Application No: 202041021952

Title: Low-Cost Intelligent Face Recognition and Temperature Monitoring System.

Indian Patent Application No: 202041047712

Title: Portable E-Vocal Communication Device for Disable  

Indian Patent Application No: 202041052221 

Consultancy work

Project : Augment Reality App for Furniture Shopping

     Company : Aadhavan Furniture, Erode

Project : Virtual Reality App for Furniture Shopping

     Company : Aadhavan Furniture, Erode

Project : Payment Gateway Integration

     Company : Admire Solutions, Erode

Project : Web Application for Invoice Generation

Company : Preciso Tools and Engineering, Bangalore

Project : Hospital Process Automation(Web Application)

     Company : RKS Hospital, Erode

Professional Society Membership

• Life Member: Indian Society for Technical Education(ISTE)

• IEEE Computer Society