THILAGAM T

@saec.ac.in

ASSISTANT PROFESSOR AND DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
S.A. ENGINEERING COLLEGE

THILAGAM T


               Download Compact PDF  
https://researchid.co/thilaka28

EDUCATION

M.E (CSE)
Ph.D (PUSUING)

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence, Computer Science, Computer Networks and Communications
37

Scopus Publications

359

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • AI, Sustainability, and Human Well- Being in Logistics Employment: Transforming Work, Efficiency, and Responsible Growth
    S. Anbu, T. Thilagam, G. Manisha, P. Jayabharathi, R. Vinoth, et al.
    Impacts of AI on Employment and Skills in Logistics, 2026
    This chapter explores the transformative role of Artificial Intelligence (AI) in modern logistics, emphasizing its influence on operational efficiency, sustainability, and human well-being. It explores how AI-driven technologies including automation, predictive analytics, and intelligent decision systems enhance productivity while supporting environmental goals through optimized energy use and reduced emissions. The chapter highlights the evolving nature of logistics employment, detailing skill transitions, safety improvements, and psychological impacts associated with human AI collaboration. Ethical considerations, regulatory frameworks, and governance models are analyzed to ensure responsible and equitable AI deployment. Key challenges and future research directions are identified, focusing on sustainable AI development, workforce inclusion, data security, and policy innovation. The chapter underscores the need for balanced, human-centric adoption to achieve resilient and sustainable logistics ecosystems.
  • Key Drivers of Change in Industry 4.0: AI, IoT, Robotics, and Big Data
    V. Rekha, T. P. Anish, T. Thilagam, B. Yamini, V. Nivaskumar
    Navigating Human Machine Collaboration in Smart Factories, 2025
    Industry 4.0 marks a revolutionary phase in industrial development, characterized by the integration of advanced digital technologies such as artificial intelligence (AI), the Internet of Things (IoT), robotics, and Big Data analytics. This chapter explores the core components and enabling technologies of Industry 4.0, emphasizing their applications in manufacturing, logistics, and smart systems. It highlights the synergy between these technologies, their impact on operational efficiency, and the creation of interconnected, intelligent ecosystems. Additionally, it discusses challenges related to implementation, data security, regulatory issues, and workforce readiness. The chapter also explores emerging trends such as 5G, blockchain, and quantum computing, offering insights into future research opportunities. Overall, the chapter underscores the transformative potential of Industry 4.0 in driving global competitiveness and innovation.
  • Optimizing Production Through Sensors, Data Analytics, and Real-Time Information Flow
    K. Venkatesh Guru, B. Mythili, T. Thilagam, B. Yuvasri, L. Dharani, et al.
    Navigating Human Machine Collaboration in Smart Factories, 2025
    This chapter explores the integration of sensors, data analytics, and real-time information flow for optimizing production systems in modern industrial environments. As industries evolve toward smarter, more connected operations, the ability to monitor, analyze, and respond to dynamic conditions in real time has become essential. The chapter reviews sensor technologies, data acquisition methods, analytics techniques, and communication protocols that support production optimization. It also discusses enabling technologies such as IoT, AI, and edge computing, along with real-world applications and evaluation metrics. Key challenges and future research directions are explored, highlighting gaps in scalability, security, interoperability, and human-machine collaboration.
  • A Framework for Enhancing Transparency and Security in Telehealth Record Access Using Dual-One-Time Passwords
    S. Hemalatha, T. Thilagam, Surya Lakshmi Kantham Vinti, B. U. Anu Barathi, B. Yamini Supriya, et al.
    International Journal of Safety and Security Engineering, 2025
  • Internet of Things (IoT) in Urban Development: Applications, Challenges, and Future Research Directions
    B. Maheswari, S. Subha, T. Thilagam
    Post Quantum Cryptography and Iot Communications for Sustainable Urban Development, 2025
    The internet of things (IoT) is revolutionizing urban development by enabling real-time data collection, intelligent automation, and interconnected infrastructure across various sectors. This chapter explores the foundational concepts of IoT in the urban context; key application areas such as transportation, energy, waste management, public safety, and healthcare; and highlights current challenges including privacy, interoperability, and governance. It further discusses emerging trends like AI integration, digital twins, blockchain security, and sustainable IoT practices. The chapter also outlines future research directions focusing on interdisciplinary approaches, innovative business models, and ethical urban innovation. By examining both the potential and limitations of IoT, the chapter emphasizes its transformative role in building sustainable, inclusive, and resilient smart cities.
  • Machine Learning for a Smarter Food Industry: Trends, Challenges, and Innovations
    M. Anita, N. Subhash Chandra, N. Pavithra, K. Bhavani, P. Aparna, et al.
    AI Innovations for Improving the Food Industry, 2025
    The food industry is undergoing a significant transformation driven by the integration of Machine Learning (ML) technologies. This survey chapter explores the diverse applications of ML across key areas such as agriculture, food safety, quality control, supply chain optimization, and personalized nutrition. We categorize widely used ML models, analyze domain-specific challenges, and highlight recent advancements including federated learning, explainable AI, and multimodal approaches. Furthermore, we discuss critical issues such as data privacy, model transparency, and scalability. The chapter also identifies emerging trends and proposes future research directions aimed at building sustainable, intelligent food systems.
  • Harnessing Deep Learning for a Smarter and Sustainable Food Industry
    A. N. Vinodhini, B. Yamini, A. Revathi, R. Kennady, T. Thilagam, et al.
    AI Innovations for Improving the Food Industry, 2025
    DL is slowly revolutionizing the modern food sector by allowing for smart automation, quality assurance, and consumer-centric services in the food supply chain. This chapter provides a detailed description of various DL applications in the fields of food inspection, recognition, spoilage, agriculture, and nutrition recommendations. Disparate concepts of DL architectures are also discussed as well as the recent popular trends such as federated and multimodal learning and its integration with IoT and edge computing. The chapter also describes the issues concerning the quality of data, its interpretability, deployment, and the ethical issue. Finally, we provide insights on research themes that would help in the development of food systems that are sustainable, protective of the consumer's privacy, and efficient. This chapter explores how DL can be used to power innovation and resilience in the food system that is rapidly becoming data-oriented.
  • Machine Learning and Computational Intelligence for Smart Healthcare: Advancing Diagnosis and Treatment
    Siva Subramanian R., R. Asha, J. Sangeetha, A. Adaikkammai, T. Thilagam, et al.
    Applied AI and Computational Intelligence in Diagnostics and Decision Making, 2025
    Machine Learning (ML) and Computational Intelligence (CI) are revolutionizing the healthcare sector by enhancing diagnostic accuracy, personalizing treatments, and optimizing healthcare delivery. This chapter explores the applications, challenges, and emerging trends of ML and CI in smart healthcare, focusing on areas such as medical imaging, disease prediction, personalized medicine, and treatment recommendations. Key challenges such as data quality, algorithmic bias, and model interpretability are discussed, alongside emerging technologies like federated learning, explainable AI, and digital twins. The integration of ML and CI with clinical workflows promises to improve patient outcomes, reduce costs, and foster a more personalized approach to healthcare. The future of smart healthcare lies in developing transparent, collaborative, and scalable AI systems that enhance human expertise while preserving patient privacy and safety.
  • NLP and Machine Learning Innovations in Education: Transforming Learning and Personalization
    K. Sahitya Priyadharshini, B. Yamini, T. P. Anish, T. Thilagam, A. Adaikkammai, et al.
    Educational Applications of Natural Language Processing Chatbots and AI, 2025
    This survey chapter examines how Natural Language Processing (NLP) and Machine Learning (ML) are transforming the modern education. It shows ways in which AI technologies are transforming learning experience with intelligent tutoring systems, automated feedback, adaptive learning platforms, and personalized recommendations. The chapter reviews baseline concepts, major applications, and emerging innovations, including large language models and multimodal analytics. It also tackles some of the major issues such as algorithmic bias, data privacy, and ethical use of AI in education. Interdisciplinary work and responsible design are highlighted as being critical to making AI-driven education equitable, transparent, and effective. By combining the current trends, the chapter provides an overview of the way NLP and ML are improving personalization and the future of learning.
  • Transforming Education with NLP and Machine Learning: Innovations, Applications, and Future Prospects
    R. Siva Subramanian, M. Swetha, K. Krishnaveni, T. Thilagam, K. Saranya, et al.
    Educational Applications of Natural Language Processing Chatbots and AI, 2025
    Natural Language Processing (NLP) and Machine Learning (ML) are transforming education by enhancing personalized learning, automating assessments, and improving content generation. Key innovations include AI-powered tutoring systems, adaptive learning platforms, and language acquisition tools that cater to individual student needs. NLP applications, such as sentiment analysis and language modeling, alongside ML algorithms for predictive analytics, are enabling more efficient and inclusive learning experiences. However, challenges such as data privacy concerns, bias in AI models, and technological barriers remain. The future of education lies in integrating these technologies with immersive tools like AR/VR, fostering lifelong learning, and supporting educators as co-teachers. With continuous research and development, NLP and ML hold the potential to reshape educational landscapes, offering both opportunities and ethical considerations.
  • The Role of Artificial Intelligence in Transforming Supply Chain Management
    P. Suganya, Subramanian R. Siva, S. N. Ananthi, T. Thilagam, J. Elavarasi, et al.
    Transformative Impact of AI in Supply Chain Management, 2025
  • Artificial intelligence in personalized education: Revolutionizing learning paths and student engagement
    AI Personalization Equity and the Future of Learning, 2025
  • Transforming hospitality management through intelligent systems and immersive technologies
    S. Palanikumar, N. Kanimozhi, T. Thilagam, R. Siva Subramanian
    Revolutionizing Hospitality Management Systems with AI VR and Machine Learning, 2025
  • The role of risk management in modern business and technology
    S. Nandhini, B. Yamini, G. Anurekha, T. Thilagam, Sankar Ganesh S., et al.
    AI Methods for Environmental Protection and Resource Conservation, 2025
  • Advancing sustainable development through green economics
    Dhivya Devi S., K. Balasubramanian, A. Adaikkammai, T. Thilagam, R. Vinoth, et al.
    AI Methods for Environmental Protection and Resource Conservation, 2025
  • Machine Learning Approaches to Intrusion Detection in Cloud Computing for Healthcare Cybersecurity
    T. Thilagam, R. Aruna, G. Manisha, D. Chitradevi, A. Prema
    Recent Advances in Computer Science and Communications, 2025
  • A HYBRID APPROACH FOR INTRUSION DETECTION AND PRE VENTION IN MOBILE AD HOC NETWORKS
    Journal of Theoretical and Applied Information Technology, 2025
  • Collaborative Health Intelligence: Federated Learning and the Future of AI- Driven Medical Care
    B. Yamini, Siva Subramanian R., T. Thilagam, Anish T. P.
    Enabling Collaborative Health Intelligence with Federated Learning, 2025
  • Next- Generation Medical Intelligence: Harnessing Federated Learning and Collaborative AI for Healthcare Innovation
    S. Anusha, J. Balachandar, J. Bibija, B. Yamini, T. Thilagam, et al.
    Enabling Collaborative Health Intelligence with Federated Learning, 2025
  • Neuro-Fuzzy Systems: A Study of Architectures, Applications, and Future Directions
    Siva Subramanian R, T.Veeramani, C.Lakshmipriya, T.Thilagam, D.Lekha, et al.
    Proceedings of 5th International Conference on Soft Computing for Security Applications Icscsa 2025, 2025
  • Prediction and Comparison of ML Algorithm for Heart Disease
    G. Belshia Jebamalar, J.A. Adlin Layola, J. Rajalakshmi, T. Thilagam, M. Kausthuban, et al.
    Communications in Computer and Information Science, 2025
  • Enhancing swimming pool hygiene: A robotic approach to debris removal and water quality monitoring
    Hemalatha Senthilmahesh, Kiran Mayee Adavala, Thilagam Thangamariappan, Pullela S. V. V. S. R. Kumar, Ramesh Tumaati, et al.
    Asian Journal of Water Environment and Pollution, 2025
  • Green Data Centers: Advancing Sustainability in the Digital Era
    J. Elavarasi, G. Amudha, S.N. Ananthi, T. Thilagam, B. Saratha, et al.
    Proceedings of 5th International Conference on Trends in Material Science and Inventive Materials Ictmim 2025, 2025
  • Blockchain for pharmaceutical data management and quantum computing innovations
    Harikrishna Bommala, J. Raja, P. Latha, T. Thilagam, P. Valarmathi, et al.
    AI Powered Advances in Pharmacology, 2024
  • IMPROVING QUALITY OF SERVICE IN MOBILE ADHOC NETWORK BY DOING MISSING PACKET COLLECTION DUE TO BUFFER OVERFLOW WITH DIVIDE AND CONQUER STRATEGY
    Journal of Theoretical and Applied Information Technology, 2024
  • A Review on the Effectiveness of Deep Learning Algorithms for Pedestrian Detection
    Arumai Shiney. S, T. Thilagam, Manisha. G, Ananthi S N
    2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024
  • DrowsiGuard: Machine Learning-Based Driver Drowsiness Detection System for Enhanced Road Safety
    S. Gunanandhini, T. Thilagam, G. Manisha, S.N. Ananthi, G. Belshia Jebamalar
    2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024
  • Effective Street View Traffic Sign Detection and Recognition Using Deep Learning
    T. Thilagam, S. Gunanandhini, G. Belshia Jebamalar, G. Manisha, S. N. Ananthi
    Lecture Notes in Networks and Systems, 2024
  • Exploring the Experimental Possibilities of an Intelligent Blood Pressure Prediction Scheme using IoT enabled Machine Learning Principles
    T. Thilagam, S. Rajarajeswari, D Shobana, S. Ramkumar, M. Bharathi, et al.
    2024 4th International Conference on Intelligent Technologies Conit 2024, 2024
  • Medicinal Plant Identification Using CNN and Pytorch Lightning
    T. Thilagam, Anees Fathima M, Varsha V, Janani P, Priyadarshini A, et al.
    2024 International Conference on Smart Technologies for Sustainable Development Goals Icstsdg 2024, 2024
  • Neural Networks for Fault diagnosis in Electrical Machine
    R. Vinston Raja, J. Raja, Sreenivasulu Gogula, Atul Katiyar, T. Thilagam, et al.
    2024 Asian Conference on Intelligent Technologies Acoit 2024, 2024
  • A Robust Development of Calorie Prediction Methodology based on Artificial Intelligence Assisted Machine Learning Model
    G Naga Venkata RamaKrishna, S Sreelakshmi, Meenakshi Diwakar, S. Ramkumar, T Vinithra Banu, et al.
    2024 4th International Conference on Intelligent Technologies Conit 2024, 2024
  • LM-GA: A Novel IDS with AES and Machine Learning Architecture for Enhanced Cloud Storage Security
    Thilagam T, Aruna R
    Journal of Machine and Computing, 2023
  • Intrusion detection for network based cloud computing by custom RC-NN and optimization
    T. Thilagam, R. Aruna
    ICT Express, 2021
  • A Review on the Effectiveness of Machine Learning and Deep Learning Algorithms for Cyber Security
    R. Geetha, T. Thilagam
    Archives of Computational Methods in Engineering, 2021
  • Tamilian Cryptography: An Efficient Hybrid Symmetric Key Encryption Algorithm
    R. Geetha, T. Padmavathy, T. Thilagam, A. Lallithasree
    Wireless Personal Communications, 2020
  • A survey on security and privacy issues in cloud computing
    International Journal of Engineering and Technology Uae, 2018

RECENT SCHOLAR PUBLICATIONS

  • Machine Learning Approaches to Intrusion Detection in Cloud Computing for Healthcare Cybersecurity
    T Thilagam, R Aruna, G Manisha, D Chitradevi, A Prema
    Recent Advances in Computer Science and Communications 19 (4), E26662558350946 , 2026
    2026
  • AI and the Evolution of Human Communication: Transforming Interaction, Expression, and Connection in the Digital Age
    CS Sasikala, R Vinoth, T Thilagam, G Premalatha, G Manisha, MG Dinesh
    Impacts of AI on Human Expression and Relationship Building, 1-24 , 2026
    2026
  • AI, Sustainability, and Human Well-Being in Logistics Employment: Transforming Work, Efficiency, and Responsible Growth
    S Anbu, T Thilagam, G Manisha, P Jayabharathi, R Vinoth, MG Dinesh
    Impacts of AI on Employment and Skills in Logistics, 127-154 , 2026
    2026
  • Integrating Generative AI, Blockchain, and Smart Health Technologies for Intelligent Clinical Decision Support
    F Sammy, P Gajalakshmi, R Veerasundari, T Thilagam, LAA Gracious
    Responsible Analytics for Superior Health Quality Outcomes, 241-268 , 2026
    2026
  • Optimizing Production Through Sensors, Data Analytics, and Real-Time Information Flow
    KV Guru, B Mythili, T Thilagam, B Yuvasri, L Dharani, MG Dinesh
    Navigating Human-Machine Collaboration in Smart Factories, 279-296 , 2026
    2026
  • Key Drivers of Change in Industry 4.0: AI, IoT, Robotics, and Big Data
    V Rekha, TP Anish, T Thilagam, B Yamini, V Nivaskumar
    Navigating Human-Machine Collaboration in Smart Factories, 261-278 , 2026
    2026
  • Next-Generation Medical Intelligence: Harnessing Federated Learning and Collaborative AI for Healthcare Innovation
    S Anusha, J Balachandar, J Bibija, B Yamini, T Thilagam, AG LA
    Enabling Collaborative Health Intelligence With Federated Learning, 271-292 , 2026
    2026
  • Collaborative Health Intelligence: Federated Learning and the Future of AI-Driven Medical Care
    B Yamini, T Thilagam
    Enabling Collaborative Health Intelligence With Federated Learning, 89-110 , 2026
    2026
  • Internet of Things (IoT) in Urban Development: Applications, Challenges, and Future Research Directions
    B Maheswari, S Subha, T Thilagam
    Post-Quantum Cryptography and IoT Communications for Sustainable Urban … , 2026
    2026
  • Machine Learning for a Smarter Food Industry: Trends, Challenges, and Innovations
    M Anita, NS Chandra, N Pavithra, K Bhavani, P Aparna, T Thilagam
    AI Innovations for Improving the Food Industry, 69-96 , 2026
    2026
  • Harnessing Deep Learning for a Smarter and Sustainable Food Industry
    AN Vinodhini, B Yamini, A Revathi, R Kennady, T Thilagam, B Maheswari, ...
    AI Innovations for Improving the Food Industry, 97-124 , 2026
    2026
  • Machine Learning and Computational Intelligence for Smart Healthcare: Advancing Diagnosis and Treatment
    R Asha, J Sangeetha, A Adaikkammai, T Thilagam, P Aparna
    Applied AI and Computational Intelligence in Diagnostics and Decision-Making … , 2026
    2026
    Citations: 2
  • Transforming Education with NLP and Machine Learning: Innovations, Applications, and Future Prospects
    RS Subramanian, M Swetha, K Krishnaveni, T Thilagam, K Saranya, ...
    Educational Applications of Natural Language Processing, Chatbots, and AI … , 2026
    2026
    Citations: 3
  • Artificial Intelligence in Personalized Education: Revolutionizing Learning Paths and Student Engagement
    SD Dhivya, R Balakrishna, TSB Priya, T Thilagam, V Sathya, ...
    AI, Personalization, Equity, and the Future of Learning, 453-468 , 2026
    2026
    Citations: 2
  • NLP and Machine Learning Innovations in Education: Transforming Learning and Personalization
    KS Priyadharshini, B Yamini, TP Anish, T Thilagam, A Adaikkammai
    Educational Applications of Natural Language Processing, Chatbots, and AI … , 2026
    2026
  • The role of artificial intelligence in transforming supply chain management
    P Suganya, SR Siva, SN Ananthi, T Thilagam, J Elavarasi, GLA Anto, ...
    Transformative Impact of AI in Supply Chain Management, 271-294 , 2026
    2026
    Citations: 4
  • A Framework for Enhancing Transparency and Security in Telehealth Record Access Using Dual-One-Time Passwords.
    S Hemalatha, T Thilagam, SLK Vinti, BU Barathi, BY Supriya, ...
    International Journal of Safety & Security Engineering 15 (11) , 2025
    2025
  • Neuro-Fuzzy Systems: A Study of Architectures, Applications, and Future Directions
    T Veeramani, C Lakshmipriya, T Thilagam, D Lekha, K Sudha
    2025 5th International Conference on Soft Computing for Security … , 2025
    2025
    Citations: 1
  • Green data centers: advancing sustainability in the digital era
    J Elavarasi, G Amudha, SN Ananthi, T Thilagam, B Saratha
    2025 5th International Conference on Trends in Material Science and … , 2025
    2025
    Citations: 4
  • A HYBRID APPROACH FOR INTRUSION DETECTION AND PRE VENTION IN MOBILE AD HOC NETWORKS
    S Hemalatha, S Shalini, PS KUMAR, R SRINIVAS, T Thilagam, ...
    Journal of Theoretical and Applied Information Technology 15, 1128-44 , 2025
    2025
    Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

  • A Review on the Effectiveness of Machine Learning and Deep Learning Algorithms for Cyber Security: R. Geetha, T. Thilagam
    R Geetha, T Thilagam
    Archives of Computational Methods in Engineering 28 (4), 2861-2879 , 2021
    2021
    Citations: 181
  • Intrusion detection for network based cloud computing by custom RC-NN and optimization
    T Thilagam, R Aruna
    ICT Express 7 (4), 512-520 , 2021
    2021
    Citations: 102
  • Tamilian cryptography: an efficient hybrid symmetric key encryption algorithm
    R Geetha, T Padmavathy, T Thilagam, A Lallithasree
    Wireless Personal Communications 112 (1), 21-36 , 2020
    2020
    Citations: 25
  • LM-GA: a novel IDS with AES and machine learning architecture for enhanced cloud storage security
    T Thilagam, R Aruna
    Journal of Machine and Computing 3 (2), 69-79 , 2023
    2023
    Citations: 5
  • Intrusion detection for network based cloud computing by custom RC-NN and optimization. ICT Express, 7 (4), 512–520
    T Thilagam, R Aruna
    2021
    Citations: 5
  • A Survey on Security and Privacy Issues in Cloud Computing
    CA T. Thilagam1* , K. Arthi2
    International Journal of Engineering & Technology 7 (2.4) , 2018
    2018
    Citations: 5
  • The role of artificial intelligence in transforming supply chain management
    P Suganya, SR Siva, SN Ananthi, T Thilagam, J Elavarasi, GLA Anto, ...
    Transformative Impact of AI in Supply Chain Management, 271-294 , 2026
    2026
    Citations: 4
  • Green data centers: advancing sustainability in the digital era
    J Elavarasi, G Amudha, SN Ananthi, T Thilagam, B Saratha
    2025 5th International Conference on Trends in Material Science and … , 2025
    2025
    Citations: 4
  • Exploring the Experimental Possibilities of an Intelligent Blood Pressure Prediction Scheme using IoT enabled Machine Learning Principles
    T Thilagam, S Rajarajeswari, D Shobana, S Ramkumar, M Bharathi, ...
    2024 4th International Conference on Intelligent Technologies (CONIT), 1-6 , 2024
    2024
    Citations: 4
  • Transforming Education with NLP and Machine Learning: Innovations, Applications, and Future Prospects
    RS Subramanian, M Swetha, K Krishnaveni, T Thilagam, K Saranya, ...
    Educational Applications of Natural Language Processing, Chatbots, and AI … , 2026
    2026
    Citations: 3
  • Advancing Sustainable Development Through Green Economics
    K Balasubramanian, A Adaikkammai, T Thilagam, R Vinoth, V Sathya
    AI Methods for Environmental Protection and Resource Conservation, 47-82 , 2025
    2025
    Citations: 3
  • A Robust Development of Calorie Prediction Methodology based on Artificial Intelligence Assisted Machine Learning Model
    GNV RamaKrishna, S Sreelakshmi, M Diwakar, S Ramkumar, TV Banu, ...
    2024 4th International Conference on Intelligent Technologies (CONIT), 1-6 , 2024
    2024
    Citations: 3
  • Prediction and Comparison of ML Algorithm for Heart Disease
    G Belshia Jebamalar, JA Adlin Layola, J Rajalakshmi, T Thilagam, ...
    International Conference on Advances in Artificial Intelligence and Machine … , 2023
    2023
    Citations: 3
  • Machine Learning and Computational Intelligence for Smart Healthcare: Advancing Diagnosis and Treatment
    R Asha, J Sangeetha, A Adaikkammai, T Thilagam, P Aparna
    Applied AI and Computational Intelligence in Diagnostics and Decision-Making … , 2026
    2026
    Citations: 2
  • Artificial Intelligence in Personalized Education: Revolutionizing Learning Paths and Student Engagement
    SD Dhivya, R Balakrishna, TSB Priya, T Thilagam, V Sathya, ...
    AI, Personalization, Equity, and the Future of Learning, 453-468 , 2026
    2026
    Citations: 2
  • A HYBRID APPROACH FOR INTRUSION DETECTION AND PRE VENTION IN MOBILE AD HOC NETWORKS
    S Hemalatha, S Shalini, PS KUMAR, R SRINIVAS, T Thilagam, ...
    Journal of Theoretical and Applied Information Technology 15, 1128-44 , 2025
    2025
    Citations: 2
  • Blockchain for Pharmaceutical Data Management and Quantum Computing Innovations
    H Bommala, J Raja, P Latha, T Thilagam, P Valarmathi, M Sudhakar
    AI-Powered Advances in Pharmacology, 201-234 , 2025
    2025
    Citations: 2
  • Neuro-Fuzzy Systems: A Study of Architectures, Applications, and Future Directions
    T Veeramani, C Lakshmipriya, T Thilagam, D Lekha, K Sudha
    2025 5th International Conference on Soft Computing for Security … , 2025
    2025
    Citations: 1
  • The Role of Risk Management in Modern Business and Technology
    S Nandhini, B Yamini, G Anurekha, T Thilagam, PJB Pajila
    AI Methods for Environmental Protection and Resource Conservation, 217-244 , 2025
    2025
    Citations: 1
  • Effective Street View Traffic Sign Detection and Recognition Using Deep Learning
    T Thilagam, S Gunanandhini, G Belshia Jebamalar, G Manisha, ...
    International Conference on Innovations in Data Analytics, 297-312 , 2023
    2023
    Citations: 1