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Mr. T RAGHUNATHAN

Mr. T RAGHUNATHAN

M.E.,(Ph.D)

Assistant Professor (Sr.Gr.)

Artificial Intelligence & Data Science
AICTE ID: 1-747153335
raghunathan.t@drngpit.ac.in
ORCID Scopus LinkedIn Vidwan

Biography

Academic professional with a solid educational background and a passion for teaching. Completed Undergraduate studies at Maharaja Engineering College and Postgraduate degree at Anna University in Trichy. Currently, doing doctoral research at Anna University in Chennai. With Eleven years of teaching experience under the belt, brings a wealth of knowledge and expertise to your students, enriching their learning journey with your dedication and commitment to education.

Academic Credentials

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Degree Specialization Institute University Year of Passing
M.E. Computer Science and Engineering University College of Engineering (BIT Campus) Trichy Anna University Chennai 2014
B.Tech. Information Technology Maharaja Engineering College , Coimbatore Anna University Chennai 2009

Academic & Professional Experience

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Experience / Role Type Organization Duration Total
Assistant Professor Teaching Dr.N.G.P. Institute of Technology Jun 2024 - Present 2 Years 1 Month
Assistant Professor Teaching Sri Krishna College of Technology Jun 2019 - April 2024 4 years 10 Months
Assistant Professor Teaching Arjun College of Technology Dec 2017 - May 2019 1 year 5 Months
Assistant Professor Teaching PSV College of Engineering and Technology Jun 2014 - Nov 2017 3 Years 4 Months

Areas of Expertise

Wireless Sensor Network and Cloud Computing Machine Learning

Departmental Roles

Lab Incharge Class Advisor Placement In-Charge Association In-Charge

Journal Publications

  1. U Abinaya, S Anitha Devi, B Haritha and T Raghunathan. Noval Approach For ChronicKidney Disease Using Machine Learning Methodology ICCCEBS 2021. 1916 (2021)
  2. G. Sandhya, T. Raghunathan, E. Saranya, C. Kalpana, B. Dhanalakshmi. (2020). A GanBased X-Ray Model for Detecting Objects using Convolution Neural Networks. International Journal of Advanced Science and Technology, 29(05), 5337 – 5344 ISSN:2005-4238.
  3. M.Manikandan, T.Raghunathan, M.Sundarrajan, J.Akshya. Resource Allocation Assisted by Cloud Computing in Cyber-Physical System (CPS). International Journal of Recent Technology and Engineering (IJRTE). Volume-8, Issue-1,1287-1290. ISSN: 2277-3878.
  4. Sri Sowharan P K , Ukesh R , Vasanth M , Raghunathan T Integrating Iot With Ai-Enabled Wireless Sensor Networks For Landslide Monitoring And Early Warning Systems. Migration Letters, Volume: 21, No: S7 (2024), pp. 956-966, ISSN: 1741-8984 (Print) ISSN: 1741-8992 (Online)

National/International Conferences

  1. Selvaganesan, C., Manisha, P. T., Peter, S. S., Raghunathan, T., & Muralidharan, V (2025,March). Detecting and Refining Misinformation Using Domain-Adversarial Graph Neural Network:A Hybrid Method. In 2025 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI) (pp. 1-7). IEEE.
  2. Amutha, S., Raj, R. R. A., Saranya, S., Raghunathan, T., Choudhry, M. D., & Sundarrajan, M.(2025, September). Immersive Holographic Digital Twins for Predictive Maintenance in Robotics.In 2025 5th International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT) (pp. 1-6). IEEE.
  3. Shoba, B., Raghunathan, T., Peter, S. S., Sundarrajan, M., & Choudhry, M. D. (2025, January). Integrating Instruction-based Learning with Bidirectional LSTM for Autonomous Vehicle Pedestrian Detection. In 2025 International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI) (pp. 273-279). IEEE.
  4. Raghunathan, T., Mishra, A., & Mahur, A. K. (2024, March). Multi-modal AI/ML integration for precision Glaucoma detection: a comprehensive analysis using optical coherence tomography, fundus imaging, RNFL, and vessel density. In 2024 2nd International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA) (pp. 1-7). IEEE
  5. Janakiraman, S., Deva Priya, M., Christy Jeba Malar, A., Padmavathi, S., & Raghunathan, T. (2023, April). Iterated shape-bias graph cut-based segmentation for detecting cervical cancer from pap smear cells. In International Conference on IoT, Intelligent Computing and Security: Select Proceedings of IICS 2021 (pp. 355-365). Singapore: Springer Nature Singapore.