Dr. KALAIVANAN K

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TNEA:2764 TNEA Counselling Code: 2764

Faculty Profile
Dr. KALAIVANAN K
Assistant Professor lll
Dr. KALAIVANAN K
Assistant Professor lll, INFORMATION TECHNOLOGY
Areas of Interests: Machine Learning, Deep Learning
Portfolios: Department Examcell Coordinator
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About me

My name is Dr. K. Kalaivanan Karuppannan, and I am working as an Assistant Professor in the Department of Information Technology with 13 years of teaching and research experience. I hold a Ph.D. in Machine Learning, M.Tech in Information Technology, and B.Tech in Information Technology. My research interests include machine learning, deep learning, water quality prediction, medical image analysis, and intelligent data-driven systems. I have published research papers in reputed international journals such as Abdominal Radiology, Expert Systems, Urban Water Journal, and Environmental Research Communications.In addition to research, I have strong teaching experience in core computer science subjects such as Data Structures and Algorithms, Design and Analysis of Algorithms, Computer Networks, Python Programming, Software Engineering, and Software Testing. I focus on outcome-based education, hands-on learning, and mentoring students in research and project work. I have also handled academic administrative roles, including Internal Examination Cell Coordinator and Department ISO Coordinator.

Professional Information
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  • Indian Society for Technical Education
  • 1) Kalaivanan, K., & Vellingiri, J. (2025). Accurate colorectal cancer detection using a random hinge exponential distribution coupled attention network on pathological images. Abdominal Radiology
  • 2) Vellingiri, J., Kalaivanan, K., Kaliraj, S., & Bai, F. J. J. S. (2024). AO-SVM: A machine learning model for predicting water quality in the Cauvery River. Environmental Research Communications
  • 3) Kalaivanan, K., & Vellingiri, J. (2024). A Grey Wolf Optimized-stacked ensemble approach for nitrate contamination prediction in Cauvery Delta. Korea Economic and Environmental Geology, 57, 329-342
  • 4) Kalaivanan, K., & Vellingiri, J. (2024). A hybrid machine learning approach for enhanced anomaly detection in drinking water quality. International Journal of Environmental Studies, 81(2), 661-674.
  • 5) Vellingiri, J., Kalaivanan, K., Gopinath, M. P., Gobinath, C., Subramaniam, P. R., & Rangarajan, S. (2023). Strategies for classifying water quality in the Cauvery River using a federated learning technique. International Journal of Cognitive Computing in Engineering, 4, 187-193.
  • 6) Kalaivanan, K., & Vellingiri, J. (2023). A metaheuristic optimization algorithm (Lion-BES-XGB) for water quality prediction. Urban Water Journal, 20(6), 751-762.
  • 7) Kalaivanan, K., & Vellingiri, J. (2023). Normalized Hellinger feature selection and soft margin boosting classification for water quality prediction. Expert Systems Journal, 41(5), e13221.
  • Introduction to Machine Learning-NPTEL
  • Ph.D.-Machine Learning @ Vellore Institute of Technology
  • M.Tech -Information Technology @ Bharathidasan University
  • B. Tech - Information Technology @ Anna University