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KOTEESWARAN S

Professor, Department of Computer Science and Engineering (AI and ML) · S.A. Engineering College (Autonomous)

https://researchid.co/koteeswaran
@saec.ac.in
63Scopus Publications
545Google Scholar Citations
14Google Scholar h-index
17Google Scholar i10-index

Research Interests

Artificial Intelligence, Data Science, Deep Learning, Internet of Things and Software Engineering.

Biography

Dr. S. Koteeswaran, B.Tech., M.E., Ph.D. currently working as Professor in the Department of Computer Science and Engineering (AI&ML), S.A. Engineering College, Chennai-600077, TamilNadu, India. He is having 15 years of teaching experience and published more than 50 research articles in various peer reviewed Journals. He is author for two text books and two edited books for Computer Science & Engineering Programme. His research interests include Artificial Intelligence, Machine Learning, Deep Learning, Big Data and Analytics and Internet of Things. He has presented several papers in conference proceedings. He is a reviewer for more than a dozen journals and also organized more than 25 various events such as National and International Conferences, Faculty Development Programs, Workshops, Seminars, National Level Paper Contests, Quiz programmes, 24 Hours IEEE Xtreme Programming Competition and 36 hours Hachathon. He is a Member of ACM, Member of IAEng, Global Member of ISOC.

Education

 Ph.D. (Computer Science and Engineering) Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Chennai, 2013.  M.E. (Software Engineering) Vel Tech Engineering College, Anna University, Chennai, 2009.  B.Tech. (Information Technology) Amrita Institute of Technology and Science, Anna University, Chennai, 2006.

Recent Scopus Publications

  1. A Sophisticated Onscreen Smart Framework for Predicting Diabetes in Remote Healthcare
    Diagnostics, 2026
  2. Manual and Automated Web-Based Diagnosis and Interpretation of Mammograms of Breast Cancer and Robust Analysis
    Communications in Computer and Information Science, 2026
  3. An efficient patient’s response predicting system using multi-scale dilated ensemble network framework with optimization strategy
    Scientific Reports, 2025
  4. IoT-based prediction model for aquaponic fish pond water quality using multiscale feature fusion with convolutional autoencoder and GRU networks
    Scientific Reports, 2025
  5. AI Innovations for Improving the Food Industry
    AI Innovations for Improving the Food Industry, 2025

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