Assistant Professor at KPR Institute of Engineering and Technology, India
Dr. Kothai Ganesan is an Assistant Professor in Computer Science and Engineering (Artificial Intelligence and Machine Learning) at KPR Institute of Engineering and Technology. She holds a Bachelor’s degree and Master’s degree in Engineering from Anna University and a Ph.D. from SRM Institute of Science and Technology, with research focusing on Intelligent Transport Systems, traffic prediction, and secure data transmission. Her published work includes studies in vehicular networks, traffic congestion, and security protocols, alongside ongoing research in medical imaging, AI-enhanced diagnostic tools, and image processing. A recognized mentor and department coordinator, Dr. Kothai integrates modern tools like Docker into her curriculum, advancing industry-aligned education. Her contributions have been acknowledged in journals, conferences, and professional memberships, including IEEE Computational Intelligence Society.
Publication Profile :
Scopus
🎓 Educational Background :
Dr. Kothai Ganesan is an accomplished Assistant Professor in the Computer Science and Engineering (Artificial Intelligence and Machine Learning) department at KPR Institute of Engineering and Technology. Her academic journey began with a Bachelor’s degree in Computer Science and Engineering from Anna University (2012–2016), followed by a Master’s in the same field, earned with first-class distinction at Anna University (2016–2018). Pursuing her passion for advanced research, Dr. Ganesan completed her Ph.D. in November 2023 at SRM Institute of Science and Technology, where her research centered on Intelligent Transport Systems, with a particular focus on traffic prediction, congestion avoidance, and secure data transmission, all aimed at improving urban mobility.
💼 Professional Experience :
Professionally, Dr. Ganesan has contributed significantly to the field of AI-driven transport systems, publishing extensively on vehicular ad hoc networks (VANETs) and innovative machine learning techniques. Her research outputs include collision prediction and secure communication protocols, enhancing safety in smart cities. She has also expanded her focus into medical AI, exploring Alzheimer’s diagnosis, pediatric epilepsy recognition, and cancer detection using optimized learning models. Alongside her research, Dr. Ganesan is an active mentor, guiding student-led projects in machine learning and artificial intelligence. As a dedicated faculty member, she serves as the IQAC Coordinator, Exam Cell Coordinator, Autonomous Coordinator, and R&D Coordinator, furthering the program’s reputation through academic rigor and practical industry integration. 📚💡
Her current research interests are broad, covering deep learning, machine learning, computer vision, and natural language processing. Dr. Ganesan’s work has gained her recognition in prestigious journals and conferences, and she actively participates in the IEEE Computational Intelligence Society as a Faculty Advisor. As a reviewer for leading journals, she contributes her expertise to the scholarly community. Dr. Ganesan’s unique blend of academic insight, mentorship, and professional innovation showcases her commitment to advancing AI and machine learning for impactful, real-world applications. 🌟
📝 Publication Top Notes :
- Ganesan, K., & [Co-authors, if applicable]. (2021). A New Hybrid Deep Learning Algorithm for Prediction of Wide Traffic Congestion in Smart Cities. Wireless Communications and Mobile Computing, 2021, Article ID 5583874, 13 pages. https://doi.org/10.1155/2021/5583874.
- Ganesan, K., & [Co-authors, if applicable]. (2020). Performance Analysis of Stationary and Deterministic AODV Model. International Journal of Interactive Mobile Technologies (IJIM), 14(17), 33–44.
- Ganesan, K., & [Co-authors, if applicable]. (2022). IoT-Based Automatic SOP Adoption in Pandemic Scenario. International Journal of High Technology Letters, June 2022.
- Ganesan, K., & [Co-authors, if applicable]. (2024). A Hybrid CNN-GRU based Intrusion Detection System for Secure Communication in Vehicular Adhoc Network. Information Security Journal, Taylor & Francis, June 2024.