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Department of Artificial Intelligence & Data Science

Year: 2021

Establishment

(Ay 2025-2026): 988

Student Strength

Last 5 Years – 21

Higher Studies

Last 5 Years - 126

Total Number of NPTEL Courses Completed

Last 5 Years – 129
Patents - 5

Publications

Last 5 Years – 543

Internship -National

Established in 2021, the Department of Artificial Intelligence and Data Science at the undergraduate level stands as a forward-thinking center for academic and technical excellence, dedicated to shaping skilled professionals in the rapidly evolving domains of AI and data science. The department offers a contemporary curriculum that integrates theoretical foundations with practical, project-based learning, ensuring students gain hands-on experience with the latest tools and methodologies. Students benefit from state-of-the-art laboratories, experienced faculty, and industry partnerships that foster exposure to real-world challenges, research opportunities, and career-oriented events. Emphasizing an interdisciplinary approach, the department encourages innovation in areas such as machine learning, big data analytics, and ethical AI, while nurturing qualities like leadership, critical thinking, and social responsibility. Since its inception in 2021, the department has aimed to produce graduates who are technically adept, ethically grounded, and adaptable to the future needs of industry and society.

Vision

The vision of the Artificial Intelligence and Data Science (AI & DS) department is to establish itself as a leader in the field by driving innovation and preparing graduates who are industry-ready and socially responsible.

Mission

  • To provide quality education that integrates core principles of AI and Data Science with hands-on experience to develop industry-ready professionals.
  • To promote innovation and research by fostering collaborations with industry, academia, and interdisciplinary domains.
  • To instill ethical values and social responsibility to ensure the development of AI solutions that benefit society.

HOD

HOD

Karpagam Academy of Higher Educations Department of Artificial Intelligence, Data Science provides undergraduate students with a top-notch education. Important subjects like artificial intelligence (AI), data analytics, machine learning, deep learning, computer vision, natural language processing (NLP), data science, big data, and generative AI are all covered in our courses.

In modern labs and smart classrooms, students learn while practicing. Through projects, research, and internships, they also gain practical experience that strengthens their technical and collaboration abilities. Students are prepared for jobs in corporations, research, or perhaps launching their own businesses after graduation.

We train students to contribute to the development of technology in the future as well as to stay current with emerging technologies. Our mission is to develop professionals in data science and artificial intelligence who are capable, accountable, socially conscious and prepared to take on challenges wherever in the world.

Programme

Programmes

Faculty

Name Qualification Designation Email ID Profile
Dr. G . Anitha MCA., M.Phil., Ph.D. Associate Professor & Head anitha.g@kahedu.edu.in Click Here
Dr. R. Chennappan MCA, MSc(Phy)., M.Phil, SET Associate Professor chennappan.rajendran@kahedu.edu.in Click Here
Mrs. S. Senthilpriya MCA., M.Phil. (Ph.D) Assistant Professor senthilpriya.ssampathkumar@kahedu.edu.in Click Here
Dr. A. Hema Ambiha MCA., M.Phil. Ph.D Assistant Professor hemaambiha.aravindakshan@kahedu.edu.in Click Here
Mrs. P. Sathiyapriya MCA., M.Phil. (Ph.D) Assistant Professor sathiyapriya.palanisamy@kahedu.edu.in Click Here
Mr. H. Ramprasanth MCA., M.Phil. (Ph.D) Assistant Professor ramprasanth.haldorai@kahedu.edu.in Click Here
Mrs. A. Vinitha MCA., Assistant Professor vinitha.ashokan@kahedu.edu.in Click Here
Mr. G. Samprakash MCA., (Ph.D) Assistant Professor samprakash.gnanaprakasam@kahedu.edu.in Click Here
Mrs. N. Nithya M.Sc., M.Phil., B.Ed., Assistant Professor nithya.nagarajan@kahedu.edu.in Click Here
Ms. V. Kowsalya MCA., (Ph.D) Assistant Professor kowsalya.velmani@kahedu.edu.in Click Here
Ms. R. Sowmiya MCA., Assistant Professor sowmiya.raghavan@kahedu.edu.in Click Here
Ms. P. E. Anusree MCA., NET Assistant Professor anusree.gangadharan@kahedu.edu.in Click Here
Mrs. N. Uma maheshwari M.C.A., M.Phil., Assistant Professor umamaheswari.narayanan@kahedu.edu.in Click Here
Ms. R. K. Keerthana MCA., Assistant Professor keerthana.raju@kahedu.edu.in Click Here
Dr. V. Vadivu M.Sc. (IT)., M.Phil., Ph.D., Assistant Professor vadivu.vijayan@kahedu.edu.in Click Here
Ms. N. Shanmugalakshmi MCA., Assistant Professor shanmugalakshmi.neelamegam@kahedu.edu.in Click Here
Mrs. N. Krithika M.C.A., Assistant Professor krithika.nataraj@kahedu.edu.in Click Here
Dr. S. SenthilKumar MCA., M.Phil., Ph.D. Assistant Professor senthilkumar.seethapathy@kahedu.edu.in Click Here
Dr. P. Vijayakumar M.Sc., M.Phil., Ph.D., Assistant Professor vijayakumar.perumal@kahedu.edu.in Click Here

Publications

Paper Publications by the Faculty Members

Best Five Papers Faculty wise:

Dr. G . Anitha

  1. Yalini, S., & Anitha, G. (2025). Machine learning framework for accurate mental stress detection in university students using random forest classification. In Proceedings of the International Conference on Emerging Trends in Engineering & Applications (ICETEA 2025) (pp. 1–6). IEEE. https://doi.org/10.1109/ICETEA64585.2025.11099999
  2. Keerthana, S., & Anitha, G. (2025). A study on cardiovascular disease detection in diabetic patients. In Proceedings of the Eleventh International Conference on Biosignals, Images, and Instrumentation (ICBSII 2025) (pp. 41?). IEEE.https://doi.org/10.1109/ICBSII65145.2025.11013590
  3. Sabeena, K. R., & Anitha, G. (2025). Sales prediction using machine learning algorithms. In Applications (pp. 73). Taylor & Francis.https://doi.org/10.1201/9781003606659
  4. Rutravigneshwaran, P., Anitha, G., & Prathapchandran, K. (2024). Trust-based support vector regressive (TSVR) security mechanism to identify malicious nodes in the Internet of Battlefield Things (IoBT). International Journal of System Assurance Engineering and Management, 15(1), 287–299. https://doi.org/10.1007/s13198-022-01719-w
  5. Gnanaselvi, J., & Anitha, G. (2020). A survey on deep learning techniques. Strad Research, 7(8), 400–405.

Mrs. S. Senthilpriya

  1. Balaji, N., & Senthil Priya, S. S. (2025, May 15). Clickbait prediction through feature extraction and feature selection by examining attributes, social influence, content, and engagement. Journal of Neonatal Surgery, 14(24S), 273-284. https://www.jneonatalsurg.com/index.php/jns/article/view/5925

Dr. R. Chennappan

  1. Althaf Ali, A., Gunavathie, M. A., Srinivasan, V., Aruna, M., Chennappan, R., & Matheena, M. (2025). Securing electronic health records using blockchain-enabled federated learning for IoT-based smart healthcare. Clinical eHealth.https://doi.org/10.1016/j.ceh.2025.04.002
  2. Chennappan, R., & Mathumathi, E. (2025). Elevating software defect prediction performance through an optimized GA-DT and PSO-ACO hybrid approach. Journal of Harbin Institute of Technology (New Series), 32(3), 66-74.
  3. Sowmiya, N., & Chennappan, R. (2025). A new algorithm for deducing user search intensities from feedback sessions. In Applications of Mathematics in Science and Technology (1st ed.). CRC Press.
  4. Chennappan, R., Vinitha, A., Vinitha, S., & Gunasundari, R. (2025). Automated disaster monitoring through social media posts using whale optimization and ANN. In Advances in Computational Intelligence and Robotics: Innovations in Optimization and Machine Learning (pp. 277-300). IGI Global. https://doi.org/10.4018/979-8-3693-5231-1.ch011.
  5. Chennappan, R., Nandhakumar, S., & Palarimath, S. (2024). O-RAN in private network for digital health applications using Twofish encryption in the Internet of Things. In Smart healthcare and machine learning (pp. 149–164). Springer Nature Singapore.
  6. Chennappan, R., & Vidyaathulasiraman. (2023). An automated software failure prediction technique using hybrid machine learning algorithms. Journal of Engineering Research, 11(1), 100002.https://doi.org/10.1016/j.jer.2023.100002

Mrs. A. Hema Ambiha

  1. Muthupandi, T., & Hema, A. A. (2025). Bioinformatics of athletes to record the cardiovascular issues through using KNN algorithm. In Applications of Mathematics in Science and Technology (pp. 359-362). CRC Press.
  2. A. Hema Ambiha, R. P. (2024). Blockchain-driven encryption and dual authentication for secure healthcare data transmission in the cloud. Journal of Computational Analysis and Applications, 33(8), 4906-4917.
  3. Hema Ambiha. A and Athira. A, “Smart Agriculture Rice Leaf Disease Detection using Deep Learning Model,” 2024 International Conference on Emerging Research in Computational Science (ICERCS), Coimbatore, India, 2024, pp. 1-7, doi: 10.1109/ICERCS63125.2024.10895956.
  4. Ambiha, A. H., & Subithra, V. (2024, October). Predicting Sham Claims in Vehicle Insurance using Machine Learning Techniques. In 2024 2nd International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS) (pp. 673-681). IEEE.
  5. Ambiha, A. H., & Pragaladan, R. (2024). Enhancing healthcare data security in cloud environments with dual authentication and optimal key-tuned encryption. Journal Scientific and Technical Of Information Technologies, Mechanics and Optics, 155(3), 456.
  6. Ambiha, A. H., S, S. K., & Kokilamani, M. (2024). A Novel Development of Medical Technology and AI for Intelligent Healthcare. In Smart Healthcare and Machine Learning (pp. 249-267). Singapore: Springer Nature Singapore.
  7. Aravindakshan, H. A., & Rengasamy, P. (2024). Enhancing healthcare data security in cloud environments with dual authentication and optimal key-tuned encryption. Научно-технический вестник информационных технологий, механики и оптики, 24(3), 456-463.
  8. Karthikeyan, M. P., Krishnaveni, K., Revathi, T., & Ambiha, A. H. (2023). Hybrid Optimization Techniques for Data Privacy Preserving in the Metaverse Ecosystem. In Handbook of Research on AI-Based Technologies and Applications in the Era of the Metaverse (pp. 395-408). IGI Global.
  9. Hema Ambiha, A. Thiyagarajan, M., Rajamohanan, R., & Appu, M. (2024, March). Deep Residual Network for Effective Lung Cancer Detection on Computed Tomography Images. In 2024 IEEE International Conference on Contemporary Computing and Communications (InC4) (Vol. 1, pp. 1-6). IEEE.

Mrs. P. Sathiyapriya

    1. Vulture Optimization Algorithm Based Hierarchical Routing Strategy (Voa-Hrs) For Vehicular Ad Hoc Networks December-2023.
    2. Sepsis Prediction Using Machine Learning and Deep Learning Algorithms, 1 st International Conference on Multidisciplinary Research and Innovation – ICMRI, April -2023.

Books:

  1. Smart Sensor Networks and Internet of Things (IoT) The International Journals, – SKRGC Publication August 2025.
  2. An Introduction to ML, DL and Natural Language Processing, Leilani Katie Publication and Press August 2025.

Mrs. A. Vinitha

  1. Divani, N., & Vinitha, A. (2025). Machine learning-based detection of malicious URLs in Twitter. In Proceedings of the 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE. https://doi.org/10.1109/ICMLAS64557.2025.10968493.

Ms. R. Sowmiya

  1. S. Jayarathna, R. Sowmiya, G. Nallasivan, G. Sahaana, S. Ashok and R. Saravanakumar, “3D CT Liver Images Lesion Extraction and Classification for Using 3D-CNN with GLRLM,” 2025 International Conference on Advanced Computing Technologies (ICoACT), Sivalasi, India, 2025, pp. 1-5, doi: 10.1109/ICoACT63339.2025.11004788.

Ms. P. E. Anusree

  1. K. V and P. E. Anusree, “Stock Market Analysis and Forecasting Using Deep Learning,” 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS), Prawet, Thailand, 2025, pp. 87-95, doi: 10.1109/ICMLAS64557.2025.10968208.

Dr. S. SenthilKumar

  1. Senthil Kumar, J. Ramprasath, V. Kalpana, Manikandan Rajagopal, Maheswaran S, Rupesh Gupta, Integrating brain-inspired computation with big-data analytics for advanced diagnostics in neuroradiology, Neuroscience Informatics, Volume 5, Issue 2, 2025, 100202, ISSN 2772-5286, https://doi.org/10.1016/j.neuri.2025.100202. (https://www.sciencedirect.com/science/article/pii/S2772528625000172).

Events

Event Organised

  1. Association inauguration “AI TechIgnite” on 21.08.2025.
  2. Two Days Hands on Training on “Latest Innovations in Emerging Tools & Technologies powered by AI” on 07.08.2025 and 08.08.2025.
  3. Alumni Talk on “Full Stack Deployment with Micro Services” on 01.08.2025 by our alumni Mr.Vinoth Kumar G, 2023 Passed out MCA, Junior Software Engineer in Caliber Interconnects Pvt.Ltd, Coimbatore.
  4. Extension program on Digital Scam Awareness Program on 31.07.2025 along with 2 faculty members and 65 students at Seerapalayam, Coimbatore.
  5. Skill development programme on “Unlocking the Power of Blockchain Technologies in AI” on 14-07-2025.

Others

  1. Hackathon on AI and Cyber Security on 04.03.2026.
  2. Two Days AI – Powered Solution Expo-2K26 on 26.02.2026 & 27.02.2026
  3. One day program on “Orientation Programme on TNPSC, Banking, SSC, RRB” for the UG students on 27.02.2026.
  4. Two Days Hands on Training on “Latest Innovations in Advanced AI Technologies” for II B.Sc CS (AI & DS) Students  on 22.12.2025 and 23.12.2025.
  5. Faculty Development Program on “Sustainable Cities & Communities with the emerging trends of Artificial Intelligence & Machine Learning” from 17.12.2025 to 21.12.2025 Via hybrid mode for our computer science stream faculty members
  6. One-day Seminar on “Recent Innovations in AI powered by Realtime Applications Development” for II B.Sc. CS (AI&DS) students on 19.12.2025.
  7. One-day Seminar on “Recent Trends and Technologies in Realtime Projects” for III B.Sc. CS (AI&DS) students on 18.12.2025.
  8. To conduct a Skill Development Programme on “Future Forward-AI Tools Driving the Next Wave of Innovation” for II B.Sc., CS (AI&DS) students on 17.12.2025.
  9. Two Days Workshop on “Latest Innovations in AI Tools and Technology powered by OpenCV control” for III B.Sc. CS (AI & DS) students on 16.12.2025 and 17.12.2025.
  10. One-day Orientation Program on “Awareness on Government Examinations” for the I UG students on 11.12.2025.
  11. Association inauguration “AI TechIgnite” on 21.08.2025.
  12. Two Days Hands on Training on “Latest Innovations in Emerging Tools & Technologies powered by AI” on 07.08.2025 and 08.08.2025.
  13. Extension program on Digital Scam Awareness Program on 31.07.2025
  14. Alumni Talk on “Full Stack Deployment with Micro Services” on 01.08.2025 by our alumni Mr.Vinoth Kumar G, 2023 Passed out MCA, Junior Software Engineer in Caliber Interconnects Pvt.Ltd, Coimbatore.
  15. Extension program on Digital Scam Awareness Program on 31.07.2025 along with 2 faculty members and 65 students at Seerapalayam

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