Name: Dr. A. Martin Designation: Assistant Professor Phone: +91-9500900380 Email:martin@cutn.ac.in
Biographic Sketch:
Dr. A. Martin Aruldoss is an Assistant Professor in the Department of Computer Science, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India. He has over 20 years of extensive experience in teaching, research, and academic administration. His academic career reflects a strong commitment to excellence in higher education, with significant contributions to both teaching and interdisciplinary research. His areas of expertise include Banking Technology, Business Intelligence, Data Science, Big Data Analytics, Explainable Artificial Intelligence (XAI), Artificial Emotional Intelligence, and Machine Learning.
Dr. Martin actively mentors postgraduate students and supervises Ph.D. scholars, fostering a research-oriented academic environment. He has published extensively in high-impact international journals from leading publishers such as IEEE, Elsevier, Springer, Emerald, and Inderscience. His notable works appear in journals like IEEE Transactions on Evolutionary Computation, Expert Systems with Applications, and International Journal of Information Management. In addition, he has authored two textbooks and contributed to several international book chapters.
His research contributions have gained global recognition, particularly his work on the “Qualitative Bankruptcy Dataset,” which has been acknowledged by the Center for Machine Learning and Intelligent Systems, University of California, Irvine, USA. His academic influence is evident through more than 2000 citations, an h-index of 18, and an i10-index of 21, along with significant Scopus citations.
Dr. Martin has successfully completed funded research projects, including a Tamil Nadu State Council for Science and Technology-supported project focused on developing a mobile application for fisherwomen and its subsequent enhancement funded by the Central University of Tamil Nadu. He has also secured approximately ₹1.75 lakhs from AICTE and the University for organizing workshops and Faculty Development Programmes (FDPs) on emerging technologies.
In addition to his academic contributions, he has organized outreach and career guidance programmes such as Zenith, DREAMS, and “Sikarathi Nokki.” He is also a contributor to a registered design titled “Mannequin for Smart Jewel Display” (Design No. 392758-001, 2023). He holds EMC2 Data Science and Big Data Analytics and Oracle Java certifications and has received IBM Faculty Mentor recognition for “The Great Mind Challenge.”
Research Highlights :
Interdisciplinary research in Computer Science with a focus on Banking Technology, Business Intelligence, Data Science, and Artificial Intelligence.
Expertise in emerging areas such as Explainable AI (XAI), Artificial Emotional Intelligence, and Big Data Analytics.
Published in high-impact international journals including IEEE, Elsevier, Springer, Emerald, and Inderscience.
Authored 2 textbooks and contributed to 9 international book chapters.
Published 48 journal articles (Web of Science, Scopus, UGC, and refereed journals).
Presented 67 research papers in national and international conferences (36 international, 31 national).
Recognized by the Center for Machine Learning and Intelligent Systems, University of California, Irvine (USA) for the Qualitative Bankruptcy Dataset.
Completed funded projects supported by Tamil Nadu State Council for Science and Technology and Central University of Tamil Nadu.
Secured funding for FDPs and workshops from AICTE and CUTN (₹1.75 lakhs).
Contributor to a registered design: “Mannequin for Smart Jewel Display” (Design No. 392758-001, 2023).
Recent Publications :
RECENT PUBLICATIONS
1. Journal Publications
Laboso, P., Aruldoss, M., Thiyagarajan, P., Lakshmi, T. M., & Wynn, M. (2026). Library systems and digital-rights management: Towards a blockchain-based solution for enhanced privacy and security. Information, 17(2), 137.
Kumar, H., Aruldoss, M., & Wynn, M. (2025). Cross-modal attention fusion: A deep learning and affective computing model for emotion recognition. Multimodal Technologies and Interaction, 9(12), 116.
Kumar, H., & Aruldoss, M. (2025). Advanced optimal cross-modal fusion mechanism for audio-video based emotion recognition. Informatica, 49(12), 61–76.
Kumar, H., & Aruldoss, M. (2025). Gated cross-modal fusion mechanism for audio-video-based emotion recognition. Engineering, Technology and Applied Science Research, 15(2), 20835–20841.
Arulprakash, E., & Martin, A. (2024). An object-oriented neural representation and its implication towards explainable AI. International Journal of Information Technology, 16(5), 1303–1318.
Kumar, H., & Martin, A. (2023). Artificial emotional intelligence: Conventional and deep learning approach. Expert Systems with Applications.
Arulprakash, E., Martin, A., & Lakshmi, T. M. (2022). A study on indirect performance parameters of object detection. SN Computer Science, 3(5), 386.
Arulprakash, E., & Aruldoss, M. (2022). A study on generic object detection with emphasis on future research directions. Journal of King Saud University – Computer and Information Sciences, 34(9), 7347–7365.
2. Conference Publications
Subanesh, A., Aruldoss, M., & Suresh Joseph, K. (2026). Food recommendation system using content-based and collaborative filtering. In Proceedings of the International Conference on Advanced Computing (ICAC-2026), Bharathiar University, India.
Suman, S. N., Punitha Devi, C., & Martin, A. (2026). Personalization of banking using machine learning. In Proceedings of ICAC-2026, Bharathiar University, India.
Asker, J. M., Ananda Krishna, M., Subanesh, A., & Martin, A. (2025). Enhancing video streaming recommendations using GenAI and XAI. In Proceedings of ICCSAM 2025, India.
Mathumidha, S., Martin, A., & Himanshu Kumar. (2025). Revolutionizing fashion using generative AI. In Proceedings of MRIET 2025, India.
Catherine Lemoria, Miranda Lakshmi, T., & Martin, A. (2025). Android malware detection using deep learning. In Proceedings of CIMA 2025, India.
Chandu, N., Kumar, H., & Martin, A. (2024). Encrypted traffic detection using statistical methods. In Proceedings of ICCT-2024, India.
Hareesh, M., Himanshu, K., & Martin, A. (2024). Credit card fraud detection using machine learning. In Proceedings of ICET-2024, India.
3. Books (2024)
Arulprakash, E., & Aruldoss, M. (2024). Enhancing explainability of neural network. LAP Lambert Academic Publishing.
4. Book Chapters
Thamarai Selvan, R., Kannan, S., Suman, S. N., & Martin, A. (2025). Classical and post-quantum cryptography: A study on RSA, CRYSTALS-Kyber and HQC. In K. R. Kishor & D. S. Nair (Eds.), Facets of some modern applications of mathematics (pp. 113–123). Department of Mathematics, D. B. Pampa College, Parumala. ISBN: 978-81-993189-3-9
Kumar, H., Martin, A., Wynn, M., & Lakshmi, M. (2025). Research challenges in deep generative models for healthcare and medical applications. In Advances in deep generative models for healthcare and medical applications (pp. 251–271). CRC Press.
Aruldoss, M., Travis, M. L., & Venkatasamy, P. V. (2024). Identification of user preference using human–computer interaction technologies and design of customized reporting for business analytics using ranking consistency index. In R. Rawat, R. K. Chakrawarti, S. K. Sarangi, P. Vyas, M. S. Alamanda, K. Srividya, & K. S. Sankaran (Eds.), Conversational artificial intelligence. John Wiley & Sons. https://doi.org/10.1002/9781394200801.ch9
5. Design / Intellectual Property
Aruldoss, M., et al. (2023). Mannequin for smart jewel display (Design No. 392758-001). Registered under the Designs Act, Government of India.
