Author

Sinu Nambiar

Department of Artificial Intelligence and Data Science Marathwada Mitra Mandal College of Engineering, Pune, Maharashtra, 411052, India

Published papers: 3
Citations: 0
Views: 309
Downloads: 24

Publications

3 papers

Open Access Research Article·pp. 1887–1895·Vol. 47, Issue 5-BMay 2026

Privacy-preserving machine learning techniques ensuring data confidentiality and model accuracy in federated learning environments

Sinu Nambiar, Manjusha Tatiya, Kajal Sanjay Diwate, Deepika Sharma, Samir N. Ajani, Yogesh Nagargoje

Published Online: 01 May 2026DOI: 10.47974/JIOS-2281

In this paper: Federated learning (FL) lets multiple people work together to train a model without storing private data in one place. This has a lot of promise for making AI more privacy-aware. However, FL is still...

Abstract References Full Text PDF (576 KB)Views: 83Downloads: 6Citations: 0

Open Access Research Article·pp. 1871–1878·Vol. 47, Issue 5-AMay 2026

Exploring quantum machine learning integrating quantum computing with AI for advanced predictive modeling and data analysis

Sinu Nambiar, Manjusha Tatiya, Pradnya S. Moon, Sagarkumar S. Badhiye, Vijaya Ravsaheb Khemnar

Published Online: 01 May 2026DOI: 10.47974/JIOS-2279

In this paper: The integration of quantum computing and artificial intelligence change the way of prediction modeling and data analysis field. This study looks at the basic ideas, design concepts, and mathematical e...

Abstract References Full Text PDF (627 KB)Views: 82Downloads: 8Citations: 0

Open Access Research Article·pp. 1681–1691·Vol. 28, Issue 5-AAug 2025

Design and implementation of quantum-resistant cryptographic algorithms in blockchain networks

Shyam Deshmukh, Sinu Nambiar, Pallavi Sachin Patil, Madhura Phatak, Bhavana Tiple, Aniket Prakashrao Munshi

Published Online: 30 Aug 2025DOI: 10.47974/JDMSC-2168

In this paper: Traditional cryptographic methods are in big danger from quantum computing, which could make blockchain networks less safe. This essay looks at how to make and use quantum-resistant encryption methods...

Abstract References Full Text PDF (727 KB)Views: 144Downloads: 10Citations: 0