Mr. Ehab Elhosary | Vision and Language | Research Excellence Award Published on 10/04/202610/04/2026 by Computer Vision Awards After Completing the Registration Process, your Biography will be displayed here. Register by using your Entry ID: 8440 Register Here
Nisharg Nargund | Document Image Analysis | Young Researcher Award Published on 27/01/202627/01/2026 by Computer Vision Awards Mr. Nisharg Nargund | Document Image Analysis | Young Researcher Award Undergrad Researcher | Kalinga Institute of Industrial Technology | India Mr. Nisharg Nargund is an emerging researcher in artificial intelligence and machine learning at the Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, India. His research focuses on large language models, retrieval-augmented generation, transformer architectures, and multi-agent AI systems. He has authored Ten scholarly and professional publications, with 2 Scopus-indexed documents receiving 19 citations and an h-index of 1. His work has been presented at leading international conferences, earning Best Paper and Best Poster awards. Through academic collaborations, industry internships, and open-source projects, his research contributes to scalable, ethical, and societally impactful AI solutions in education, language technology, and industry. Citation Metrics (Scopus) 30 20 10 0 Citations 19 Documents 2 h-index 1 🟦 Citations 🟥 Documents 🟩 h-index View Scopus Profile View Google Scholar Profile Featured Publications Deep learning in Industry 4.0: Transforming manufacturing through data-driven innovation. – In Distributed Computing and Intelligent Technology: 20th International Conference, ICDCIT 2024, Bhubaneswar, India, January 17–20, 2024, Proceedings. (2024). Cited By : 31 Conversational text extraction with large language models using retrieval-augmented systems. – In Proceedings of the 6th International Conference on Computational Intelligence and Networks . (2025). Cited By : 5 Neural orchestration for multi-agent systems: A deep learning framework for optimal agent selection in multi-domain task environments. -arXiv. (2025). Cited By : 4 Optimization of latent-space compression using game-theoretic techniques for transformer-based vector search. – arXiv. (2025). Innovative fusion of LSTM and Bi-GRU networks for enhanced hate speech detection in social media. – International Research Journal of Modernization in Engineering Technology and Science (IRJMETS). (2024).
Mr. Nisharg Nargund is an emerging researcher in artificial intelligence and machine learning at the Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, India. His research focuses on large language models, retrieval-augmented generation, transformer architectures, and multi-agent AI systems. He has authored Ten scholarly and professional publications, with 2 Scopus-indexed documents receiving 19 citations and an h-index of 1. His work has been presented at leading international conferences, earning Best Paper and Best Poster awards. Through academic collaborations, industry internships, and open-source projects, his research contributes to scalable, ethical, and societally impactful AI solutions in education, language technology, and industry. Citation Metrics (Scopus) 30 20 10 0 Citations 19 Documents 2 h-index 1 🟦 Citations 🟥 Documents 🟩 h-index View Scopus Profile View Google Scholar Profile Featured Publications Deep learning in Industry 4.0: Transforming manufacturing through data-driven innovation. – In Distributed Computing and Intelligent Technology: 20th International Conference, ICDCIT 2024, Bhubaneswar, India, January 17–20, 2024, Proceedings. (2024). Cited By : 31 Conversational text extraction with large language models using retrieval-augmented systems. – In Proceedings of the 6th International Conference on Computational Intelligence and Networks . (2025). Cited By : 5 Neural orchestration for multi-agent systems: A deep learning framework for optimal agent selection in multi-domain task environments. -arXiv. (2025). Cited By : 4 Optimization of latent-space compression using game-theoretic techniques for transformer-based vector search. – arXiv. (2025). Innovative fusion of LSTM and Bi-GRU networks for enhanced hate speech detection in social media. – International Research Journal of Modernization in Engineering Technology and Science (IRJMETS). (2024).