Mr. Sandesh Aryal | Best Researcher Award

Mr. Sandesh Aryal | Best Researcher Award

National Institute of Technology Rourkela | India

Mr. Sandesh Aryal holds a B.Tech in Electronics and Communication Engineering from the National Institute of Technology Rourkela (2021-2025) and has rapidly emerged as a research innovator in the domain of deep-learning–based biomedical image analysis. His work focuses on the classification of white blood cells via attention-augmented convolutional networks. His standout publication, “AFMNet: Adaptive Feature Modulation Network for Classification of White Blood Cells”, was published in Biocybernetics and Biomedical Engineering, and leverages adaptive spatial–channel feature modulation to achieve state-of-the-art classification performance. (Citation data: the article is indexed on ScienceDirect and ResearchGate.) His research interest spans machine learning, computer vision, biomedical signal processing, and image-based disease diagnostics. During his internship at Nepal Telecom, he gained practical exposure to wireless, transmission and power systems, complementing his core computational skills. His scholarship-supported undergraduate tenure and leadership roles (such as captain of his institute’s volleyball team) reflect a combination of technical excellence and organisational ability. With a proven ability to translate deep learning methods into biomedical applications, Sandesh is poised to contribute significantly to the intersection of AI and healthcare diagnostics.

Profile : Orcid

Featured Publication

Aryal, S., Naik, S. K., Madarapu, S., & Ari, S. (2025). AFMNet: Adaptive feature modulation network for classification of white blood cells. Biocybernetics and Biomedical Engineering.

Assist. Prof. Dr. Fayzullo Nazarov | Best Researcher Award

Assist. Prof. Dr. Fayzullo Nazarov | Best Researcher Award

Samarkand State University | Uzbekistan

Dr. Fayzullo Nazarov is a distinguished researcher at Sharof Rashidov Samarkand State University, Uzbekistan, recognized for his contributions to artificial intelligence, data science, and computational optimization. With an h-index of 10, 28 publications, and 217 citations across 94 documents, his research demonstrates significant scholarly impact and growing recognition in the field. Dr. Nazarov earned his advanced degrees in computer science and applied mathematics, where he developed a strong foundation in algorithmic modeling, neural networks, and machine learning applications. His academic and professional experience centers on the intelligent management of data systems, optimization of distribution mechanisms, and neural network ensemble methodologies. Dr. Nazarov’s recent works, including studies on effective distribution determination using neural network ensembles and machine learning-based data storage optimization, highlight his innovative approach to integrating AI with intelligent system design. He actively collaborates with international researchers to advance computational intelligence and smart data technologies. Throughout his career, Dr. Nazarov has received multiple academic recognitions for excellence in research and publication. His dedication to advancing AI-driven optimization techniques positions him as a leading researcher in intelligent systems and computational innovation, with ongoing contributions to the digital transformation of data management and predictive modeling.

Profiles : Google Scholar | Scopus

Featured Publications

khatov, A. R., Nazarov, F. M., & Rashidov, A. (2021). Mechanisms of information reliability in big data and blockchain technologies. In Proceedings of the 2021 International Conference on Information Science and Communications.

Akhatov, A. R., Nazarov, F. M., & Rashidov, A. (2021). Increasing data reliability by using big data parallelization mechanisms. In Proceedings of the 2021 International Conference on Information Science and Communications.

Rashidov, A., Akhatov, A., & Nazarov, F. (2023). The same size distribution of data based on unsupervised clustering algorithms. In The International Conference on Artificial Intelligence and Logistics.

Akhatov, A. R., Sabharwal, M., Nazarov, F. M., & Rashidov, A. (2022). Application of cryptographic methods to blockchain technology to increase data reliability. In 2nd International Conference on Advance Computing and Innovative Technologies in Engineering.

Dagur, A., Shukla, D. K., Makhmadiyarovich, N. F., & Rustamovich, A. A. (2024). Artificial intelligence and information technologies: Proceedings of the 1st International Conference on Artificial Intelligence and Information Technologies (ICAIIT 2023). CRC Press.