Laboratory of
Artificial Intelligence & Information Technology

• ABOUT.
  
  The Artificial Intelligence and Information Technologies Laboratory is a leading research center specializing in the development and implementation of advanced AI technologies. Our mission is to push the boundaries of science and technology by creating innovative solutions for complex problems across various industries.
  Our team consists of highly skilled professionals, including scientists, engineers, and researchers, who collaborate to achieve common goals. We strive to collaborate with academic institutions, industry partners, and government organizations to ensure technology transfer and promote the development of AI on a global scale.
  We take pride in our achievements and are committed to continuous improvement, applying the latest scientific developments to real-world projects. The AI&IT Laboratory offers uni opportunities for young researchers and students, providing them with access to modern resources and technologies.
  We are committed to nurturing the next generation of AI experts. Our training and development programs offer young researchers and students hands-on experience with cutting-edge technologies and methodologies. Through workshops, seminars, and internships, participants gain valuable skills and knowledge that prepare them for careers in AI research and industry. We believe that investing in talent development is crucial for the sustainable growth of the AI field.


• RESEARCH FIELDS.
  
  The Artificial Intelligence and Information Technologies Laboratory engages in a wide range of research covering the following key areas:
  • Machine Learning and Deep Learning:
  – development of algorithms and models for big data analysis;
  – application of deep neural networks for image recognition, natural language processing, and forecasting;
  
  
  • Computer Vision:
  – creation of systems for automatic recognition and interpretation of visual information;
  – research on image and video processing methods for applications in medicine, security, and robotics;
  
  
  • Natural Language Processing:
  – creation of models for understanding and generating human language;
  – research on methods for automatic translation, text analysis, and dialogue systems;
  
  
  • Robotics:
  – development of autonomous robots and control systems;
  – research on navigation algorithms and robot-environment interaction;
  
  
  • Distributed Systems and Computing:
  – research on distributed and parallel computing technologies to improve data processing efficiency;
  – development of platforms for cloud computing and big data handling;
  
  
  • AI Ethics and Safety:
  – study of the ethical aspects of AI usage and the development of safe algorithms; – research on data privacy issues and protection against cyber threats.
  
  
  Our laboratory actively publishes research results in leading scientific journals and participates in international conferences, facilitating the exchange of knowledge and experience with the global community. We are confident that our innovations will help create a smarter and safer future.


• COLLABORATIONS.
  
  The AI&IT Laboratory actively seeks collaboration with academic institutions, industry partners, and government organizations. By working together, we aim to advance AI research and development, facilitate technology transfer, and create innovative solutions for various sectors. We welcome opportunities for joint projects, knowledge exchange, and strategic partnerships that align with our mission and goals.


• PUBLICATIONS.
  
  The AI&IT Laboratory actively publishes its research findings in leading scientific journals and participates in international conferences. Our publications cover a wide range of topics in the field of AI, including machine learning, computer vision, robotics, natural language processing, and many others. We are proud of our scientific achievements and strive to share knowledge with the global community, contributing to the advancement of science and technology. Some of our recent publications include: energy future.

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  1. Opanasenko V.M., Fazilov S., Radjabov S., Kakharov S. Multilevel Face Recognition System //Cybernetics and Systems Analysis, 2024, 60(1), p.175–181. https://doi.org/10.1007/s10559-024-00655-w.
  
  

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  2. Fazilov Sh., Mirzaev O., Radjabov S., Akimishev G., Meliev F. Family of recognition algorithms based on the selection of two-dimensional representative pseudo-objects in the training set //Procedia Computer Science 234 (2024) 148-155.
  
  

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  3. Fazilov Sh., Mirzaev O., Radjabov S., Mirzayeva G., Rabbimov I. Construction of a recognition algorithm based on the assessment of the interdependence between local elements of the face image //Procedia Computer Science 234 (2024) 131-139.
  
  

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  4. Mirzaev O., Radjabov S., Mirzaev N., Rabbimov I., Baratov J. Construction of statistical recognition algorithms based on two-dimensional threshold functions //Procedia Computer Science 234 (2024) 123-130.
  
  

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  5. Mirzaev O., Radjabov S., Mirzaev N., Meliev F., Tillavoldiev A. A family of recognition algorithms based on the construction of k-dimensional threshold rules //Procedia Computer Science 237 (2024) 610-617.
  
  

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  6. Mirzaev N., Radjabov S., Nurmukhamedov T., Parsiyev G., Mirzaeva G. Algorithms for plant disease diagnostics by leaf image //BIO Web of Conferences, 2024, 93, 01010. https://doi.org/10.1051/bioconf/20249301010
  
  

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  7. Radjabov S.S., Dadaxanov M.X., Mardiyev A.Sh. Qo’lyozma matni tasviri sifatini oshirishning samarali algoritmini tanlash //Al-Farg’oniy avlodlari. – Farg’ona, 2024. – T. 1, №2. – 255-260 b.
  
  

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