BUSINESS INFORMATION SYSTEMS CLUSTER
The Games Cluster
The Games Cluster conducts research in information and communication technologies, design, psychology, and human-computer interaction related to games and gamification. The cluster’s research areas include gamification (the use of game design principles in systems that primarily support non-game tasks), development of new methods and tools for improving player testing and user research in games and entertainment systems, gamification for human health, wellbeing, and fitness, and social relationship-building gamification to build relationships and foster social interaction in groups.
The Games Cluster conducts research in information and communication technologies, design, psychology, and human-computer interaction related to games and gamification. The cluster’s research areas include gamification (the use of game design principles in systems that primarily support non-game tasks), development of new methods and tools for improving player testing and user research in games and entertainment systems, gamification for human health, wellbeing, and fitness, and social relationship-building gamification to build relationships and foster social interaction in groups.
Cluster Members
Olga Yugay
Lecturer
Lecturer
Email: oyugay@wiut.uz
Akmal Salikhov
Lecturer
Lecturer
Email:
Timur Martinez Mukimov
Research Assistant
Research Assistant
Email: mtimur@wiut.uz
IoT cluster
IoT cluster conducts research in the application of IoT solutions to solve sustainable development problems related to the improvement of quality of life, transportation problems, energy, farming, agriculture, and safety. The group studies the application of machine learning to make IoT applications far more efficient and resilient. In addition, the group works in mobile computing, cloud computing, inter-networking, and robotic systems and has direct application to the many challenges faced in real-world IoT deployments.
IoT cluster conducts research in the application of IoT solutions to solve sustainable development problems related to the improvement of quality of life, transportation problems, energy, farming, agriculture, and safety. The group studies the application of machine learning to make IoT applications far more efficient and resilient. In addition, the group works in mobile computing, cloud computing, inter-networking, and robotic systems and has direct application to the many challenges faced in real-world IoT deployments.
Cluster Members
Shirin Primkulova
Course Leader
Course Leader
Email: sprimkulova@wiut.uz
Vasiliy Kuznetsov
Senior Lecturer
Senior Lecturer
Email: vkuznetsov@wiut.uz
Bunyod Khoshimkhujaev
Lecturer
Lecturer
Email: bkhoshimkhujaev@wiut.uz
Timur Martinez Mukimov
Research Assistant
Research Assistant
Email: mtimur@wiut.uz
The Data Cluster
The Data Cluster conducts the research to manage large amounts of traditional and non-traditional data, including temporal, spatial, spatio-temporal, dimensional, multimedia, and semi-structured data. The cluster's research objective is to develop techniques that meet primarily data management needs posed by data-intensive applications.
The Data Cluster conducts the research to manage large amounts of traditional and non-traditional data, including temporal, spatial, spatio-temporal, dimensional, multimedia, and semi-structured data. The cluster's research objective is to develop techniques that meet primarily data management needs posed by data-intensive applications.
Cluster Members
Dilshod Ibragimov
Head of Subject Area
Head of Subject Area
Email: dibragimov@wiut.uz
Dmitriy Pochitaev
Senior Lecturer
Senior Lecturer
Email: dpochitaev@wiut.uz
Computational Intelligence and Machine Learning Cluster
Computational Intelligence and Machine Learning Cluster at WIUT, Uzbekistan focuses on nature-inspired computational methods with machine learning approaches, including reinforcement learning. Both fundamental and applied research is being conducted in this cluster. Our research addresses fundamental issues about how to design, use, and understand intelligent systems made up by autonomous machines. Application areas include (but are not limited to) robotics and the health-care domain. In particular, we work in evolutionary computing, machine learning and complex systems for optimization, modeling, robotics and sensory data processing.
Computational Intelligence and Machine Learning Cluster at WIUT, Uzbekistan focuses on nature-inspired computational methods with machine learning approaches, including reinforcement learning. Both fundamental and applied research is being conducted in this cluster. Our research addresses fundamental issues about how to design, use, and understand intelligent systems made up by autonomous machines. Application areas include (but are not limited to) robotics and the health-care domain. In particular, we work in evolutionary computing, machine learning and complex systems for optimization, modeling, robotics and sensory data processing.
Cluster Members
Djumanov Abdumalik
Course Leader
Course Leader
Email: adjumanov@wiut.uz
Abduvaliev Said
Lecturer
Lecturer
Email: sabduvaliev@wiut.uz
