Adaptive routing of autonomous connected vehicles for safe and efficient transportation systems in uncertain and dynamic environments
Unexpected traffic incidents and the consequent congestion have significant negative impact on the economy and the quality of people’s lives. Transportation systems can be improved by technologies of autonomous and connected vehicles, which allow vehicular control and communications, and enable effective information dissemination among vehicles. Adaptive vehicle routing is one of the most promising applications of such technologies to achieve better safety and efficiency of transportation systems.
Supported by the Russian Science Foundation under Grant No. 15-11-10032 from 2015-2017.
The explosive growth of communication technology and the Internet of Things is driving a sweeping wave of transformation. The increasing and diversified needs in cities require many applications to understand their users well. This project aims to leverage online and offline user and business entity data for recommendation, which adapts to the dynamics of mobile environment as well as user preferences.
Large-scale Graph Mining
Graph is a ubiquitous model to represent linked relationships and data, which is used almost everywhere. The huge amounts of graph data give prominence to the study of understanding and mining large-scale graphs. This project aims to develop efficient graph mining algorithms, including graph summarization and compression to ease storage, graph clustering, graph pattern mining, and visualization.
SCALING PRIVACY PROTECTTION OF SOCIAL NETWORK DATA FROM GENERATION TO MANAGEMENT
In the project framework, research group will develop methods of large random static and dynamic networks parallel generation. This research will help to solve the problem of personal data protection in social networks. Besides, it will serve as a tool to derive mathematic models in the theory of computing systems. In future, research results can be used to scale the process of network generation.
Supported by the Russian Foundation for Basic Research under Grant No.№ 31 16-37-60089\15 from 04.12.2016
CoPI: Sadegh Nobari
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