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The Data Science and Information Systems (Dainfos) Lab focuses on large-scale data management and data-driven analytics by conducting fundamental and cutting-edge research in databases, data mining, machine learning, Web mining, information retrieval, and natural language processing.

Our Goals and Speciality

Our goals: designing efficient and scalable algorithms, making sense of data for data-intensive applications. The following lists the research areas with applications that we are focusing currently:

Data mining and machine learning algorithms
– social networks mining, data integration, and analysis
– multi-core parallel algorithms
– distributed algorithms
– randomization and approximation
– data simplification and summarization
– data visulization
– graph mining, tensor-based methods
– other methods
applications: any data mining tasks including marketing, data visulization, outlier detection, recommendation, OLAP, etc.

Query processing and Searching
– building search engines
– textual and image/multimedia data retrieval
– data ranking
– entity recognition
– data integration
– query expression
– streaming/complex event processing
applications: search engine, business process management, model verification, etc.

Operation Management
– smart routing algorithms
– listing and selection
– scheduling
– others
applications: Logistics, transportation, supply chain, production, etc.

Spatio-temporal data management
– data indexing
– data compression
– 3D modeling, 2D/3D data visualization
– data warehouse
applications: mobility analysis, mobile advertising, moving objects, mapping, etc.

Data privacy and protection
– query preserved data encryption
– data sharing
– cloud data management
– graph data protection
applications: cloud computing, social networks, etc.

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